{ "schemaVersion": "deck-intelligence.v1", "id": "019dd923-5ca1-7489-b633-7fa84bbf490b", "slug": "4c8c92dad640bf3f", "title": "The art of AI maturity Advancing from practice to performance North America", "subtitle": "Accenture", "author": "Accenture", "pageCount": 40, "kind": "consulting-deck", "orientation": "landscape", "aspectRatio": 1.778, "document": { "id": "019dd923-5ca1-7489-b633-7fa84bbf490b", "slug": "4c8c92dad640bf3f", "title": "The art of AI maturity Advancing from practice to performance North America", "rawTitle": "The art of AI maturity Advancing from practice to performance North America", "authorId": "Accenture", "authorName": "Accenture", "authorDisplay": "Accenture", "kind": { "slug": "consulting-deck", "label": "Consulting deck" }, "sourceType": { "slug": "strategy_consulting", "label": "Strategy consulting" }, "fileName": "The-art-of-AI-maturity-Advancing-from-practice-to-performance-North-America.pdf", "sourceUrl": "https://www.accenture.com/content/dam/system-files/acom/custom-code/ai-maturity/Accenture-Art-AI-Maturity-NA.pdf", "sourceDate": null, "presentationDate": null, "ingestedAt": "2026-04-23 20:51:26+00", "status": "ready", "pageCount": 40, "orientation": "landscape", "aspectRatio": 1.778, "targetCompany": null, "targetTicker": null, "metadata": { "local_root": "/tmp/legacy-images/4c8c92dad640bf3f", "origin_corpus": "consulting" } }, "coverage": { "pageCount": 40, "pagesIndexed": 40, "pagesWithImages": 40, "pagesWithMetadata": 40, "imageCoveragePct": 100, "metadataCoveragePct": 100, "componentCount": 259, "chartCount": 6, "metricSlides": 23, "toolMatches": 99, "documentToolMatches": 0, "frameworkMatches": 13, "arcMatches": 2, "beatMatches": 8, "loopMatches": 6, "patternMatches": 0, "storymakersMatch": true, "scoreAvailable": true, "reviewAvailable": true, "activistThesisAvailable": false, "pitchdeckMetadataAvailable": false, "pitchdeckProfileAvailable": false }, "blocks": [], "matches": { "arcs": [ { "arc": { "name": "The Consultant's Gambit", "slug": "consultants-gambit", "status": "active", "bestFor": "Business cases, project proposals, strategic recommendations", "canonId": "019dd956-5e0a-73c8-b305-81c38c959e9c", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "Situation & Context -> Problem & Complication -> Solution & Approach -> Evidence & Proof -> Impact & Next Steps", "description": null, "familyLabel": null, "categoryName": "Strategy & Business", "categorySlug": "strategy-business" }, "matchId": "019dd95a-0542-7728-a78e-666792080e8f", "evidence": "Classic SCR-evidence-recs flow: context p3-8, complication p9-13 (only 7% are Achievers), proof p14-17 (50% revenue lift), 5 recs p20-28, impact p29-32.", "isPrimary": true, "confidence": 88, "extraction": { "at": "2026-04-29 13:07:28.977035+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null } }, { "arc": { "name": "The Triple Take", "slug": "triple-take", "status": "active", "bestFor": "Data-driven presentations, research findings", "canonId": "019dd956-6221-73ad-bc12-378f8eb1f018", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "The Facts (What) -> The Implications (So What) -> The Action (Now What)", "description": null, "familyLabel": null, "categoryName": "Analysis & Information", "categorySlug": "analysis-information" }, "matchId": "019dd95a-0542-7728-a78e-68cfbfb51150", "evidence": "Facts (AI is here, 7% are Achievers) -> Implications (Achievers outperform) -> Action (5 factors + assess yourself).", "isPrimary": false, "confidence": 60, "extraction": { "at": "2026-04-29 13:07:28.977035+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null } } ], "beats": [ { "to": 8, "arc": { "name": "The Consultant's Gambit", "slug": "consultants-gambit", "status": "active", "bestFor": "Business cases, project proposals, strategic recommendations", "canonId": "019dd956-5e0a-73c8-b305-81c38c959e9c", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "Situation & Context -> Problem & Complication -> Solution & Approach -> Evidence & Proof -> Impact & Next Steps", "description": null, "familyLabel": null, "categoryName": "Strategy & Business", "categorySlug": "strategy-business" }, "from": 3, "name": "Situation & Context", "beatId": "019dd95a-0682-776c-8e32-88fc09ca9afe", "matchId": "019dd95a-0542-7728-a78e-666792080e8f", "beatType": { "name": "Situation & Context", "slug": "consultants-gambit-situation-context", "status": "active", "canonId": "019dd9b8-05ae-741b-992d-65ee83c639b3", "version": 1, "description": null }, "evidence": "AI is essential, transformation 16 months faster than digital.", "position": 1, "isPrimaryArc": true, "parentBeatType": { "name": "Setup", "slug": "setup", "status": "active", "canonId": "019dd9b8-020e-7505-af9b-d9b9a4679bcc", "version": 1, "description": "Where the deck grounds the reader before doing anything else. Almost every arc opens here." }, "alignedBlockIds": null, "matchConfidence": 88 }, { "to": 13, "arc": { "name": "The Consultant's Gambit", "slug": "consultants-gambit", "status": "active", "bestFor": "Business cases, project proposals, strategic recommendations", "canonId": "019dd956-5e0a-73c8-b305-81c38c959e9c", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "Situation & Context -> Problem & Complication -> Solution & Approach -> Evidence & Proof -> Impact & Next Steps", "description": null, "familyLabel": null, "categoryName": "Strategy & Business", "categorySlug": "strategy-business" }, "from": 9, "name": "Problem & Complication", "beatId": "019dd95a-0682-776c-8e32-8d747bbd76a7", "matchId": "019dd95a-0542-7728-a78e-666792080e8f", "beatType": { "name": "Problem & Complication", "slug": "consultants-gambit-problem-complication", "status": "active", "canonId": "019dd9b8-064a-777f-a374-e9a8c43dedd4", "version": 1, "description": null }, "evidence": "AI maturity defined; only 7% qualify as Achievers (Fig 3 2x2).", "position": 2, "isPrimaryArc": true, "parentBeatType": { "name": "Complication", "slug": "complication", "status": "active", "canonId": "019dd9b8-0275-7709-b2d6-4f77c3fc7579", "version": 1, "description": "The point in the narrative where the audience should feel discomfort. Required for argumentative arcs." }, "alignedBlockIds": null, "matchConfidence": 88 }, { "to": 17, "arc": { "name": "The Consultant's Gambit", "slug": "consultants-gambit", "status": "active", "bestFor": "Business cases, project proposals, strategic recommendations", "canonId": "019dd956-5e0a-73c8-b305-81c38c959e9c", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "Situation & Context -> Problem & Complication -> Solution & Approach -> Evidence & Proof -> Impact & Next Steps", "description": null, "familyLabel": null, "categoryName": "Strategy & Business", "categorySlug": "strategy-business" }, "from": 14, "name": "Evidence & Proof", "beatId": "019dd95a-0682-776c-8e32-901ded58915f", "matchId": "019dd95a-0542-7728-a78e-666792080e8f", "beatType": { "name": "Solution & Approach", "slug": "consultants-gambit-solution-approach", "status": "active", "canonId": "019dd9b8-071c-7161-9184-580fdac7a4f9", "version": 1, "description": null }, "evidence": "Achievers enjoy 50% greater revenue growth, scale pilots more, lead on sustainability.", "position": 3, "isPrimaryArc": true, "parentBeatType": { "name": "Turn", "slug": "turn", "status": "active", "canonId": "019dd9b8-0396-702b-ac2f-9901f8dd8b54", "version": 1, "description": "The pivot — solution proposed, catalyst introduced, decision made. Common (15/20 arcs) but not universal: Triple-take, AIDA, PAS, Voyage-return and Pixar substitute it with a strong reflection or development beat." }, "alignedBlockIds": null, "matchConfidence": 88 }, { "to": 28, "arc": { "name": "The Consultant's Gambit", "slug": "consultants-gambit", "status": "active", "bestFor": "Business cases, project proposals, strategic recommendations", "canonId": "019dd956-5e0a-73c8-b305-81c38c959e9c", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "Situation & Context -> Problem & Complication -> Solution & Approach -> Evidence & Proof -> Impact & Next Steps", "description": null, "familyLabel": null, "categoryName": "Strategy & Business", "categorySlug": "strategy-business" }, "from": 18, "name": "Solution & Approach", "beatId": "019dd95a-0682-776c-8e32-9637b6b2b41d", "matchId": "019dd95a-0542-7728-a78e-666792080e8f", "beatType": { "name": "Evidence & Proof", "slug": "consultants-gambit-evidence-proof", "status": "active", "canonId": "019dd9b8-07b1-7688-8e1e-7637fec3802a", "version": 1, "description": null }, "evidence": "Five success factors: leadership, talent, AI core, responsible AI, investment.", "position": 4, "isPrimaryArc": true, "parentBeatType": { "name": "Evidence", "slug": "evidence", "status": "active", "canonId": "019dd9b8-03f9-772a-b84a-4f07b415b77a", "version": 1, "description": "A dedicated proof beat exists in only ~4 arcs (Gambit, Sequoia, AIDA, Monroes). Other arcs embed evidence inline within development." }, "alignedBlockIds": null, "matchConfidence": 88 }, { "to": 32, "arc": { "name": "The Consultant's Gambit", "slug": "consultants-gambit", "status": "active", "bestFor": "Business cases, project proposals, strategic recommendations", "canonId": "019dd956-5e0a-73c8-b305-81c38c959e9c", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "Situation & Context -> Problem & Complication -> Solution & Approach -> Evidence & Proof -> Impact & Next Steps", "description": null, "familyLabel": null, "categoryName": "Strategy & Business", "categorySlug": "strategy-business" }, "from": 29, "name": "Impact & Next Steps", "beatId": "019dd95a-0682-776c-8e32-99b1f355aefb", "matchId": "019dd95a-0542-7728-a78e-666792080e8f", "beatType": { "name": "Impact & Next Steps", "slug": "consultants-gambit-impact-next-steps", "status": "active", "canonId": "019dd9b8-0849-7728-9ee9-fd1609c4c655", "version": 1, "description": null }, "evidence": "7%->20% projection, 'practice makes progress', C-suite assessment table p32.", "position": 5, "isPrimaryArc": true, "parentBeatType": { "name": "Resolution", "slug": "resolution", "status": "active", "canonId": "019dd9b8-045d-703b-8dd7-e92aba3ba91b", "version": 1, "description": "How the deck ends. Required in 19/20 arcs. The exception (Sparkline) ends with new bliss which is functionally a resolution." }, "alignedBlockIds": null, "matchConfidence": 88 }, { "to": 13, "arc": { "name": "The Triple Take", "slug": "triple-take", "status": "active", "bestFor": "Data-driven presentations, research findings", "canonId": "019dd956-6221-73ad-bc12-378f8eb1f018", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "The Facts (What) -> The Implications (So What) -> The Action (Now What)", "description": null, "familyLabel": null, "categoryName": "Analysis & Information", "categorySlug": "analysis-information" }, "from": 3, "name": "The Facts (What)", "beatId": "019dd95a-0682-776c-8e32-9ee324fcf070", "matchId": "019dd95a-0542-7728-a78e-68cfbfb51150", "beatType": { "name": "The Facts (What)", "slug": "triple-take-the-facts-what", "status": "active", "canonId": "019dd9b8-092b-754c-8eaa-ede3ffdcb060", "version": 1, "description": null }, "evidence": "AI adoption stats and segmentation of the 2,000-firm sample.", "position": 1, "isPrimaryArc": false, "parentBeatType": { "name": "Setup", "slug": "setup", "status": "active", "canonId": "019dd9b8-020e-7505-af9b-d9b9a4679bcc", "version": 1, "description": "Where the deck grounds the reader before doing anything else. Almost every arc opens here." }, "alignedBlockIds": null, "matchConfidence": 60 }, { "to": 17, "arc": { "name": "The Triple Take", "slug": "triple-take", "status": "active", "bestFor": "Data-driven presentations, research findings", "canonId": "019dd956-6221-73ad-bc12-378f8eb1f018", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "The Facts (What) -> The Implications (So What) -> The Action (Now What)", "description": null, "familyLabel": null, "categoryName": "Analysis & Information", "categorySlug": "analysis-information" }, "from": 14, "name": "The Implications (So What)", "beatId": "019dd95a-0682-776c-8e32-a1d6fecab517", "matchId": "019dd95a-0542-7728-a78e-68cfbfb51150", "beatType": { "name": "The Implications (So What)", "slug": "triple-take-the-implications-so-what", "status": "active", "canonId": "019dd9b8-09c7-75cd-8c7b-ae0e23cca2b8", "version": 1, "description": null }, "evidence": "Achievers outperform peers on revenue and sustainability.", "position": 2, "isPrimaryArc": false, "parentBeatType": { "name": "Reflection", "slug": "reflection", "status": "active", "canonId": "019dd9b8-0510-73fd-8d00-1c7e45f7bc98", "version": 1, "description": "The \"so what\" beat. Used by analytical arcs (Triple-take, Onion) and learning arcs (Voyage-return, Tragedy)." }, "alignedBlockIds": null, "matchConfidence": 60 }, { "to": 32, "arc": { "name": "The Triple Take", "slug": "triple-take", "status": "active", "bestFor": "Data-driven presentations, research findings", "canonId": "019dd956-6221-73ad-bc12-378f8eb1f018", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "The Facts (What) -> The Implications (So What) -> The Action (Now What)", "description": null, "familyLabel": null, "categoryName": "Analysis & Information", "categorySlug": "analysis-information" }, "from": 18, "name": "The Action (Now What)", "beatId": "019dd95a-0682-776c-8e32-a6c160fdc8c9", "matchId": "019dd95a-0542-7728-a78e-68cfbfb51150", "beatType": { "name": "The Action (Now What)", "slug": "triple-take-the-action-now-what", "status": "active", "canonId": "019dd9b8-0a5e-735a-bf53-3a1ba629b7aa", "version": 1, "description": null }, "evidence": "Five success factors plus C-suite self-assessment.", "position": 3, "isPrimaryArc": false, "parentBeatType": { "name": "Resolution", "slug": "resolution", "status": "active", "canonId": "019dd9b8-045d-703b-8dd7-e92aba3ba91b", "version": 1, "description": "How the deck ends. Required in 19/20 arcs. The exception (Sparkline) ends with new bliss which is functionally a resolution." }, "alignedBlockIds": null, "matchConfidence": 60 } ], "loops": [ { "to": 5, "from": 3, "loop": { "name": "03_aha_moment", "slug": "03-aha-moment", "status": "active", "bestFor": "Data-heavy sections, research findings, analytical arguments", "canonId": "019dd956-66f4-7668-ab25-cec9c996c0bc", "version": 1, "bodyDocId": "019df22a-2420-77be-bc41-ded96d08cb21", "structure": "The Problem/Question -> What the Data Shows -> The Insight", "description": "Establish a tension, present data, then deliver the insight that changes everything", "familyLabel": null, "categoryName": "Narrative", "categorySlug": "narrative" }, "matchId": "019dd95a-07fe-70ce-8d3a-516cbcb3d4fa", "evidence": "Problem framing (AI ubiquity) -> data (7% Achievers) -> insight (5 differentiators).", "position": 1, "objective": "Open with the question and the 7%/20% reveal", "confidence": 75, "extraction": { "at": "2026-04-29 13:07:29.547081+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null } }, { "to": 8, "from": 7, "loop": { "name": "15_why_now", "slug": "15-why-now", "status": "active", "bestFor": "Sales pitches, fundraising, requesting immediate budget approval", "canonId": "019dd956-6c00-70cd-bd42-6bacc4af726f", "version": 1, "bodyDocId": "019df22a-2420-77be-bc41-ded96d08cb21", "structure": "The Context (Trends) -> The Trigger Event -> The Window of Opportunity", "description": "Create temporal urgency by proving that the window of opportunity is opening or closing", "familyLabel": null, "categoryName": "Urgency", "categorySlug": "urgency" }, "matchId": "019dd95a-07fe-70ce-8d3a-55ad19dc92c8", "evidence": "Trends (CEO mentions, 75% integration), trigger (early ROI), 16-month window vs digital.", "position": 2, "objective": "Justify urgency of acting on AI maturity", "confidence": 80, "extraction": { "at": "2026-04-29 13:07:29.547081+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null } }, { "to": 13, "from": 10, "loop": { "name": "30_2x2_matrix", "slug": "30-2x2-matrix", "status": "active", "bestFor": "Portfolio analysis, prioritization, strategic positioning", "canonId": "019dd956-7225-756a-9cc7-1e6d3f039818", "version": 1, "bodyDocId": "019df22a-2420-77be-bc41-ded96d08cb21", "structure": "Dimension 1 (X-axis) -> Dimension 2 (Y-axis) -> The Four Quadrants -> The Sweet Spot", "description": "Plot options on two critical dimensions to reveal the optimal quadrant", "familyLabel": null, "categoryName": "Consulting Framework", "categorySlug": "consulting-framework" }, "matchId": "019dd95a-07fe-70ce-8d3a-5987e0314b42", "evidence": "Fig 3 2x2 with axes AI Foundation/Differentiation defines Achievers/Innovators/Builders/Experimenters.", "position": 3, "objective": "Segment firms via the AI Foundation x Differentiation 2x2", "confidence": 92, "extraction": { "at": "2026-04-29 13:07:29.547081+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null } }, { "to": 17, "from": 15, "loop": { "name": "39_benchmark_gap", "slug": "39-benchmark-gap", "status": "active", "bestFor": "Performance improvement, competitive analysis, target setting", "canonId": "019dd956-75a4-7522-8d1a-af94da4703e9", "version": 1, "bodyDocId": "019df22a-2420-77be-bc41-ded96d08cb21", "structure": "Our Performance -> Industry Average -> Best-in-Class -> The Gap = The Opportunity", "description": "Compare performance against best-in-class to quantify the opportunity", "familyLabel": null, "categoryName": "Comparison", "categorySlug": "comparison" }, "matchId": "019dd95a-07fe-70ce-8d3a-5d3edf07f6fa", "evidence": "50% greater revenue growth, 5% more likely to scale pilots, capability matrix vs peers.", "position": 4, "objective": "Quantify the performance gap between Achievers and others", "confidence": 85, "extraction": { "at": "2026-04-29 13:07:29.547081+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null } }, { "to": 28, "from": 20, "loop": { "name": "40_mece_breakdown", "slug": "40-mece-breakdown", "status": "active", "bestFor": "Problem structuring, ensuring completeness, strategic analysis", "canonId": "019dd956-763c-765e-8b68-6ee3ae1ef184", "version": 1, "bodyDocId": "019df22a-2420-77be-bc41-ded96d08cb21", "structure": "The Whole -> Category A (distinct) -> Category B (distinct) -> Category C (distinct) -> Complete Coverage", "description": "Divide a complex topic into mutually exclusive, collectively exhaustive categories", "familyLabel": null, "categoryName": "Consulting Framework", "categorySlug": "consulting-framework" }, "matchId": "019dd95a-07fe-70ce-8d3a-633fdd7803ae", "evidence": "Five labelled 'Success Factor 0X' sections each pairing recommendation + case study.", "position": 5, "objective": "Lay out five MECE success factors with evidence and cases", "confidence": 88, "extraction": { "at": "2026-04-29 13:07:29.547081+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null } }, { "to": 32, "from": 29, "loop": { "name": "24_time_machine", "slug": "24-time-machine", "status": "active", "bestFor": "Vision casting, long-term strategy, investment pitches", "canonId": "019dd956-6f7f-70b2-b087-a16fe20515a7", "version": 1, "bodyDocId": "019df22a-2420-77be-bc41-ded96d08cb21", "structure": "Fast Forward to Success -> What Made It Possible -> Back to Today's Decision", "description": "Transport the audience to a future state where your solution has already succeeded", "familyLabel": null, "categoryName": "Vision", "categorySlug": "vision" }, "matchId": "019dd95a-07fe-70ce-8d3a-67238c35e578", "evidence": "Full-bleed 7%->20% by 2024 vision slide, then C-suite questions to act now.", "position": 6, "objective": "Cast forward to 2024 vision and route back to today's assessment", "confidence": 78, "extraction": { "at": "2026-04-29 13:07:29.547081+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null } } ], "tools": [ { "tool": { "name": "Anchoring Bias", "slug": "anchoring-bias", "status": "active", "bestFor": null, "canonId": "019dd956-9254-73de-8f1b-c7250f8f4c9c", "version": 1, "bodyDocId": null, "description": "First piece of information becomes reference point for all subsequent judgments", "familyLabel": null, "categoryName": "Block", "categorySlug": "block" }, "agent": "Architect", "layer": "block", "agents": [ "Architect", "Storyteller" ], "matchId": "019dd95a-0f08-73d3-987c-4ad436a3aaaa", "evidence": "Sets '16 months faster' as the framing anchor for the deck.", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 65, "extraction": { "at": "2026-04-29 13:07:31.336924+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 3, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "Pyramid Principle", "slug": "pyramid-principle", "status": "active", "bestFor": "When the document has a single governing decision or recommendation the reader is asked to accept, and the case can be decomposed into a small number of clean groups. Strategy decks, board memos, investment committee papers.", "canonId": "019dd956-7cbd-7219-a477-c871e2bc1aff", "version": 1, "bodyDocId": "88b6ac56-b880-46f9-8621-ef3491ab6235", "description": "Lead with the answer; group three to five MECE supports beneath it; recurse one level down. Top-down hierarchical structure for any document with a single recommendation.", "familyLabel": null, "categoryName": "Block", "categorySlug": "block" }, "agent": "Architect", "layer": "block", "agents": [ "Architect" ], "matchId": "019dd95a-0f08-73d3-987c-4d3407f92a6b", "evidence": "Top-line answer (NA perspective on AI maturity) precedes supporting data.", "pageRefs": null, "priority": "Core", "whenToUse": "When the document has a single governing decision or recommendation the reader is asked to accept, and the case can be decomposed into a small number of clean groups. Strategy decks, board memos, investment committee papers.", "confidence": 60, "extraction": { "at": "2026-04-29 13:07:31.336924+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 3, "whyItWorks": "Solves the two failure modes of expert communication at once: (1) the long climb where readers wait pages for the answer, and (2) logical mush from non-MECE groupings. Progressive disclosure lets a reader stop at any depth and get the right information.", "antipattern": "Chronological structure (\"what we did, what we found, what we conclude\") instead of logical hierarchy. Top-of-pyramid that is a topic (\"strategic options\") instead of an answer (\"pursue Option B because...\"). Non-MECE supports that overlap or fail to cover the universe.", "cardinality": null, "narrativePurpose": "Transfer conviction with minimum reader effort by mirroring how decision-makers consume information: answer first, scaffolding behind." }, { "tool": { "name": "Curiosity Gap", "slug": "curiosity-gap", "status": "active", "bestFor": null, "canonId": "019dd956-9703-74ef-8b85-96dfd8525025", "version": 1, "bodyDocId": null, "description": "People seek missing information - create open questions that demand resolution", "familyLabel": null, "categoryName": "Block", "categorySlug": "block" }, "agent": "Storyteller", "layer": "block", "agents": [ "Storyteller" ], "matchId": "019dd95a-0f08-73d3-987c-6ba60a6140df", "evidence": "Question title plus enumerated answers create resolution-seeking tension.", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 75, "extraction": { "at": "2026-04-29 13:07:31.336924+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 5, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "Scarcity", "slug": "scarcity", "status": "active", "bestFor": null, "canonId": "019dd956-9610-7038-a580-6ef34d95f742", "version": 1, "bodyDocId": null, "description": "Limited availability increases perceived value - time limits and exclusivity", "familyLabel": null, "categoryName": "Block", "categorySlug": "block" }, "agent": "Storyteller", "layer": "block", "agents": [ "Storyteller" ], "matchId": "019dd95a-0f08-73d3-987c-adda7a47f67d", "evidence": "Only 7% framing makes Achiever status feel scarce and aspirational.", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 75, "extraction": { "at": "2026-04-29 13:07:31.336924+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 11, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "Storytelling Effect", "slug": "storytelling-effect", "status": "active", "bestFor": null, "canonId": "019dd956-981b-74f9-9096-5c8df03dab5a", "version": 1, "bodyDocId": null, "description": "Stories are remembered up to 22x better than facts alone", "familyLabel": null, "categoryName": "Block", "categorySlug": "block" }, "agent": "Storyteller", "layer": "block", "agents": [ "Storyteller" ], "matchId": "019dd95a-0f08-73d3-987c-c8442947cc38", "evidence": "First in a sequence of company vignettes used as memory hooks.", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 70, "extraction": { "at": "2026-04-29 13:07:31.336924+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 13, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "MECE Principle", "slug": "mece-principle", "status": "active", "bestFor": null, "canonId": "019dd956-7c60-71a8-8758-c79d914489c9", "version": 1, "bodyDocId": null, "description": "Mutually Exclusive, Collectively Exhaustive - ensuring complete, non-overlapping structure", "familyLabel": null, "categoryName": "Block", "categorySlug": "block" }, "agent": "Architect", "layer": "block", "agents": [ "Architect" ], "matchId": "019dd95a-0f08-73d3-987d-0df2f98702da", "evidence": "Five labelled, non-overlapping success factors structure the section.", "pageRefs": null, "priority": "Core", "whenToUse": null, "confidence": 80, "extraction": { "at": "2026-04-29 13:07:31.336924+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 20, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "Information Gap Theory", "slug": "information-gap-theory", "status": "active", "bestFor": null, "canonId": "019dd956-a856-765e-88bc-f703bdfec762", "version": 1, "bodyDocId": null, "description": "Curiosity arises from gap between what we know and want to know", "familyLabel": null, "categoryName": "Loop", "categorySlug": "loop" }, "agent": "Storyteller", "layer": "loop", "agents": [ "Storyteller" ], "matchId": "019dd95a-0f08-73d3-987c-446a4fc7d98e", "evidence": "Opens loop by raising the AI-maturity question without answering.", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 70, "extraction": { "at": "2026-04-29 13:07:31.336924+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 3, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "Chunking", "slug": "chunking", "status": "active", "bestFor": null, "canonId": "019dd956-abab-72ce-b64c-2924cc83cf39", "version": 1, "bodyDocId": null, "description": "Information grouped into chunks is remembered better - structure content in digestible units", "familyLabel": null, "categoryName": "Loop", "categorySlug": "loop" }, "agent": "Architect", "layer": "loop", "agents": [ "Architect" ], "matchId": "019dd95a-0f08-73d3-987c-62e9b857db7f", "evidence": "Five numbered success factors presented as a memorable list.", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 80, "extraction": { "at": "2026-04-29 13:07:31.336924+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 5, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "Foreshadowing", "slug": "foreshadowing", "status": "active", "bestFor": null, "canonId": "019dd956-a406-7159-bb8c-aeef05df2563", "version": 1, "bodyDocId": null, "description": "Planting hints of what's to come for later payoff", "familyLabel": null, "categoryName": "Loop", "categorySlug": "loop" }, "agent": "Storyteller", "layer": "loop", "agents": [ "Storyteller" ], "matchId": "019dd95a-0f08-73d3-987c-673e1809a76b", "evidence": "Lists the five factors that Section 4 will unpack one by one.", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 80, "extraction": { "at": "2026-04-29 13:07:31.336924+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 5, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "Causal Chain", "slug": "causal-chain", "status": "active", "bestFor": null, "canonId": "019dd956-9e98-7269-907b-8cf727e9499d", "version": 1, "bodyDocId": null, "description": "Showing how one event leads to another in sequence", "familyLabel": null, "categoryName": "Loop", "categorySlug": "loop" }, "agent": "Architect", "layer": "loop", "agents": [ "Architect" ], "matchId": "019dd95a-0f08-73d3-987c-7d59e527aa7f", "evidence": "Early ROI -> confidence -> faster adoption -> 16-month lead.", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 65, "extraction": { "at": "2026-04-29 13:07:31.336924+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 7, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "Contrast Pairs", "slug": "contrast-pairs", "status": "active", "bestFor": null, "canonId": "019dd956-9b77-70d3-88b1-f34e26f60860", "version": 1, "bodyDocId": null, "description": "Creating tension through opposites: Before↔After, Problem↔Solution, Pain↔Relief", "familyLabel": null, "categoryName": "Loop", "categorySlug": "loop" }, "agent": "Storyteller", "layer": "loop", "agents": [ "Storyteller" ], "matchId": "019dd95a-0f08-73d3-987c-de5beef91744", "evidence": "Sets up Achievers<->Experimenters contrast that drives the loop.", "pageRefs": null, "priority": "Core", "whenToUse": null, "confidence": 80, "extraction": { "at": "2026-04-29 13:07:31.336924+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 15, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "Data Story Arc", "slug": "data-story-arc", "status": "active", "bestFor": null, "canonId": "019dd956-9c30-728e-b974-d3fb123dcf5a", "version": 1, "bodyDocId": null, "description": "Context → Conflict → Insight → Implication structure for data narratives", "familyLabel": null, "categoryName": "Loop", "categorySlug": "loop" }, "agent": "Storyteller", "layer": "loop", "agents": [ "Storyteller" ], "matchId": "019dd95a-0f08-73d3-987c-e02a57d87b3b", "evidence": "Opens benchmarking arc: context, conflict (gap), insight.", "pageRefs": null, "priority": "Core", "whenToUse": null, "confidence": 70, "extraction": { "at": "2026-04-29 13:07:31.336924+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 15, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "Parallel Structure", "slug": "parallel-structure", "status": "active", "bestFor": null, "canonId": "019dd956-9f34-762a-93b7-1d8e84bbd153", "version": 1, "bodyDocId": null, "description": "Using similar grammatical structure for related ideas", "familyLabel": null, "categoryName": "Loop", "categorySlug": "loop" }, "agent": "Architect", "layer": "loop", "agents": [ "Architect" ], "matchId": "019dd95a-0f08-73d3-987d-0956cc8dd458", "evidence": "Opens 'Success Factor 01-05' template repeated through p28.", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 85, "extraction": { "at": "2026-04-29 13:07:31.336924+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 20, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "Tension Management", "slug": "tension-management", "status": "active", "bestFor": null, "canonId": "019dd956-9bd5-70ed-a5d2-1ce45853c248", "version": 1, "bodyDocId": null, "description": "Planning emotional peaks and valleys throughout the narrative", "familyLabel": null, "categoryName": "Loop", "categorySlug": "loop" }, "agent": "Storyteller", "layer": "loop", "agents": [ "Storyteller" ], "matchId": "019dd95a-0f08-73d3-987d-440ac1dc5edc", "evidence": "Contrasts current 3% with aspirational 45% to manufacture urgency.", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 60, "extraction": { "at": "2026-04-29 13:07:31.336924+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 27, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "Payoff", "slug": "payoff", "status": "active", "bestFor": null, "canonId": "019dd956-a464-704b-b1a1-e1d483709f00", "version": 1, "bodyDocId": null, "description": "Delivering on earlier setup for satisfying resolution", "familyLabel": null, "categoryName": "Loop", "categorySlug": "loop" }, "agent": "Storyteller", "layer": "loop", "agents": [ "Storyteller" ], "matchId": "019dd95a-0f08-73d3-987d-5eadf790f13d", "evidence": "Delivers on the 7%->20% promise foreshadowed back on p5.", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 70, "extraction": { "at": "2026-04-29 13:07:31.336924+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 29, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "The Turn", "slug": "the-turn", "status": "active", "bestFor": null, "canonId": "019dd956-a2b1-7787-8ff6-60ba7e50b814", "version": 1, "bodyDocId": null, "description": "Pivotal moment where perspective shifts or insight emerges", "familyLabel": null, "categoryName": "Loop", "categorySlug": "loop" }, "agent": "Storyteller", "layer": "loop", "agents": [ "Storyteller" ], "matchId": "019dd95a-0f08-73d3-987d-5951407c1cdd", "evidence": "Pivot from past data to forward-looking 2024 trajectory.", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 75, "extraction": { "at": "2026-04-29 13:07:31.336924+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 29, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "Tricolon", "slug": "tricolon", "status": "active", "bestFor": null, "canonId": "019dd956-a13d-7356-9038-da27abe565f8", "version": 1, "bodyDocId": null, "description": "Three parallel phrases of increasing length or intensity", "familyLabel": null, "categoryName": "Loop", "categorySlug": "loop" }, "agent": "Storyteller", "layer": "loop", "agents": [ "Storyteller" ], "matchId": "019dd95a-0f08-73d3-987d-6f5c5ea39eb0", "evidence": "Three parallel clauses: cloud-enabler / data-driver / AI-differentiator.", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 80, "extraction": { "at": "2026-04-29 13:07:31.336924+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 31, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "Chunking", "slug": "chunking", "status": "active", "bestFor": null, "canonId": "019dd956-abab-72ce-b64c-2924cc83cf39", "version": 1, "bodyDocId": null, "description": "Information grouped into chunks is remembered better - structure content in digestible units", "familyLabel": null, "categoryName": "Loop", "categorySlug": "loop" }, "agent": "Architect", "layer": "loop", "agents": [ "Architect" ], "matchId": "019dd95a-0f08-73d3-987d-7cd8bc816f72", "evidence": "Questions chunked into four MECE capability buckets.", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 70, "extraction": { "at": "2026-04-29 13:07:31.336924+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 32, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "Slide recipe: Cover", "slug": "cover-slide", "status": "active", "bestFor": null, "canonId": "019df269-2a08-767d-9128-e7431e6fe8a3", "version": 1, "bodyDocId": "019df269-29e5-7738-b5fa-6892e5dc8e65", "description": "The first ten seconds. Build it deliberately.", "familyLabel": "slide-recipe", "categoryName": "Slide", "categorySlug": "slide" }, "agent": "designer", "layer": "slide", "agents": [ "designer" ], "matchId": "7d6c6f14-a1de-4260-8e41-d092b097e7d6", "evidence": "This slide is a cover slide with a title, subtitle, and callout.", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 0.9, "extraction": { "at": "2026-07-16 21:02:22.342639+00", "model": "or:meta-llama/llama-4-scout", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 1, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "Action Titles", "slug": "action-titles", "status": "active", "bestFor": "Any decision-grade deliverable — strategy recommendation, board update, investment memo, M&A review, post-mortem — where the reader is being asked to agree, decide, or act and will skim the title bar at speed.", "canonId": "019dd956-ac70-700b-a608-ba58e78f5dcc", "version": 1, "bodyDocId": "816dad3c-9983-41c1-a86e-978ebd582841", "description": "The McKinsey-bred discipline of writing every slide title as a complete declarative sentence with a verb and an insight, not a topic label. Each title is a sub-claim that ladders up to the deck's governing thought; read in sequence, the titles reconstruct the executive summary.", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Architect", "layer": "slide", "agents": [ "Architect" ], "matchId": "019dd95a-0f08-73d3-987c-3cc7233b8c60", "evidence": "Subhead frames the so-what about NA pace of AI.", "pageRefs": null, "priority": "Core", "whenToUse": "Any decision-grade deliverable — strategy recommendation, board update, investment memo, M&A review, post-mortem — where the reader is being asked to agree, decide, or act and will skim the title bar at speed.", "confidence": 70, "extraction": { "at": "2026-04-29 13:07:31.336924+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 3, "whyItWorks": "Solves two failure modes at once. (1) The buried claim: action titles place the conclusion on the page before any analysis is read, so a busy reader doesn't reverse-engineer it from the chart. (2) The spineless deck: because each title is a claim, slides have to ladder up to the governing thought; logical gaps become visible as topic-shaped titles in a sequence that no longer reads as a story.", "antipattern": "Topic labels disguised as titles — Volume by quarter, Key findings, Pricing strategy, Margins have been impacted. No verb, or a passive verb with no agent, or a fact (Revenue grew 12%) without the so-what. Also: titles that overreach the chart's evidence, multi-claim X-grew-but-Y-fell welded titles, and mechanical repetition of the same X-drove-Y template across the deck.", "cardinality": null, "narrativePurpose": "Forces the deck to carry its argument in the title bar so a senior reader can extract the recommendation without opening a single slide; converts a binder of topics into a navigable pyramid where every slide is a node defending the apex." }, { "tool": { "name": "Concrete Language", "slug": "concrete-language", "status": "active", "bestFor": null, "canonId": "019dd956-bcd4-7398-9723-6aa72346170b", "version": 1, "bodyDocId": null, "description": "Using specific sensory details instead of abstract terms", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Storyteller", "layer": "slide", "agents": [ "Storyteller" ], "matchId": "019dd95a-0f08-73d3-987c-411b26009db8", "evidence": "Callout: '16 months faster than digital transformation'.", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 85, "extraction": { "at": "2026-04-29 13:07:31.336924+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 3, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "Executive summary", "slug": "executive-summary", "status": "active", "bestFor": null, "canonId": "019dd9e1-4b63-72d5-9734-da757d91ca61", "version": 1, "bodyDocId": null, "description": "A condensed view of the entire argument on a single slide / block.", "familyLabel": null, "categoryName": null, "categorySlug": null }, "agent": null, "layer": "slide", "agents": null, "matchId": "b85a6189-b3a0-4f38-b847-6838ff852d1c", "evidence": "This slide is an executive summary with a title, paragraphs, and metrics.", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 0.9, "extraction": { "at": "2026-07-16 21:02:22.465468+00", "model": "or:meta-llama/llama-4-scout", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 3, "whyItWorks": null, "antipattern": null, "cardinality": "common", "narrativePurpose": null }, { "tool": { "name": "Concrete Language", "slug": "concrete-language", "status": "active", "bestFor": null, "canonId": "019dd956-bcd4-7398-9723-6aa72346170b", "version": 1, "bodyDocId": null, "description": "Using specific sensory details instead of abstract terms", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Storyteller", "layer": "slide", "agents": [ "Storyteller" ], "matchId": "019dd95a-0f08-73d3-987c-55e495c7c15b", "evidence": "Callout quantifies '7% of firms have advanced their AI maturity'.", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 85, "extraction": { "at": "2026-04-29 13:07:31.336924+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 4, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "Core Message Extraction", "slug": "core-message-extraction", "status": "active", "bestFor": "Any slide that carries an argument or finding. The diagnostic: if the slide has a chart on it, it needs a core message. Run extraction whenever the current title is a topic (Q3 performance, Customer satisfaction) rather than a claim, or when a reader could reasonably draw more than one conclusion from the visible evidence.", "canonId": "019dd956-bc71-707d-8867-1b2e810175cf", "version": 1, "bodyDocId": "f85613cb-4b77-462f-bfe6-3b862516e1a6", "description": "The discipline of distilling raw analysis, data, or content into a single declarative sentence — the slide's core message — that the audience would walk away with if they remembered nothing else. Process, not artefact: extraction questions run on the raw content until one sentence falls out.", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Architect", "layer": "slide", "agents": [ "Architect" ], "matchId": "019dd95a-0f08-73d3-987c-5a2c44e477d2", "evidence": "Distils whole report into the 7% Achievers thesis.", "pageRefs": null, "priority": null, "whenToUse": "Any slide that carries an argument or finding. The diagnostic: if the slide has a chart on it, it needs a core message. Run extraction whenever the current title is a topic (Q3 performance, Customer satisfaction) rather than a claim, or when a reader could reasonably draw more than one conclusion from the visible evidence.", "confidence": 70, "extraction": { "at": "2026-04-29 13:07:31.336924+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 4, "whyItWorks": "Solves the two failure modes of slide writing simultaneously: the topic title (which outsources interpretation to the audience and produces three different conclusions in three different heads) and the multi-thesis stapler (which exceeds working memory and gets remembered as fragments). Aligns with how readers actually consume decks — Heath & Heath's Find the Core, the journalist's nut graf, and Minto's governing thought all converge on the same cognitive economics.", "antipattern": "Topic titles disguised as core messages (Customer satisfaction, no verb, no stake); multi-thesis sentences stapled with and; hedged sentences (may show signs of possible softening); chart-caption titles (Revenue fell 4%) that restate what the chart already shows instead of naming the so-what; meta-commentary (this slide explores...) that describes the slide rather than concluding it.", "cardinality": null, "narrativePurpose": "Forces the slide author to do the interpretive work before the slide ships, so the audience does not have to do it during the meeting. Wins the WYSIATI battle on purpose — the loudest fragment on the page becomes the author's chosen sentence rather than whichever chart label happens to be largest." }, { "tool": { "name": "Executive summary", "slug": "executive-summary", "status": "active", "bestFor": null, "canonId": "019dd9e1-4b63-72d5-9734-da757d91ca61", "version": 1, "bodyDocId": null, "description": "A condensed view of the entire argument on a single slide / block.", "familyLabel": null, "categoryName": null, "categorySlug": null }, "agent": null, "layer": "slide", "agents": null, "matchId": "6f8d1bc3-95b4-4403-97cb-eb94af3418c1", "evidence": "This slide is an executive summary with a title, paragraphs, and metrics.", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 0.9, "extraction": { "at": "2026-07-16 21:02:22.55519+00", "model": "or:meta-llama/llama-4-scout", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 4, "whyItWorks": null, "antipattern": null, "cardinality": "common", "narrativePurpose": null }, { "tool": { "name": "Opening Hooks", "slug": "opening-hooks", "status": "active", "bestFor": null, "canonId": "019dd956-aeb0-77d5-bfbd-9cd9a6be8186", "version": 1, "bodyDocId": null, "description": "Techniques to capture attention: Startling statistic, provocative question, short story, analogy, contrast", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Storyteller", "layer": "slide", "agents": [ "Storyteller" ], "matchId": "019dd95a-0f08-73d3-987c-51a8a2b475ec", "evidence": "'In fewer than 70 years...' opens with a startling time-scale frame.", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 80, "extraction": { "at": "2026-04-29 13:07:31.336924+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 4, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "Action Titles", "slug": "action-titles", "status": "active", "bestFor": "Any decision-grade deliverable — strategy recommendation, board update, investment memo, M&A review, post-mortem — where the reader is being asked to agree, decide, or act and will skim the title bar at speed.", "canonId": "019dd956-ac70-700b-a608-ba58e78f5dcc", "version": 1, "bodyDocId": "816dad3c-9983-41c1-a86e-978ebd582841", "description": "The McKinsey-bred discipline of writing every slide title as a complete declarative sentence with a verb and an insight, not a topic label. Each title is a sub-claim that ladders up to the deck's governing thought; read in sequence, the titles reconstruct the executive summary.", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Architect", "layer": "slide", "agents": [ "Architect" ], "matchId": "019dd95a-0f08-73d3-987c-5d6eed0e25d8", "evidence": "Provocative question title: 'What do AI Achievers do differently?'", "pageRefs": null, "priority": "Core", "whenToUse": "Any decision-grade deliverable — strategy recommendation, board update, investment memo, M&A review, post-mortem — where the reader is being asked to agree, decide, or act and will skim the title bar at speed.", "confidence": 80, "extraction": { "at": "2026-04-29 13:07:31.336924+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 5, "whyItWorks": "Solves two failure modes at once. (1) The buried claim: action titles place the conclusion on the page before any analysis is read, so a busy reader doesn't reverse-engineer it from the chart. (2) The spineless deck: because each title is a claim, slides have to ladder up to the governing thought; logical gaps become visible as topic-shaped titles in a sequence that no longer reads as a story.", "antipattern": "Topic labels disguised as titles — Volume by quarter, Key findings, Pricing strategy, Margins have been impacted. No verb, or a passive verb with no agent, or a fact (Revenue grew 12%) without the so-what. Also: titles that overreach the chart's evidence, multi-claim X-grew-but-Y-fell welded titles, and mechanical repetition of the same X-drove-Y template across the deck.", "cardinality": null, "narrativePurpose": "Forces the deck to carry its argument in the title bar so a senior reader can extract the recommendation without opening a single slide; converts a binder of topics into a navigable pyramid where every slide is a node defending the apex." }, { "tool": { "name": "Action Titles", "slug": "action-titles", "status": "active", "bestFor": "Any decision-grade deliverable — strategy recommendation, board update, investment memo, M&A review, post-mortem — where the reader is being asked to agree, decide, or act and will skim the title bar at speed.", "canonId": "019dd956-ac70-700b-a608-ba58e78f5dcc", "version": 1, "bodyDocId": "816dad3c-9983-41c1-a86e-978ebd582841", "description": "The McKinsey-bred discipline of writing every slide title as a complete declarative sentence with a verb and an insight, not a topic label. Each title is a sub-claim that ladders up to the deck's governing thought; read in sequence, the titles reconstruct the executive summary.", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Architect", "layer": "slide", "agents": [ "Architect" ], "matchId": "019dd95a-0f08-73d3-987c-6c4500121f00", "evidence": "Subhead asserts insight: 'AI is absolutely essential to competitive advantage'.", "pageRefs": null, "priority": "Core", "whenToUse": "Any decision-grade deliverable — strategy recommendation, board update, investment memo, M&A review, post-mortem — where the reader is being asked to agree, decide, or act and will skim the title bar at speed.", "confidence": 85, "extraction": { "at": "2026-04-29 13:07:31.336924+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 7, "whyItWorks": "Solves two failure modes at once. (1) The buried claim: action titles place the conclusion on the page before any analysis is read, so a busy reader doesn't reverse-engineer it from the chart. (2) The spineless deck: because each title is a claim, slides have to ladder up to the governing thought; logical gaps become visible as topic-shaped titles in a sequence that no longer reads as a story.", "antipattern": "Topic labels disguised as titles — Volume by quarter, Key findings, Pricing strategy, Margins have been impacted. No verb, or a passive verb with no agent, or a fact (Revenue grew 12%) without the so-what. Also: titles that overreach the chart's evidence, multi-claim X-grew-but-Y-fell welded titles, and mechanical repetition of the same X-drove-Y template across the deck.", "cardinality": null, "narrativePurpose": "Forces the deck to carry its argument in the title bar so a senior reader can extract the recommendation without opening a single slide; converts a binder of topics into a navigable pyramid where every slide is a node defending the apex." }, { "tool": { "name": "Annotation", "slug": "annotation", "status": "active", "bestFor": null, "canonId": "019dd956-b5b9-7668-bf0e-3af99823ec5c", "version": 1, "bodyDocId": null, "description": "Adding explanatory labels to highlight key data points", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Designer", "layer": "slide", "agents": [ "Designer" ], "matchId": "019dd95a-0f08-73d3-987c-740c57a9f707", "evidence": "Callout '16 months (13%)' annotates the gap between curves.", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 85, "extraction": { "at": "2026-04-29 13:07:31.336924+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 7, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "Chart Selection Guide", "slug": "chart-selection-guide", "status": "active", "bestFor": null, "canonId": "019dd956-b1a0-700b-ba17-0e16c4d5bcae", "version": 1, "bodyDocId": null, "description": "Choosing the right chart type for your data and message", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Designer", "layer": "slide", "agents": [ "Designer" ], "matchId": "889056d0-fb51-4cb6-b03d-455414e589b5", "evidence": "This slide includes a chart (Figure 1) that supports the discussion of industry trends.", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 0.5, "extraction": { "at": "2026-07-16 21:02:22.717023+00", "model": "or:meta-llama/llama-4-scout", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 7, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "Chart Selection Guide", "slug": "chart-selection-guide", "status": "active", "bestFor": null, "canonId": "019dd956-b1a0-700b-ba17-0e16c4d5bcae", "version": 1, "bodyDocId": null, "description": "Choosing the right chart type for your data and message", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Designer", "layer": "slide", "agents": [ "Designer" ], "matchId": "019dd95a-0f08-73d3-987c-722664bfbbf0", "evidence": "S-curve compares AI vs digital transformation diffusion.", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 80, "extraction": { "at": "2026-04-29 13:07:31.336924+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 7, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "Concrete Language", "slug": "concrete-language", "status": "active", "bestFor": null, "canonId": "019dd956-bcd4-7398-9723-6aa72346170b", "version": 1, "bodyDocId": null, "description": "Using specific sensory details instead of abstract terms", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Storyteller", "layer": "slide", "agents": [ "Storyteller" ], "matchId": "019dd95a-0f08-73d3-987c-792d0dddc71e", "evidence": "46% of CEOs, 75% integration, 26% scaled pilots.", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 85, "extraction": { "at": "2026-04-29 13:07:31.336924+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 7, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "Annotation", "slug": "annotation", "status": "active", "bestFor": null, "canonId": "019dd956-b5b9-7668-bf0e-3af99823ec5c", "version": 1, "bodyDocId": null, "description": "Adding explanatory labels to highlight key data points", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Designer", "layer": "slide", "agents": [ "Designer" ], "matchId": "019dd95a-0f08-73d3-987c-8803ca43a868", "evidence": "Endpoint labels 9%/21%/30% pinpoint the trajectory.", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 75, "extraction": { "at": "2026-04-29 13:07:31.336924+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 8, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "Chart Selection Guide", "slug": "chart-selection-guide", "status": "active", "bestFor": null, "canonId": "019dd956-b1a0-700b-ba17-0e16c4d5bcae", "version": 1, "bodyDocId": null, "description": "Choosing the right chart type for your data and message", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Designer", "layer": "slide", "agents": [ "Designer" ], "matchId": "019dd95a-0f08-73d3-987c-8026b9df577a", "evidence": "Sankey-style flow shows revenue-share migration 9%->21%->30%.", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 80, "extraction": { "at": "2026-04-29 13:07:31.336924+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 8, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "Color Strategy", "slug": "color-strategy", "status": "active", "bestFor": null, "canonId": "019dd956-b202-77cf-8a6e-f445b08c0fd3", "version": 1, "bodyDocId": null, "description": "Using color for emphasis, categories, sentiment, and hierarchy", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Designer", "layer": "slide", "agents": [ "Designer" ], "matchId": "019dd95a-0f08-73d3-987c-8619607a2053", "evidence": "Purple gradient encodes High/Medium/Low AI-influenced bands.", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 75, "extraction": { "at": "2026-04-29 13:07:31.336924+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 8, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "Concrete Language", "slug": "concrete-language", "status": "active", "bestFor": null, "canonId": "019dd956-bcd4-7398-9723-6aa72346170b", "version": 1, "bodyDocId": null, "description": "Using specific sensory details instead of abstract terms", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Storyteller", "layer": "slide", "agents": [ "Storyteller" ], "matchId": "019dd95a-0f08-73d3-987c-8da6a1113acb", "evidence": "Specific percentages and 31% 2024 budget figure in body.", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 85, "extraction": { "at": "2026-04-29 13:07:31.336924+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 8, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "Concrete Language", "slug": "concrete-language", "status": "active", "bestFor": null, "canonId": "019dd956-bcd4-7398-9723-6aa72346170b", "version": 1, "bodyDocId": null, "description": "Using specific sensory details instead of abstract terms", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Storyteller", "layer": "slide", "agents": [ "Storyteller" ], "matchId": "019dd95a-0f08-73d3-987c-9777c430d9ef", "evidence": "Customers, shareholders, employees named as outcome dimensions.", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 60, "extraction": { "at": "2026-04-29 13:07:31.336924+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 10, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "Core Message Extraction", "slug": "core-message-extraction", "status": "active", "bestFor": "Any slide that carries an argument or finding. The diagnostic: if the slide has a chart on it, it needs a core message. Run extraction whenever the current title is a topic (Q3 performance, Customer satisfaction) rather than a claim, or when a reader could reasonably draw more than one conclusion from the visible evidence.", "canonId": "019dd956-bc71-707d-8867-1b2e810175cf", "version": 1, "bodyDocId": "f85613cb-4b77-462f-bfe6-3b862516e1a6", "description": "The discipline of distilling raw analysis, data, or content into a single declarative sentence — the slide's core message — that the audience would walk away with if they remembered nothing else. Process, not artefact: extraction questions run on the raw content until one sentence falls out.", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Architect", "layer": "slide", "agents": [ "Architect" ], "matchId": "019dd95a-0f08-73d3-987c-91cfe0408de9", "evidence": "Defines AI maturity as the central concept for the whole report.", "pageRefs": null, "priority": null, "whenToUse": "Any slide that carries an argument or finding. The diagnostic: if the slide has a chart on it, it needs a core message. Run extraction whenever the current title is a topic (Q3 performance, Customer satisfaction) rather than a claim, or when a reader could reasonably draw more than one conclusion from the visible evidence.", "confidence": 80, "extraction": { "at": "2026-04-29 13:07:31.336924+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 10, "whyItWorks": "Solves the two failure modes of slide writing simultaneously: the topic title (which outsources interpretation to the audience and produces three different conclusions in three different heads) and the multi-thesis stapler (which exceeds working memory and gets remembered as fragments). Aligns with how readers actually consume decks — Heath & Heath's Find the Core, the journalist's nut graf, and Minto's governing thought all converge on the same cognitive economics.", "antipattern": "Topic titles disguised as core messages (Customer satisfaction, no verb, no stake); multi-thesis sentences stapled with and; hedged sentences (may show signs of possible softening); chart-caption titles (Revenue fell 4%) that restate what the chart already shows instead of naming the so-what; meta-commentary (this slide explores...) that describes the slide rather than concluding it.", "cardinality": null, "narrativePurpose": "Forces the slide author to do the interpretive work before the slide ships, so the audience does not have to do it during the meeting. Wins the WYSIATI battle on purpose — the loudest fragment on the page becomes the author's chosen sentence rather than whichever chart label happens to be largest." }, { "tool": { "name": "2x2 matrix", "slug": "matrix-2x2", "status": "active", "bestFor": null, "canonId": "019dd9e1-50ab-72d1-8afb-3ab0a38e32a8", "version": 1, "bodyDocId": null, "description": "BCG matrix, importance/urgency, any axes-and-quadrants frame.", "familyLabel": null, "categoryName": null, "categorySlug": null }, "agent": null, "layer": "slide", "agents": null, "matchId": "d75fd6c4-fb15-4386-b4c5-67c186024840", "evidence": "This slide includes a 2x2 matrix that categorizes organizations into AI Achievers, AI Builders, etc.", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 0.8, "extraction": { "at": "2026-07-16 21:02:22.910197+00", "model": "or:meta-llama/llama-4-scout", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 11, "whyItWorks": null, "antipattern": null, "cardinality": "common", "narrativePurpose": null }, { "tool": { "name": "Action Titles", "slug": "action-titles", "status": "active", "bestFor": "Any decision-grade deliverable — strategy recommendation, board update, investment memo, M&A review, post-mortem — where the reader is being asked to agree, decide, or act and will skim the title bar at speed.", "canonId": "019dd956-ac70-700b-a608-ba58e78f5dcc", "version": 1, "bodyDocId": "816dad3c-9983-41c1-a86e-978ebd582841", "description": "The McKinsey-bred discipline of writing every slide title as a complete declarative sentence with a verb and an insight, not a topic label. Each title is a sub-claim that ladders up to the deck's governing thought; read in sequence, the titles reconstruct the executive summary.", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Architect", "layer": "slide", "agents": [ "Architect" ], "matchId": "019dd95a-0f08-73d3-987c-988bbdd684fa", "evidence": "Title states the so-what: 'Only 7% of organizations are AI Achievers'.", "pageRefs": null, "priority": "Core", "whenToUse": "Any decision-grade deliverable — strategy recommendation, board update, investment memo, M&A review, post-mortem — where the reader is being asked to agree, decide, or act and will skim the title bar at speed.", "confidence": 90, "extraction": { "at": "2026-04-29 13:07:31.336924+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 11, "whyItWorks": "Solves two failure modes at once. (1) The buried claim: action titles place the conclusion on the page before any analysis is read, so a busy reader doesn't reverse-engineer it from the chart. (2) The spineless deck: because each title is a claim, slides have to ladder up to the governing thought; logical gaps become visible as topic-shaped titles in a sequence that no longer reads as a story.", "antipattern": "Topic labels disguised as titles — Volume by quarter, Key findings, Pricing strategy, Margins have been impacted. No verb, or a passive verb with no agent, or a fact (Revenue grew 12%) without the so-what. Also: titles that overreach the chart's evidence, multi-claim X-grew-but-Y-fell welded titles, and mechanical repetition of the same X-drove-Y template across the deck.", "cardinality": null, "narrativePurpose": "Forces the deck to carry its argument in the title bar so a senior reader can extract the recommendation without opening a single slide; converts a binder of topics into a navigable pyramid where every slide is a node defending the apex." }, { "tool": { "name": "Annotation", "slug": "annotation", "status": "active", "bestFor": null, "canonId": "019dd956-b5b9-7668-bf0e-3af99823ec5c", "version": 1, "bodyDocId": null, "description": "Adding explanatory labels to highlight key data points", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Designer", "layer": "slide", "agents": [ "Designer" ], "matchId": "019dd95a-0f08-73d3-987c-a13946e009f7", "evidence": "Each quadrant labelled with name, % and short descriptor.", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 80, "extraction": { "at": "2026-04-29 13:07:31.336924+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 11, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "Color Strategy", "slug": "color-strategy", "status": "active", "bestFor": null, "canonId": "019dd956-b202-77cf-8a6e-f445b08c0fd3", "version": 1, "bodyDocId": null, "description": "Using color for emphasis, categories, sentiment, and hierarchy", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Designer", "layer": "slide", "agents": [ "Designer" ], "matchId": "019dd95a-0f08-73d3-987c-a47bf9474550", "evidence": "Achievers tinted in signature purple, others muted.", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 70, "extraction": { "at": "2026-04-29 13:07:31.336924+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 11, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "Concrete Language", "slug": "concrete-language", "status": "active", "bestFor": null, "canonId": "019dd956-bcd4-7398-9723-6aa72346170b", "version": 1, "bodyDocId": null, "description": "Using specific sensory details instead of abstract terms", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Storyteller", "layer": "slide", "agents": [ "Storyteller" ], "matchId": "019dd95a-0f08-73d3-987c-a84ef8da7810", "evidence": "7%, 10%, 8%, 75% sized as headline numbers.", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 85, "extraction": { "at": "2026-04-29 13:07:31.336924+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 11, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "Visual Hierarchy", "slug": "visual-hierarchy", "status": "active", "bestFor": null, "canonId": "019dd956-b2ca-706b-937f-e52441086fd7", "version": 1, "bodyDocId": null, "description": "Order of perception through Size > Color > Position > Weight > Space", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Designer", "layer": "slide", "agents": [ "Designer" ], "matchId": "019dd95a-0f08-73d3-987c-9fc1c5fce2ad", "evidence": "Big colored % per quadrant dominates the chart.", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 75, "extraction": { "at": "2026-04-29 13:07:31.336924+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 11, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "Action Titles", "slug": "action-titles", "status": "active", "bestFor": "Any decision-grade deliverable — strategy recommendation, board update, investment memo, M&A review, post-mortem — where the reader is being asked to agree, decide, or act and will skim the title bar at speed.", "canonId": "019dd956-ac70-700b-a608-ba58e78f5dcc", "version": 1, "bodyDocId": "816dad3c-9983-41c1-a86e-978ebd582841", "description": "The McKinsey-bred discipline of writing every slide title as a complete declarative sentence with a verb and an insight, not a topic label. Each title is a sub-claim that ladders up to the deck's governing thought; read in sequence, the titles reconstruct the executive summary.", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Architect", "layer": "slide", "agents": [ "Architect" ], "matchId": "019dd95a-0f08-73d3-987c-b13f84edd1c0", "evidence": "Subhead asserts gap will narrow by 2024.", "pageRefs": null, "priority": "Core", "whenToUse": "Any decision-grade deliverable — strategy recommendation, board update, investment memo, M&A review, post-mortem — where the reader is being asked to agree, decide, or act and will skim the title bar at speed.", "confidence": 65, "extraction": { "at": "2026-04-29 13:07:31.336924+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 12, "whyItWorks": "Solves two failure modes at once. (1) The buried claim: action titles place the conclusion on the page before any analysis is read, so a busy reader doesn't reverse-engineer it from the chart. (2) The spineless deck: because each title is a claim, slides have to ladder up to the governing thought; logical gaps become visible as topic-shaped titles in a sequence that no longer reads as a story.", "antipattern": "Topic labels disguised as titles — Volume by quarter, Key findings, Pricing strategy, Margins have been impacted. No verb, or a passive verb with no agent, or a fact (Revenue grew 12%) without the so-what. Also: titles that overreach the chart's evidence, multi-claim X-grew-but-Y-fell welded titles, and mechanical repetition of the same X-drove-Y template across the deck.", "cardinality": null, "narrativePurpose": "Forces the deck to carry its argument in the title bar so a senior reader can extract the recommendation without opening a single slide; converts a binder of topics into a navigable pyramid where every slide is a node defending the apex." }, { "tool": { "name": "Audience Definition", "slug": "audience-definition", "status": "active", "bestFor": null, "canonId": "019dd956-7f2a-775d-aeee-ff099bcb7756", "version": 1, "bodyDocId": null, "description": "Six key questions: Who are they? What do they know? What do they believe? What do they care about? What do they fear? What decisions can they make?", "familyLabel": null, "categoryName": "Block", "categorySlug": "block" }, "agent": "Storyteller", "layer": "slide", "agents": [ "Storyteller" ], "matchId": "42de0fc3-5228-40e2-89ef-1f53718199c6", "evidence": "The slide mentions 'industries like tech are currently far ahead in their respective AI maturity' implying a consideration of the audience's industry perspective.", "pageRefs": null, "priority": "Core", "whenToUse": null, "confidence": 0.7, "extraction": { "at": "2026-07-16 21:02:29.954701+00", "model": "or:meta-llama/llama-4-scout", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 12, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "Chart Selection Guide", "slug": "chart-selection-guide", "status": "active", "bestFor": null, "canonId": "019dd956-b1a0-700b-ba17-0e16c4d5bcae", "version": 1, "bodyDocId": null, "description": "Choosing the right chart type for your data and message", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Designer", "layer": "slide", "agents": [ "Designer" ], "matchId": "019dd95a-0f08-73d3-987c-ba2aee4088c2", "evidence": "Industry comparison chart shows current vs 2024 spread.", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 65, "extraction": { "at": "2026-04-29 13:07:31.336924+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 12, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "Concrete Language", "slug": "concrete-language", "status": "active", "bestFor": null, "canonId": "019dd956-bcd4-7398-9723-6aa72346170b", "version": 1, "bodyDocId": null, "description": "Using specific sensory details instead of abstract terms", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Storyteller", "layer": "slide", "agents": [ "Storyteller" ], "matchId": "019dd95a-0f08-73d3-987c-b55ac48404c7", "evidence": "Industry-level maturity scores quoted (e.g. '60').", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 70, "extraction": { "at": "2026-04-29 13:07:31.336924+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 12, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "Concrete Language", "slug": "concrete-language", "status": "active", "bestFor": null, "canonId": "019dd956-bcd4-7398-9723-6aa72346170b", "version": 1, "bodyDocId": null, "description": "Using specific sensory details instead of abstract terms", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Storyteller", "layer": "slide", "agents": [ "Storyteller" ], "matchId": "019dd95a-0f08-73d3-987c-c0826c15065a", "evidence": "Callout: '50% of revenue, up from 15%'.", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 80, "extraction": { "at": "2026-04-29 13:07:31.336924+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 13, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "Singularity Effect", "slug": "singularity-effect", "status": "active", "bestFor": null, "canonId": "019dd956-dcd3-7287-94d8-5a49496c2ddb", "version": 1, "bodyDocId": null, "description": "People care more about individuals than statistics - use specific examples", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Storyteller", "layer": "slide", "agents": [ "Storyteller" ], "matchId": "019dd95a-0f08-73d3-987c-c73f24089782", "evidence": "Single named retailer humanizes the industry-trend abstraction.", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 70, "extraction": { "at": "2026-04-29 13:07:31.336924+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 13, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "Story Moments", "slug": "story-moments", "status": "active", "bestFor": null, "canonId": "019dd956-ae4e-768d-a18b-108e6cda511e", "version": 1, "bodyDocId": null, "description": "Design key emotional beats: The Shock, The Vision, The Proof, The Choice, The Call", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Storyteller", "layer": "slide", "agents": [ "Storyteller" ], "matchId": "019dd95a-0f08-73d3-987c-be69e7a13427", "evidence": "Apparel COVID e-commerce case as a concrete win moment.", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 75, "extraction": { "at": "2026-04-29 13:07:31.336924+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 13, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "Story Moments", "slug": "story-moments", "status": "active", "bestFor": null, "canonId": "019dd956-ae4e-768d-a18b-108e6cda511e", "version": 1, "bodyDocId": null, "description": "Design key emotional beats: The Shock, The Vision, The Proof, The Choice, The Call", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Storyteller", "layer": "slide", "agents": [ "Storyteller" ], "matchId": "bb51670d-5835-4349-bf77-e57f77fa229a", "evidence": "The slide provides various examples of companies using AI, which are storytelling moments.", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 0.6, "extraction": { "at": "2026-07-16 21:02:30.026549+00", "model": "or:meta-llama/llama-4-scout", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 13, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "Action Titles", "slug": "action-titles", "status": "active", "bestFor": "Any decision-grade deliverable — strategy recommendation, board update, investment memo, M&A review, post-mortem — where the reader is being asked to agree, decide, or act and will skim the title bar at speed.", "canonId": "019dd956-ac70-700b-a608-ba58e78f5dcc", "version": 1, "bodyDocId": "816dad3c-9983-41c1-a86e-978ebd582841", "description": "The McKinsey-bred discipline of writing every slide title as a complete declarative sentence with a verb and an insight, not a topic label. Each title is a sub-claim that ladders up to the deck's governing thought; read in sequence, the titles reconstruct the executive summary.", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Architect", "layer": "slide", "agents": [ "Architect" ], "matchId": "0aa14a4f-52cc-45e8-b497-7a785f330330", "evidence": "The slide has a clear action title: 'AI Achievers advance from practice to performance'.", "pageRefs": null, "priority": "Core", "whenToUse": "Any decision-grade deliverable — strategy recommendation, board update, investment memo, M&A review, post-mortem — where the reader is being asked to agree, decide, or act and will skim the title bar at speed.", "confidence": 0.9, "extraction": { "at": "2026-07-16 21:02:30.091851+00", "model": "or:meta-llama/llama-4-scout", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 14, "whyItWorks": "Solves two failure modes at once. (1) The buried claim: action titles place the conclusion on the page before any analysis is read, so a busy reader doesn't reverse-engineer it from the chart. (2) The spineless deck: because each title is a claim, slides have to ladder up to the governing thought; logical gaps become visible as topic-shaped titles in a sequence that no longer reads as a story.", "antipattern": "Topic labels disguised as titles — Volume by quarter, Key findings, Pricing strategy, Margins have been impacted. No verb, or a passive verb with no agent, or a fact (Revenue grew 12%) without the so-what. Also: titles that overreach the chart's evidence, multi-claim X-grew-but-Y-fell welded titles, and mechanical repetition of the same X-drove-Y template across the deck.", "cardinality": null, "narrativePurpose": "Forces the deck to carry its argument in the title bar so a senior reader can extract the recommendation without opening a single slide; converts a binder of topics into a navigable pyramid where every slide is a node defending the apex." }, { "tool": { "name": "2x2 matrix", "slug": "matrix-2x2", "status": "active", "bestFor": null, "canonId": "019dd9e1-50ab-72d1-8afb-3ab0a38e32a8", "version": 1, "bodyDocId": null, "description": "BCG matrix, importance/urgency, any axes-and-quadrants frame.", "familyLabel": null, "categoryName": null, "categorySlug": null }, "agent": null, "layer": "slide", "agents": null, "matchId": "3a3ab2cd-8202-4133-a522-e8cd6a6a4957", "evidence": "Although not a traditional 2x2 matrix, the slide compares AI achievers with other groups in a tabular format.", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 0.5, "extraction": { "at": "2026-07-16 21:02:30.154103+00", "model": "or:meta-llama/llama-4-scout", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 15, "whyItWorks": null, "antipattern": null, "cardinality": "common", "narrativePurpose": null }, { "tool": { "name": "Action Titles", "slug": "action-titles", "status": "active", "bestFor": "Any decision-grade deliverable — strategy recommendation, board update, investment memo, M&A review, post-mortem — where the reader is being asked to agree, decide, or act and will skim the title bar at speed.", "canonId": "019dd956-ac70-700b-a608-ba58e78f5dcc", "version": 1, "bodyDocId": "816dad3c-9983-41c1-a86e-978ebd582841", "description": "The McKinsey-bred discipline of writing every slide title as a complete declarative sentence with a verb and an insight, not a topic label. Each title is a sub-claim that ladders up to the deck's governing thought; read in sequence, the titles reconstruct the executive summary.", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Architect", "layer": "slide", "agents": [ "Architect" ], "matchId": "019dd95a-0f08-73d3-987c-cdcbb07e9173", "evidence": "'AI Achievers advance from practice to performance' states the verdict.", "pageRefs": null, "priority": "Core", "whenToUse": "Any decision-grade deliverable — strategy recommendation, board update, investment memo, M&A review, post-mortem — where the reader is being asked to agree, decide, or act and will skim the title bar at speed.", "confidence": 85, "extraction": { "at": "2026-04-29 13:07:31.336924+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 15, "whyItWorks": "Solves two failure modes at once. (1) The buried claim: action titles place the conclusion on the page before any analysis is read, so a busy reader doesn't reverse-engineer it from the chart. (2) The spineless deck: because each title is a claim, slides have to ladder up to the governing thought; logical gaps become visible as topic-shaped titles in a sequence that no longer reads as a story.", "antipattern": "Topic labels disguised as titles — Volume by quarter, Key findings, Pricing strategy, Margins have been impacted. No verb, or a passive verb with no agent, or a fact (Revenue grew 12%) without the so-what. Also: titles that overreach the chart's evidence, multi-claim X-grew-but-Y-fell welded titles, and mechanical repetition of the same X-drove-Y template across the deck.", "cardinality": null, "narrativePurpose": "Forces the deck to carry its argument in the title bar so a senior reader can extract the recommendation without opening a single slide; converts a binder of topics into a navigable pyramid where every slide is a node defending the apex." }, { "tool": { "name": "Color Strategy", "slug": "color-strategy", "status": "active", "bestFor": null, "canonId": "019dd956-b202-77cf-8a6e-f445b08c0fd3", "version": 1, "bodyDocId": null, "description": "Using color for emphasis, categories, sentiment, and hierarchy", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Designer", "layer": "slide", "agents": [ "Designer" ], "matchId": "019dd95a-0f08-73d3-987c-d94bba45a13e", "evidence": "Filled vs hollow squares encode out- vs under-performing.", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 75, "extraction": { "at": "2026-04-29 13:07:31.336924+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 15, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "Concrete Language", "slug": "concrete-language", "status": "active", "bestFor": null, "canonId": "019dd956-bcd4-7398-9723-6aa72346170b", "version": 1, "bodyDocId": null, "description": "Using specific sensory details instead of abstract terms", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Storyteller", "layer": "slide", "agents": [ "Storyteller" ], "matchId": "019dd95a-0f08-73d3-987c-d0da7fb84ca7", "evidence": "'50% greater revenue growth' anchors the gap.", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 85, "extraction": { "at": "2026-04-29 13:07:31.336924+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 15, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "Small Multiples", "slug": "small-multiples", "status": "active", "bestFor": null, "canonId": "019dd956-b32d-7586-b368-baa1dd388ed4", "version": 1, "bodyDocId": null, "description": "Repeating similar charts for comparison across categories or time", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Designer", "layer": "slide", "agents": [ "Designer" ], "matchId": "019dd95a-0f08-73d3-987c-d6417e7a8a19", "evidence": "Fig 5 grid of 17 capabilities x 4 archetypes for at-a-glance compare.", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 85, "extraction": { "at": "2026-04-29 13:07:31.336924+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 15, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "Action Titles", "slug": "action-titles", "status": "active", "bestFor": "Any decision-grade deliverable — strategy recommendation, board update, investment memo, M&A review, post-mortem — where the reader is being asked to agree, decide, or act and will skim the title bar at speed.", "canonId": "019dd956-ac70-700b-a608-ba58e78f5dcc", "version": 1, "bodyDocId": "816dad3c-9983-41c1-a86e-978ebd582841", "description": "The McKinsey-bred discipline of writing every slide title as a complete declarative sentence with a verb and an insight, not a topic label. Each title is a sub-claim that ladders up to the deck's governing thought; read in sequence, the titles reconstruct the executive summary.", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Architect", "layer": "slide", "agents": [ "Architect" ], "matchId": "019dd95a-0f08-73d3-987c-e487f368a7d7", "evidence": "Title 'Turning pilots into production' delivers a verb-led message.", "pageRefs": null, "priority": "Core", "whenToUse": "Any decision-grade deliverable — strategy recommendation, board update, investment memo, M&A review, post-mortem — where the reader is being asked to agree, decide, or act and will skim the title bar at speed.", "confidence": 80, "extraction": { "at": "2026-04-29 13:07:31.336924+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 16, "whyItWorks": "Solves two failure modes at once. (1) The buried claim: action titles place the conclusion on the page before any analysis is read, so a busy reader doesn't reverse-engineer it from the chart. (2) The spineless deck: because each title is a claim, slides have to ladder up to the governing thought; logical gaps become visible as topic-shaped titles in a sequence that no longer reads as a story.", "antipattern": "Topic labels disguised as titles — Volume by quarter, Key findings, Pricing strategy, Margins have been impacted. No verb, or a passive verb with no agent, or a fact (Revenue grew 12%) without the so-what. Also: titles that overreach the chart's evidence, multi-claim X-grew-but-Y-fell welded titles, and mechanical repetition of the same X-drove-Y template across the deck.", "cardinality": null, "narrativePurpose": "Forces the deck to carry its argument in the title bar so a senior reader can extract the recommendation without opening a single slide; converts a binder of topics into a navigable pyramid where every slide is a node defending the apex." }, { "tool": { "name": "Concrete Language", "slug": "concrete-language", "status": "active", "bestFor": null, "canonId": "019dd956-bcd4-7398-9723-6aa72346170b", "version": 1, "bodyDocId": null, "description": "Using specific sensory details instead of abstract terms", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Storyteller", "layer": "slide", "agents": [ "Storyteller" ], "matchId": "019dd95a-0f08-73d3-987c-eadf6e1a1063", "evidence": "60 vs 44 scale-rate, 5% more likely to scale.", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 80, "extraction": { "at": "2026-04-29 13:07:31.336924+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 16, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "Action Titles", "slug": "action-titles", "status": "active", "bestFor": "Any decision-grade deliverable — strategy recommendation, board update, investment memo, M&A review, post-mortem — where the reader is being asked to agree, decide, or act and will skim the title bar at speed.", "canonId": "019dd956-ac70-700b-a608-ba58e78f5dcc", "version": 1, "bodyDocId": "816dad3c-9983-41c1-a86e-978ebd582841", "description": "The McKinsey-bred discipline of writing every slide title as a complete declarative sentence with a verb and an insight, not a topic label. Each title is a sub-claim that ladders up to the deck's governing thought; read in sequence, the titles reconstruct the executive summary.", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Architect", "layer": "slide", "agents": [ "Architect" ], "matchId": "019dd95a-0f08-73d3-987c-ed8f03f70aa3", "evidence": "'Focusing beyond financial metrics' signals the next dimension.", "pageRefs": null, "priority": "Core", "whenToUse": "Any decision-grade deliverable — strategy recommendation, board update, investment memo, M&A review, post-mortem — where the reader is being asked to agree, decide, or act and will skim the title bar at speed.", "confidence": 75, "extraction": { "at": "2026-04-29 13:07:31.336924+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 17, "whyItWorks": "Solves two failure modes at once. (1) The buried claim: action titles place the conclusion on the page before any analysis is read, so a busy reader doesn't reverse-engineer it from the chart. (2) The spineless deck: because each title is a claim, slides have to ladder up to the governing thought; logical gaps become visible as topic-shaped titles in a sequence that no longer reads as a story.", "antipattern": "Topic labels disguised as titles — Volume by quarter, Key findings, Pricing strategy, Margins have been impacted. No verb, or a passive verb with no agent, or a fact (Revenue grew 12%) without the so-what. Also: titles that overreach the chart's evidence, multi-claim X-grew-but-Y-fell welded titles, and mechanical repetition of the same X-drove-Y template across the deck.", "cardinality": null, "narrativePurpose": "Forces the deck to carry its argument in the title bar so a senior reader can extract the recommendation without opening a single slide; converts a binder of topics into a navigable pyramid where every slide is a node defending the apex." }, { "tool": { "name": "Authority Bias", "slug": "authority-bias", "status": "active", "bestFor": null, "canonId": "019dd956-c38d-70b9-a284-b2b479763356", "version": 1, "bodyDocId": null, "description": "Expert opinions are weighted more heavily - cite credible sources", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Storyteller", "layer": "slide", "agents": [ "Architect", "Storyteller" ], "matchId": "019dd95a-0f08-73d3-987c-f7dfed8ecbef", "evidence": "Cites Accenture's Sustainable Technology survey of 500+ multinationals.", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 65, "extraction": { "at": "2026-04-29 13:07:31.336924+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 17, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "Concrete Language", "slug": "concrete-language", "status": "active", "bestFor": null, "canonId": "019dd956-bcd4-7398-9723-6aa72346170b", "version": 1, "bodyDocId": null, "description": "Using specific sensory details instead of abstract terms", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Storyteller", "layer": "slide", "agents": [ "Storyteller" ], "matchId": "019dd95a-0f08-73d3-987c-f263775fabfe", "evidence": "70% reduced emissions via AI; 8% stat in body.", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 80, "extraction": { "at": "2026-04-29 13:07:31.336924+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 17, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "Section divider", "slug": "section-divider", "status": "active", "bestFor": null, "canonId": "019dd9e1-4c66-707d-8d1f-6e14547134c7", "version": 1, "bodyDocId": null, "description": "A transitional slide marking the start of a new section.", "familyLabel": null, "categoryName": null, "categorySlug": null }, "agent": null, "layer": "slide", "agents": null, "matchId": "48c11967-1810-4ee7-aada-0c9a94accf68", "evidence": "The slide is clearly a section divider with a title and subtitle.", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 0.9, "extraction": { "at": "2026-07-16 21:02:30.282899+00", "model": "or:meta-llama/llama-4-scout", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 18, "whyItWorks": null, "antipattern": null, "cardinality": "common", "narrativePurpose": null }, { "tool": { "name": "Action Titles", "slug": "action-titles", "status": "active", "bestFor": "Any decision-grade deliverable — strategy recommendation, board update, investment memo, M&A review, post-mortem — where the reader is being asked to agree, decide, or act and will skim the title bar at speed.", "canonId": "019dd956-ac70-700b-a608-ba58e78f5dcc", "version": 1, "bodyDocId": "816dad3c-9983-41c1-a86e-978ebd582841", "description": "The McKinsey-bred discipline of writing every slide title as a complete declarative sentence with a verb and an insight, not a topic label. Each title is a sub-claim that ladders up to the deck's governing thought; read in sequence, the titles reconstruct the executive summary.", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Architect", "layer": "slide", "agents": [ "Architect" ], "matchId": "019dd95a-0f08-73d3-987c-f85f60a1558c", "evidence": "Action title 'Champion AI as a strategic priority...' states the rec.", "pageRefs": null, "priority": "Core", "whenToUse": "Any decision-grade deliverable — strategy recommendation, board update, investment memo, M&A review, post-mortem — where the reader is being asked to agree, decide, or act and will skim the title bar at speed.", "confidence": 90, "extraction": { "at": "2026-04-29 13:07:31.336924+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 20, "whyItWorks": "Solves two failure modes at once. (1) The buried claim: action titles place the conclusion on the page before any analysis is read, so a busy reader doesn't reverse-engineer it from the chart. (2) The spineless deck: because each title is a claim, slides have to ladder up to the governing thought; logical gaps become visible as topic-shaped titles in a sequence that no longer reads as a story.", "antipattern": "Topic labels disguised as titles — Volume by quarter, Key findings, Pricing strategy, Margins have been impacted. No verb, or a passive verb with no agent, or a fact (Revenue grew 12%) without the so-what. Also: titles that overreach the chart's evidence, multi-claim X-grew-but-Y-fell welded titles, and mechanical repetition of the same X-drove-Y template across the deck.", "cardinality": null, "narrativePurpose": "Forces the deck to carry its argument in the title bar so a senior reader can extract the recommendation without opening a single slide; converts a binder of topics into a navigable pyramid where every slide is a node defending the apex." }, { "tool": { "name": "Authority Bias", "slug": "authority-bias", "status": "active", "bestFor": null, "canonId": "019dd956-c38d-70b9-a284-b2b479763356", "version": 1, "bodyDocId": null, "description": "Expert opinions are weighted more heavily - cite credible sources", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Storyteller", "layer": "slide", "agents": [ "Architect", "Storyteller" ], "matchId": "019dd95a-0f08-73d3-987d-0077d5a6a5ab", "evidence": "Named Fortune-500 CEO as the validating voice.", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 85, "extraction": { "at": "2026-04-29 13:07:31.336924+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 20, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "CEO quote contradiction", "slug": "ceo-quote-contradiction", "status": "active", "bestFor": "When management credibility is the lever", "canonId": "019dd9e1-52e9-717f-8454-93e627563ed6", "version": 1, "bodyDocId": "019dd9a1-8296-720d-8f51-da76937f9415", "description": "You reproduce management's own words — verbatim, with source and date — and\nthen place them next to the outcome that contradicts them. The CEO built\nthe rope; you put it around their own neck.", "familyLabel": null, "categoryName": null, "categorySlug": null }, "agent": null, "layer": "slide", "agents": null, "matchId": "057c10c5-ce51-4cfc-a0e9-9317678ff211", "evidence": "The slide includes a CEO quote, which could potentially be used to contradict a previous statement.", "pageRefs": null, "priority": null, "whenToUse": "When management credibility is the lever", "confidence": 0.6, "extraction": { "at": "2026-07-16 21:02:30.378817+00", "model": "or:meta-llama/llama-4-scout", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 20, "whyItWorks": "- **Maximum credibility**: no adjective you could write is as damning as the\n target's own prior statement.\n- **No rebuttal path**: management can't argue they didn't say it.\n- **It forces accountability onto a person**, not an institution — even if\n you aren't explicitly naming a villain elsewhere.\n- **Reporters amplify it**. A CEO-quote-contradiction slide is quotable,\n which means it lands in WSJ/FT/Bloomberg coverage.", "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "Concrete Language", "slug": "concrete-language", "status": "active", "bestFor": null, "canonId": "019dd956-bcd4-7398-9723-6aa72346170b", "version": 1, "bodyDocId": null, "description": "Using specific sensory details instead of abstract terms", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Storyteller", "layer": "slide", "agents": [ "Storyteller" ], "matchId": "019dd95a-0f08-73d3-987d-065a82c5d6af", "evidence": "85% of NA Achievers vs 53% Builders, 57% Experimenters.", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 85, "extraction": { "at": "2026-04-29 13:07:31.336924+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 20, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "Credibility Transfer", "slug": "credibility-transfer", "status": "active", "bestFor": null, "canonId": "019dd956-bd34-759a-8e3b-2f14b571a2a1", "version": 1, "bodyDocId": null, "description": "Borrowing authority from trusted sources or vivid details", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Storyteller", "layer": "slide", "agents": [ "Storyteller" ], "matchId": "019dd95a-0f08-73d3-987c-ff515049c8b6", "evidence": "Pull quote from Stephen Squeri, CEO of American Express.", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 90, "extraction": { "at": "2026-04-29 13:07:31.336924+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 20, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "Concrete Language", "slug": "concrete-language", "status": "active", "bestFor": null, "canonId": "019dd956-bcd4-7398-9723-6aa72346170b", "version": 1, "bodyDocId": null, "description": "Using specific sensory details instead of abstract terms", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Storyteller", "layer": "slide", "agents": [ "Storyteller" ], "matchId": "019dd95a-0f08-73d3-987d-1063827989f7", "evidence": "Callout cites US$70M and 4% vs 3% comparison.", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 75, "extraction": { "at": "2026-04-29 13:07:31.336924+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 21, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "Story Moments", "slug": "story-moments", "status": "active", "bestFor": null, "canonId": "019dd956-ae4e-768d-a18b-108e6cda511e", "version": 1, "bodyDocId": null, "description": "Design key emotional beats: The Shock, The Vision, The Proof, The Choice, The Call", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Storyteller", "layer": "slide", "agents": [ "Storyteller" ], "matchId": "019dd95a-0f08-73d3-987d-14b2367452f5", "evidence": "Vignette of a NA Achiever embracing collaboration tools.", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 70, "extraction": { "at": "2026-04-29 13:07:31.336924+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 21, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "Action Titles", "slug": "action-titles", "status": "active", "bestFor": "Any decision-grade deliverable — strategy recommendation, board update, investment memo, M&A review, post-mortem — where the reader is being asked to agree, decide, or act and will skim the title bar at speed.", "canonId": "019dd956-ac70-700b-a608-ba58e78f5dcc", "version": 1, "bodyDocId": "816dad3c-9983-41c1-a86e-978ebd582841", "description": "The McKinsey-bred discipline of writing every slide title as a complete declarative sentence with a verb and an insight, not a topic label. Each title is a sub-claim that ladders up to the deck's governing thought; read in sequence, the titles reconstruct the executive summary.", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Architect", "layer": "slide", "agents": [ "Architect" ], "matchId": "019dd95a-0f08-73d3-987d-19c9f532e24c", "evidence": "Action title 'Invest heavily in talent...' is the recommendation.", "pageRefs": null, "priority": "Core", "whenToUse": "Any decision-grade deliverable — strategy recommendation, board update, investment memo, M&A review, post-mortem — where the reader is being asked to agree, decide, or act and will skim the title bar at speed.", "confidence": 90, "extraction": { "at": "2026-04-29 13:07:31.336924+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 22, "whyItWorks": "Solves two failure modes at once. (1) The buried claim: action titles place the conclusion on the page before any analysis is read, so a busy reader doesn't reverse-engineer it from the chart. (2) The spineless deck: because each title is a claim, slides have to ladder up to the governing thought; logical gaps become visible as topic-shaped titles in a sequence that no longer reads as a story.", "antipattern": "Topic labels disguised as titles — Volume by quarter, Key findings, Pricing strategy, Margins have been impacted. No verb, or a passive verb with no agent, or a fact (Revenue grew 12%) without the so-what. Also: titles that overreach the chart's evidence, multi-claim X-grew-but-Y-fell welded titles, and mechanical repetition of the same X-drove-Y template across the deck.", "cardinality": null, "narrativePurpose": "Forces the deck to carry its argument in the title bar so a senior reader can extract the recommendation without opening a single slide; converts a binder of topics into a navigable pyramid where every slide is a node defending the apex." }, { "tool": { "name": "Concrete Language", "slug": "concrete-language", "status": "active", "bestFor": null, "canonId": "019dd956-bcd4-7398-9723-6aa72346170b", "version": 1, "bodyDocId": null, "description": "Using specific sensory details instead of abstract terms", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Storyteller", "layer": "slide", "agents": [ "Storyteller" ], "matchId": "019dd95a-0f08-73d3-987d-1c19f31c9904", "evidence": "56% with mandatory training; 35% NA stat.", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 85, "extraction": { "at": "2026-04-29 13:07:31.336924+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 22, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "Concrete Language", "slug": "concrete-language", "status": "active", "bestFor": null, "canonId": "019dd956-bcd4-7398-9723-6aa72346170b", "version": 1, "bodyDocId": null, "description": "Using specific sensory details instead of abstract terms", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Storyteller", "layer": "slide", "agents": [ "Storyteller" ], "matchId": "019dd95a-0f08-73d3-987d-23198726ca9e", "evidence": "35% Achievers vs 33% Innovators vs 27% Experimenters.", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 80, "extraction": { "at": "2026-04-29 13:07:31.336924+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 23, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "Story Moments", "slug": "story-moments", "status": "active", "bestFor": null, "canonId": "019dd956-ae4e-768d-a18b-108e6cda511e", "version": 1, "bodyDocId": null, "description": "Design key emotional beats: The Shock, The Vision, The Proof, The Choice, The Call", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Storyteller", "layer": "slide", "agents": [ "Storyteller" ], "matchId": "019dd95a-0f08-73d3-987d-2734dc9b4e2a", "evidence": "Case illustration of AI talent depth across firm.", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 65, "extraction": { "at": "2026-04-29 13:07:31.336924+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 23, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "Action Titles", "slug": "action-titles", "status": "active", "bestFor": "Any decision-grade deliverable — strategy recommendation, board update, investment memo, M&A review, post-mortem — where the reader is being asked to agree, decide, or act and will skim the title bar at speed.", "canonId": "019dd956-ac70-700b-a608-ba58e78f5dcc", "version": 1, "bodyDocId": "816dad3c-9983-41c1-a86e-978ebd582841", "description": "The McKinsey-bred discipline of writing every slide title as a complete declarative sentence with a verb and an insight, not a topic label. Each title is a sub-claim that ladders up to the deck's governing thought; read in sequence, the titles reconstruct the executive summary.", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Architect", "layer": "slide", "agents": [ "Architect" ], "matchId": "019dd95a-0f08-73d3-987d-2913f03ac63f", "evidence": "Action title 'Industrialize AI tools and teams to create an AI core'.", "pageRefs": null, "priority": "Core", "whenToUse": "Any decision-grade deliverable — strategy recommendation, board update, investment memo, M&A review, post-mortem — where the reader is being asked to agree, decide, or act and will skim the title bar at speed.", "confidence": 90, "extraction": { "at": "2026-04-29 13:07:31.336924+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 24, "whyItWorks": "Solves two failure modes at once. (1) The buried claim: action titles place the conclusion on the page before any analysis is read, so a busy reader doesn't reverse-engineer it from the chart. (2) The spineless deck: because each title is a claim, slides have to ladder up to the governing thought; logical gaps become visible as topic-shaped titles in a sequence that no longer reads as a story.", "antipattern": "Topic labels disguised as titles — Volume by quarter, Key findings, Pricing strategy, Margins have been impacted. No verb, or a passive verb with no agent, or a fact (Revenue grew 12%) without the so-what. Also: titles that overreach the chart's evidence, multi-claim X-grew-but-Y-fell welded titles, and mechanical repetition of the same X-drove-Y template across the deck.", "cardinality": null, "narrativePurpose": "Forces the deck to carry its argument in the title bar so a senior reader can extract the recommendation without opening a single slide; converts a binder of topics into a navigable pyramid where every slide is a node defending the apex." }, { "tool": { "name": "Audience Definition", "slug": "audience-definition", "status": "active", "bestFor": null, "canonId": "019dd956-7f2a-775d-aeee-ff099bcb7756", "version": 1, "bodyDocId": null, "description": "Six key questions: Who are they? What do they know? What do they believe? What do they care about? What do they fear? What decisions can they make?", "familyLabel": null, "categoryName": "Block", "categorySlug": "block" }, "agent": "Storyteller", "layer": "slide", "agents": [ "Storyteller" ], "matchId": "c8aa27d3-563e-4128-bbdf-320c0d876da6", "evidence": "To extract value from their data quickly and effectively, Achievers in North America are 72% more likely, on average, than Experimenters to either develop custom-built machine learning applications...", "pageRefs": null, "priority": "Core", "whenToUse": null, "confidence": 0.7, "extraction": { "at": "2026-07-16 21:02:24.203124+00", "model": "or:meta-llama/llama-4-scout", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 24, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "Concrete Language", "slug": "concrete-language", "status": "active", "bestFor": null, "canonId": "019dd956-bcd4-7398-9723-6aa72346170b", "version": 1, "bodyDocId": null, "description": "Using specific sensory details instead of abstract terms", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Storyteller", "layer": "slide", "agents": [ "Storyteller" ], "matchId": "019dd95a-0f08-73d3-987d-2c17b3c3b92a", "evidence": "80% callout; 72% more likely vs Experimenters.", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 85, "extraction": { "at": "2026-04-29 13:07:31.336924+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 24, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "Data Story Arc", "slug": "data-story-arc", "status": "active", "bestFor": null, "canonId": "019dd956-9c30-728e-b974-d3fb123dcf5a", "version": 1, "bodyDocId": null, "description": "Context → Conflict → Insight → Implication structure for data narratives", "familyLabel": null, "categoryName": "Loop", "categorySlug": "loop" }, "agent": "Storyteller", "layer": "slide", "agents": [ "Storyteller" ], "matchId": "26b43720-735e-4a65-be0d-419b059f8028", "evidence": "To build AI cores, Achievers harness the power of internal and external data... 80% of North America-based organizations (vs. 75% globally) have already re-worked their strategy and cloud plans to ac", "pageRefs": null, "priority": "Core", "whenToUse": null, "confidence": 0.6, "extraction": { "at": "2026-07-16 21:02:24.243176+00", "model": "or:meta-llama/llama-4-scout", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 24, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "Concrete Language", "slug": "concrete-language", "status": "active", "bestFor": null, "canonId": "019dd956-bcd4-7398-9723-6aa72346170b", "version": 1, "bodyDocId": null, "description": "Using specific sensory details instead of abstract terms", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Storyteller", "layer": "slide", "agents": [ "Storyteller" ], "matchId": "019dd95a-0f08-73d3-987d-30d7e81c1df1", "evidence": "5% Y1 efficiency, $100M annual savings target.", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 85, "extraction": { "at": "2026-04-29 13:07:31.336924+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 25, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "Story Moments", "slug": "story-moments", "status": "active", "bestFor": null, "canonId": "019dd956-ae4e-768d-a18b-108e6cda511e", "version": 1, "bodyDocId": null, "description": "Design key emotional beats: The Shock, The Vision, The Proof, The Choice, The Call", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Storyteller", "layer": "slide", "agents": [ "Storyteller" ], "matchId": "019dd95a-0f08-73d3-987d-36c1894bde7b", "evidence": "Industrialization case quantified with savings figure.", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 70, "extraction": { "at": "2026-04-29 13:07:31.336924+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 25, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "Action Titles", "slug": "action-titles", "status": "active", "bestFor": "Any decision-grade deliverable — strategy recommendation, board update, investment memo, M&A review, post-mortem — where the reader is being asked to agree, decide, or act and will skim the title bar at speed.", "canonId": "019dd956-ac70-700b-a608-ba58e78f5dcc", "version": 1, "bodyDocId": "816dad3c-9983-41c1-a86e-978ebd582841", "description": "The McKinsey-bred discipline of writing every slide title as a complete declarative sentence with a verb and an insight, not a topic label. Each title is a sub-claim that ladders up to the deck's governing thought; read in sequence, the titles reconstruct the executive summary.", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Architect", "layer": "slide", "agents": [ "Architect" ], "matchId": "019dd95a-0f08-73d3-987d-3bc14e2deefe", "evidence": "Action title 'Design AI responsibly, from the start'.", "pageRefs": null, "priority": "Core", "whenToUse": "Any decision-grade deliverable — strategy recommendation, board update, investment memo, M&A review, post-mortem — where the reader is being asked to agree, decide, or act and will skim the title bar at speed.", "confidence": 90, "extraction": { "at": "2026-04-29 13:07:31.336924+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 26, "whyItWorks": "Solves two failure modes at once. (1) The buried claim: action titles place the conclusion on the page before any analysis is read, so a busy reader doesn't reverse-engineer it from the chart. (2) The spineless deck: because each title is a claim, slides have to ladder up to the governing thought; logical gaps become visible as topic-shaped titles in a sequence that no longer reads as a story.", "antipattern": "Topic labels disguised as titles — Volume by quarter, Key findings, Pricing strategy, Margins have been impacted. No verb, or a passive verb with no agent, or a fact (Revenue grew 12%) without the so-what. Also: titles that overreach the chart's evidence, multi-claim X-grew-but-Y-fell welded titles, and mechanical repetition of the same X-drove-Y template across the deck.", "cardinality": null, "narrativePurpose": "Forces the deck to carry its argument in the title bar so a senior reader can extract the recommendation without opening a single slide; converts a binder of topics into a navigable pyramid where every slide is a node defending the apex." }, { "tool": { "name": "Concrete Language", "slug": "concrete-language", "status": "active", "bestFor": null, "canonId": "019dd956-bcd4-7398-9723-6aa72346170b", "version": 1, "bodyDocId": null, "description": "Using specific sensory details instead of abstract terms", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Storyteller", "layer": "slide", "agents": [ "Storyteller" ], "matchId": "019dd95a-0f08-73d3-987d-3e9a29f85584", "evidence": "97% expect regulatory impact; 77% say company-wide priority.", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 85, "extraction": { "at": "2026-04-29 13:07:31.336924+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 26, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "Concrete Language", "slug": "concrete-language", "status": "active", "bestFor": null, "canonId": "019dd956-bcd4-7398-9723-6aa72346170b", "version": 1, "bodyDocId": null, "description": "Using specific sensory details instead of abstract terms", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Storyteller", "layer": "slide", "agents": [ "Storyteller" ], "matchId": "019dd95a-0f08-73d3-987d-42b6f470d066", "evidence": "Only 3% have responsible AI today vs 45% targeting it by 2024.", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 85, "extraction": { "at": "2026-04-29 13:07:31.336924+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 27, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "Action Titles", "slug": "action-titles", "status": "active", "bestFor": "Any decision-grade deliverable — strategy recommendation, board update, investment memo, M&A review, post-mortem — where the reader is being asked to agree, decide, or act and will skim the title bar at speed.", "canonId": "019dd956-ac70-700b-a608-ba58e78f5dcc", "version": 1, "bodyDocId": "816dad3c-9983-41c1-a86e-978ebd582841", "description": "The McKinsey-bred discipline of writing every slide title as a complete declarative sentence with a verb and an insight, not a topic label. Each title is a sub-claim that ladders up to the deck's governing thought; read in sequence, the titles reconstruct the executive summary.", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Architect", "layer": "slide", "agents": [ "Architect" ], "matchId": "019dd95a-0f08-73d3-987d-492757d85e68", "evidence": "Action title 'Prioritize long- and short-term AI investments'.", "pageRefs": null, "priority": "Core", "whenToUse": "Any decision-grade deliverable — strategy recommendation, board update, investment memo, M&A review, post-mortem — where the reader is being asked to agree, decide, or act and will skim the title bar at speed.", "confidence": 90, "extraction": { "at": "2026-04-29 13:07:31.336924+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 28, "whyItWorks": "Solves two failure modes at once. (1) The buried claim: action titles place the conclusion on the page before any analysis is read, so a busy reader doesn't reverse-engineer it from the chart. (2) The spineless deck: because each title is a claim, slides have to ladder up to the governing thought; logical gaps become visible as topic-shaped titles in a sequence that no longer reads as a story.", "antipattern": "Topic labels disguised as titles — Volume by quarter, Key findings, Pricing strategy, Margins have been impacted. No verb, or a passive verb with no agent, or a fact (Revenue grew 12%) without the so-what. Also: titles that overreach the chart's evidence, multi-claim X-grew-but-Y-fell welded titles, and mechanical repetition of the same X-drove-Y template across the deck.", "cardinality": null, "narrativePurpose": "Forces the deck to carry its argument in the title bar so a senior reader can extract the recommendation without opening a single slide; converts a binder of topics into a navigable pyramid where every slide is a node defending the apex." }, { "tool": { "name": "Concrete Language", "slug": "concrete-language", "status": "active", "bestFor": null, "canonId": "019dd956-bcd4-7398-9723-6aa72346170b", "version": 1, "bodyDocId": null, "description": "Using specific sensory details instead of abstract terms", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Storyteller", "layer": "slide", "agents": [ "Storyteller" ], "matchId": "019dd95a-0f08-73d3-987d-4f80b0164f8c", "evidence": "Budget share trajectory 11% -> 25% -> 31%.", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 85, "extraction": { "at": "2026-04-29 13:07:31.336924+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 28, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "Closing Techniques", "slug": "closing-techniques", "status": "active", "bestFor": null, "canonId": "019dd956-af13-774b-a4fd-7db0a3a88d51", "version": 1, "bodyDocId": null, "description": "Strong endings: Callback, challenge, vision, clear CTA, memorable line", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Storyteller", "layer": "slide", "agents": [ "Storyteller" ], "matchId": "019dd95a-0f08-73d3-987d-55f52d3b63a7", "evidence": "Vision statement designed as the deck's emotional crescendo.", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 75, "extraction": { "at": "2026-04-29 13:07:31.336924+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 29, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "Emotional Appeal", "slug": "emotional-appeal", "status": "active", "bestFor": null, "canonId": "019dd956-bde9-7668-8be7-0097678fec59", "version": 1, "bodyDocId": null, "description": "Connecting to audience feelings rather than just logic", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Storyteller", "layer": "slide", "agents": [ "Storyteller" ], "matchId": "019dd95a-0f08-73d3-987d-5377d11fdccf", "evidence": "Full-bleed silhouette with arms raised under the 7%->20% claim.", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 80, "extraction": { "at": "2026-04-29 13:07:31.336924+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 29, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "Picture Superiority Effect", "slug": "picture-superiority-effect", "status": "active", "bestFor": null, "canonId": "019dd956-c201-7014-bb58-3e85e3e11dfd", "version": 1, "bodyDocId": null, "description": "Pictures remembered 6x better than words - prioritize visuals over text", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Designer", "layer": "slide", "agents": [ "Designer" ], "matchId": "019dd95a-0f08-73d3-987d-6271fd647b61", "evidence": "Single hero image carries the whole vision statement.", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 70, "extraction": { "at": "2026-04-29 13:07:31.336924+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 29, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "Section divider", "slug": "section-divider", "status": "active", "bestFor": null, "canonId": "019dd9e1-4c66-707d-8d1f-6e14547134c7", "version": 1, "bodyDocId": null, "description": "A transitional slide marking the start of a new section.", "familyLabel": null, "categoryName": null, "categorySlug": null }, "agent": null, "layer": "slide", "agents": null, "matchId": "dcdf4dea-6ee9-4237-88b3-3e996f6e4a52", "evidence": "Practice makes progress", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 0.8, "extraction": { "at": "2026-07-16 21:02:24.552402+00", "model": "or:meta-llama/llama-4-scout", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 30, "whyItWorks": null, "antipattern": null, "cardinality": "common", "narrativePurpose": null }, { "tool": { "name": "Action Titles", "slug": "action-titles", "status": "active", "bestFor": "Any decision-grade deliverable — strategy recommendation, board update, investment memo, M&A review, post-mortem — where the reader is being asked to agree, decide, or act and will skim the title bar at speed.", "canonId": "019dd956-ac70-700b-a608-ba58e78f5dcc", "version": 1, "bodyDocId": "816dad3c-9983-41c1-a86e-978ebd582841", "description": "The McKinsey-bred discipline of writing every slide title as a complete declarative sentence with a verb and an insight, not a topic label. Each title is a sub-claim that ladders up to the deck's governing thought; read in sequence, the titles reconstruct the executive summary.", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Architect", "layer": "slide", "agents": [ "Architect" ], "matchId": "019dd95a-0f08-73d3-987d-679eabe98641", "evidence": "'Practice makes progress' is a memorable verbal hook.", "pageRefs": null, "priority": "Core", "whenToUse": "Any decision-grade deliverable — strategy recommendation, board update, investment memo, M&A review, post-mortem — where the reader is being asked to agree, decide, or act and will skim the title bar at speed.", "confidence": 75, "extraction": { "at": "2026-04-29 13:07:31.336924+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 31, "whyItWorks": "Solves two failure modes at once. (1) The buried claim: action titles place the conclusion on the page before any analysis is read, so a busy reader doesn't reverse-engineer it from the chart. (2) The spineless deck: because each title is a claim, slides have to ladder up to the governing thought; logical gaps become visible as topic-shaped titles in a sequence that no longer reads as a story.", "antipattern": "Topic labels disguised as titles — Volume by quarter, Key findings, Pricing strategy, Margins have been impacted. No verb, or a passive verb with no agent, or a fact (Revenue grew 12%) without the so-what. Also: titles that overreach the chart's evidence, multi-claim X-grew-but-Y-fell welded titles, and mechanical repetition of the same X-drove-Y template across the deck.", "cardinality": null, "narrativePurpose": "Forces the deck to carry its argument in the title bar so a senior reader can extract the recommendation without opening a single slide; converts a binder of topics into a navigable pyramid where every slide is a node defending the apex." }, { "tool": { "name": "Closing Techniques", "slug": "closing-techniques", "status": "active", "bestFor": null, "canonId": "019dd956-af13-774b-a4fd-7db0a3a88d51", "version": 1, "bodyDocId": null, "description": "Strong endings: Callback, challenge, vision, clear CTA, memorable line", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Storyteller", "layer": "slide", "agents": [ "Storyteller" ], "matchId": "019dd95a-0f08-73d3-987d-6a7f6b0fbd4c", "evidence": "Coined phrase plus 'cloud as enabler, data as driver, AI as differentiator' tricolon.", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 75, "extraction": { "at": "2026-04-29 13:07:31.336924+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 31, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "Core Message Extraction", "slug": "core-message-extraction", "status": "active", "bestFor": "Any slide that carries an argument or finding. The diagnostic: if the slide has a chart on it, it needs a core message. Run extraction whenever the current title is a topic (Q3 performance, Customer satisfaction) rather than a claim, or when a reader could reasonably draw more than one conclusion from the visible evidence.", "canonId": "019dd956-bc71-707d-8867-1b2e810175cf", "version": 1, "bodyDocId": "f85613cb-4b77-462f-bfe6-3b862516e1a6", "description": "The discipline of distilling raw analysis, data, or content into a single declarative sentence — the slide's core message — that the audience would walk away with if they remembered nothing else. Process, not artefact: extraction questions run on the raw content until one sentence falls out.", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Architect", "layer": "slide", "agents": [ "Architect" ], "matchId": "019dd95a-0f08-73d3-987d-73600343e645", "evidence": "Synthesises the deck thesis in a single sentence.", "pageRefs": null, "priority": null, "whenToUse": "Any slide that carries an argument or finding. The diagnostic: if the slide has a chart on it, it needs a core message. Run extraction whenever the current title is a topic (Q3 performance, Customer satisfaction) rather than a claim, or when a reader could reasonably draw more than one conclusion from the visible evidence.", "confidence": 70, "extraction": { "at": "2026-04-29 13:07:31.336924+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 31, "whyItWorks": "Solves the two failure modes of slide writing simultaneously: the topic title (which outsources interpretation to the audience and produces three different conclusions in three different heads) and the multi-thesis stapler (which exceeds working memory and gets remembered as fragments). Aligns with how readers actually consume decks — Heath & Heath's Find the Core, the journalist's nut graf, and Minto's governing thought all converge on the same cognitive economics.", "antipattern": "Topic titles disguised as core messages (Customer satisfaction, no verb, no stake); multi-thesis sentences stapled with and; hedged sentences (may show signs of possible softening); chart-caption titles (Revenue fell 4%) that restate what the chart already shows instead of naming the so-what; meta-commentary (this slide explores...) that describes the slide rather than concluding it.", "cardinality": null, "narrativePurpose": "Forces the slide author to do the interpretive work before the slide ships, so the audience does not have to do it during the meeting. Wins the WYSIATI battle on purpose — the loudest fragment on the page becomes the author's chosen sentence rather than whichever chart label happens to be largest." }, { "tool": { "name": "Action Titles", "slug": "action-titles", "status": "active", "bestFor": "Any decision-grade deliverable — strategy recommendation, board update, investment memo, M&A review, post-mortem — where the reader is being asked to agree, decide, or act and will skim the title bar at speed.", "canonId": "019dd956-ac70-700b-a608-ba58e78f5dcc", "version": 1, "bodyDocId": "816dad3c-9983-41c1-a86e-978ebd582841", "description": "The McKinsey-bred discipline of writing every slide title as a complete declarative sentence with a verb and an insight, not a topic label. Each title is a sub-claim that ladders up to the deck's governing thought; read in sequence, the titles reconstruct the executive summary.", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Architect", "layer": "slide", "agents": [ "Architect" ], "matchId": "019dd95a-0f08-73d3-987d-75ffc593d341", "evidence": "Figure 7 framed as 'sample questions for C-suite leaders'.", "pageRefs": null, "priority": "Core", "whenToUse": "Any decision-grade deliverable — strategy recommendation, board update, investment memo, M&A review, post-mortem — where the reader is being asked to agree, decide, or act and will skim the title bar at speed.", "confidence": 70, "extraction": { "at": "2026-04-29 13:07:31.336924+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 32, "whyItWorks": "Solves two failure modes at once. (1) The buried claim: action titles place the conclusion on the page before any analysis is read, so a busy reader doesn't reverse-engineer it from the chart. (2) The spineless deck: because each title is a claim, slides have to ladder up to the governing thought; logical gaps become visible as topic-shaped titles in a sequence that no longer reads as a story.", "antipattern": "Topic labels disguised as titles — Volume by quarter, Key findings, Pricing strategy, Margins have been impacted. No verb, or a passive verb with no agent, or a fact (Revenue grew 12%) without the so-what. Also: titles that overreach the chart's evidence, multi-claim X-grew-but-Y-fell welded titles, and mechanical repetition of the same X-drove-Y template across the deck.", "cardinality": null, "narrativePurpose": "Forces the deck to carry its argument in the title bar so a senior reader can extract the recommendation without opening a single slide; converts a binder of topics into a navigable pyramid where every slide is a node defending the apex." }, { "tool": { "name": "Gestalt Principles", "slug": "gestalt-principles", "status": "active", "bestFor": null, "canonId": "019dd956-b266-7631-9b7e-44d83bd5d4f3", "version": 1, "bodyDocId": null, "description": "Proximity, Similarity, Enclosure, Continuity, Closure, Connection - how humans perceive visual groups", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Designer", "layer": "slide", "agents": [ "Designer", "Architect" ], "matchId": "019dd95a-0f08-73d3-987d-7aa1252abdbd", "evidence": "Coloured row labels group questions by capability category.", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 70, "extraction": { "at": "2026-04-29 13:07:31.336924+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 32, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "Nudge", "slug": "nudge", "status": "active", "bestFor": null, "canonId": "019dd956-c61a-72f9-920c-88acf4ecc336", "version": 1, "bodyDocId": null, "description": "Subtle hints can significantly affect decisions - strategic CTA placement", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Designer", "layer": "slide", "agents": [ "Architect", "Designer" ], "matchId": "019dd95a-0f08-73d3-987d-8297cb9ccde8", "evidence": "Self-diagnostic questions nudge readers toward an internal audit.", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 60, "extraction": { "at": "2026-04-29 13:07:31.336924+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 32, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "Concrete Language", "slug": "concrete-language", "status": "active", "bestFor": null, "canonId": "019dd956-bcd4-7398-9723-6aa72346170b", "version": 1, "bodyDocId": null, "description": "Using specific sensory details instead of abstract terms", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Storyteller", "layer": "slide", "agents": [ "Storyteller" ], "matchId": "019dd95a-0f08-73d3-987d-84e76c6be040", "evidence": "Median maturity index of 36/100 quoted in callout.", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 70, "extraction": { "at": "2026-04-29 13:07:31.336924+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 35, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "Authority Bias", "slug": "authority-bias", "status": "active", "bestFor": null, "canonId": "019dd956-c38d-70b9-a284-b2b479763356", "version": 1, "bodyDocId": null, "description": "Expert opinions are weighted more heavily - cite credible sources", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Storyteller", "layer": "slide", "agents": [ "Architect", "Storyteller" ], "matchId": "019dd95a-0f08-73d3-987d-8e40eb36dfe4", "evidence": "Statistical-significance language adds methodological credibility.", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 65, "extraction": { "at": "2026-04-29 13:07:31.336924+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 36, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "Concrete Language", "slug": "concrete-language", "status": "active", "bestFor": null, "canonId": "019dd956-bcd4-7398-9723-6aa72346170b", "version": 1, "bodyDocId": null, "description": "Using specific sensory details instead of abstract terms", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Storyteller", "layer": "slide", "agents": [ "Storyteller" ], "matchId": "019dd95a-0f08-73d3-987d-8a56f27d2031", "evidence": "p < 0.01 significance for CX and sustainability differences.", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 70, "extraction": { "at": "2026-04-29 13:07:31.336924+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 36, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null } ], "frameworks": [ { "matchId": "c612ce1d-1232-4ca0-8e9c-a46233784537", "evidence": "Slide title references AI maturity", "framework": null, "confidence": 0.7, "extraction": { "at": "2026-05-02 19:49:06.539+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 7, "frameworkName": "maturity-model" }, { "matchId": "019dd95a-1ca5-70bb-bb9f-4dfad538ddcc", "evidence": "Two overlaid S-curves comparing AI vs digital transformation adoption.", "framework": null, "confidence": 75, "extraction": { "at": "2026-04-29 13:07:34.826634+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 7, "frameworkName": "S-Curve / Diffusion Curve" }, { "matchId": "f9a265ce-9abd-47d5-bcb5-2c2a8d99fa98", "evidence": "The slide explicitly discusses an 'AI-maturity framework' and defines the concept of maturity.", "framework": null, "confidence": 0.9, "extraction": { "at": "2026-05-02 19:49:11.107+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 10, "frameworkName": "maturity-model" }, { "matchId": "019dd95a-1ca5-70bb-bb9f-51648a4e750f", "evidence": "Axes labelled 'AI Foundation' (x) and 'AI Differentiation' (y); four named quadrants.", "framework": null, "confidence": 95, "extraction": { "at": "2026-04-29 13:07:34.826634+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 11, "frameworkName": "2x2 Matrix" }, { "matchId": "1fc3a0c9-c4cf-4b50-9242-33c1d08ebd78", "evidence": "The slide uses a 2x2 grid to categorize companies based on two axes: AI Foundation and AI Differentiation.", "framework": null, "confidence": 1, "extraction": { "at": "2026-05-02 19:49:12.308+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 11, "frameworkName": "matrix-2x2" }, { "matchId": "5b97fe21-6bb3-465b-a20a-0d2619218219", "evidence": "The chart tracks the evolution of AI maturity scores over time across industries.", "framework": null, "confidence": 0.9, "extraction": { "at": "2026-05-02 19:49:07.307+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 12, "frameworkName": "maturity-model" }, { "matchId": "019dd95a-1ca5-70bb-bb9f-57dbefdb2e6f", "evidence": "17 capabilities x 4 archetypes grid with filled/hollow performance markers.", "framework": null, "confidence": 80, "extraction": { "at": "2026-04-29 13:07:34.826634+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 15, "frameworkName": "Capability Heatmap" }, { "matchId": "fdb3c76e-c57c-48f3-8dbd-1913fd5752f4", "evidence": "Categorization of AI profiles (Achievers, Builders, Innovators, Experimenters) across capabilities", "framework": null, "confidence": 0.9, "extraction": { "at": "2026-05-02 19:49:08.583+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 15, "frameworkName": "maturity-model" }, { "matchId": "378d7092-238a-4cd5-ad30-6bc4db81fce8", "evidence": "Mentions 'AI maturity' and 'benchmark AI maturity'", "framework": null, "confidence": 0.8, "extraction": { "at": "2026-05-02 19:49:10.543+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 31, "frameworkName": "maturity-model" }, { "matchId": "019dd95a-1ca5-70bb-bb9f-5b9f4ef5ba08", "evidence": "Four named pillars: Strategy & Sponsorship, Data & AI Core, Talent & Culture, Responsible AI.", "framework": null, "confidence": 85, "extraction": { "at": "2026-04-29 13:07:34.826634+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 32, "frameworkName": "AI Maturity Model" }, { "matchId": "3d5d0e70-7f6c-4c77-9e9e-ea1f534d2392", "evidence": "The slide explicitly labels the content as an 'AI maturity assessment' and categorizes questions into pillars of maturity.", "framework": null, "confidence": 1, "extraction": { "at": "2026-05-02 19:49:09.608+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 32, "frameworkName": "maturity-model" }, { "matchId": "f454066a-9439-477b-9de4-cc73c40e3880", "evidence": "Description of regression modeling and K-fold cross-validation", "framework": null, "confidence": 0.9, "extraction": { "at": "2026-05-02 19:49:10.638+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 35, "frameworkName": "analytical-method" }, { "matchId": "ff1a1e4f-08c7-48ce-a58a-52295c1abe5c", "evidence": "The slide outlines the specific statistical and analytical steps taken to derive study conclusions.", "framework": null, "confidence": 0.9, "extraction": { "at": "2026-05-02 19:49:09.948+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 36, "frameworkName": "analytical-method" } ], "patterns": [] }, "storymakers": { "model": "claude-cli-sonnet-4.6", "backend": null, "rawJson": { "arc": { "id": 1, "slug": "consultants-gambit", "beats": [ { "name": "Situation & Context", "end_page": 8, "evidence": "AI is essential, transformation 16 months faster than digital.", "position": 1, "start_page": 3 }, { "name": "Problem & Complication", "end_page": 13, "evidence": "AI maturity defined; only 7% qualify as Achievers (Fig 3 2x2).", "position": 2, "start_page": 9 }, { "name": "Evidence & Proof", "end_page": 17, "evidence": "Achievers enjoy 50% greater revenue growth, scale pilots more, lead on sustainability.", "position": 3, "start_page": 14 }, { "name": "Solution & Approach", "end_page": 28, "evidence": "Five success factors: leadership, talent, AI core, responsible AI, investment.", "position": 4, "start_page": 18 }, { "name": "Impact & Next Steps", "end_page": 32, "evidence": "7%->20% projection, 'practice makes progress', C-suite assessment table p32.", "position": 5, "start_page": 29 } ], "evidence": "Classic SCR-evidence-recs flow: context p3-8, complication p9-13 (only 7% are Achievers), proof p14-17 (50% revenue lift), 5 recs p20-28, impact p29-32.", "confidence": 88 }, "loops": [ { "id": 3, "slug": "03-aha-moment", "end_page": 5, "evidence": "Problem framing (AI ubiquity) -> data (7% Achievers) -> insight (5 differentiators).", "position": 1, "objective": "Open with the question and the 7%/20% reveal", "confidence": 75, "start_page": 3 }, { "id": 15, "slug": "15-why-now", "end_page": 8, "evidence": "Trends (CEO mentions, 75% integration), trigger (early ROI), 16-month window vs digital.", "position": 2, "objective": "Justify urgency of acting on AI maturity", "confidence": 80, "start_page": 7 }, { "id": 30, "slug": "30-2x2-matrix", "end_page": 13, "evidence": "Fig 3 2x2 with axes AI Foundation/Differentiation defines Achievers/Innovators/Builders/Experimenters.", "position": 3, "objective": "Segment firms via the AI Foundation x Differentiation 2x2", "confidence": 92, "start_page": 10 }, { "id": 39, "slug": "39-benchmark-gap", "end_page": 17, "evidence": "50% greater revenue growth, 5% more likely to scale pilots, capability matrix vs peers.", "position": 4, "objective": "Quantify the performance gap between Achievers and others", "confidence": 85, "start_page": 15 }, { "id": 40, "slug": "40-mece-breakdown", "end_page": 28, "evidence": "Five labelled 'Success Factor 0X' sections each pairing recommendation + case study.", "position": 5, "objective": "Lay out five MECE success factors with evidence and cases", "confidence": 88, "start_page": 20 }, { "id": 24, "slug": "24-time-machine", "end_page": 32, "evidence": "Full-bleed 7%->20% by 2024 vision slide, then C-suite questions to act now.", "position": 6, "objective": "Cast forward to 2024 vision and route back to today's assessment", "confidence": 78, "start_page": 29 } ], "slide_tools": [ { "tools": [ { "id": 118, "slug": "action-titles", "layer": "Slide", "evidence": "Subhead frames the so-what about NA pace of AI.", "confidence": 70 }, { "id": 154, "slug": "concrete-language", "layer": "Slide", "evidence": "Callout: '16 months faster than digital transformation'.", "confidence": 85 }, { "id": 109, "slug": "information-gap-theory", "layer": "Loop", "evidence": "Opens loop by raising the AI-maturity question without answering.", "confidence": 70 }, { "id": 56, "slug": "anchoring-bias", "layer": "Block", "evidence": "Sets '16 months faster' as the framing anchor for the deck.", "confidence": 65 }, { "id": 3, "slug": "pyramid-principle", "layer": "Block", "evidence": "Top-line answer (NA perspective on AI maturity) precedes supporting data.", "confidence": 60 } ], "page_number": 3 }, { "tools": [ { "id": 123, "slug": "opening-hooks", "layer": "Slide", "evidence": "'In fewer than 70 years...' opens with a startling time-scale frame.", "confidence": 80 }, { "id": 154, "slug": "concrete-language", "layer": "Slide", "evidence": "Callout quantifies '7% of firms have advanced their AI maturity'.", "confidence": 85 }, { "id": 153, "slug": "core-message-extraction", "layer": "Slide", "evidence": "Distils whole report into the 7% Achievers thesis.", "confidence": 70 } ], "page_number": 4 }, { "tools": [ { "id": 118, "slug": "action-titles", "layer": "Slide", "evidence": "Provocative question title: 'What do AI Achievers do differently?'", "confidence": 80 }, { "id": 116, "slug": "chunking", "layer": "Loop", "evidence": "Five numbered success factors presented as a memorable list.", "confidence": 80 }, { "id": 99, "slug": "foreshadowing", "layer": "Loop", "evidence": "Lists the five factors that Section 4 will unpack one by one.", "confidence": 80 }, { "id": 67, "slug": "curiosity-gap", "layer": "Block", "evidence": "Question title plus enumerated answers create resolution-seeking tension.", "confidence": 75 } ], "page_number": 5 }, { "tools": [ { "id": 118, "slug": "action-titles", "layer": "Slide", "evidence": "Subhead asserts insight: 'AI is absolutely essential to competitive advantage'.", "confidence": 85 }, { "id": 129, "slug": "chart-selection-guide", "layer": "Slide", "evidence": "S-curve compares AI vs digital transformation diffusion.", "confidence": 80 }, { "id": 138, "slug": "annotation", "layer": "Slide", "evidence": "Callout '16 months (13%)' annotates the gap between curves.", "confidence": 85 }, { "id": 154, "slug": "concrete-language", "layer": "Slide", "evidence": "46% of CEOs, 75% integration, 26% scaled pilots.", "confidence": 85 }, { "id": 86, "slug": "causal-chain", "layer": "Loop", "evidence": "Early ROI -> confidence -> faster adoption -> 16-month lead.", "confidence": 65 } ], "page_number": 7 }, { "tools": [ { "id": 129, "slug": "chart-selection-guide", "layer": "Slide", "evidence": "Sankey-style flow shows revenue-share migration 9%->21%->30%.", "confidence": 80 }, { "id": 130, "slug": "color-strategy", "layer": "Slide", "evidence": "Purple gradient encodes High/Medium/Low AI-influenced bands.", "confidence": 75 }, { "id": 138, "slug": "annotation", "layer": "Slide", "evidence": "Endpoint labels 9%/21%/30% pinpoint the trajectory.", "confidence": 75 }, { "id": 154, "slug": "concrete-language", "layer": "Slide", "evidence": "Specific percentages and 31% 2024 budget figure in body.", "confidence": 85 } ], "page_number": 8 }, { "tools": [ { "id": 153, "slug": "core-message-extraction", "layer": "Slide", "evidence": "Defines AI maturity as the central concept for the whole report.", "confidence": 80 }, { "id": 154, "slug": "concrete-language", "layer": "Slide", "evidence": "Customers, shareholders, employees named as outcome dimensions.", "confidence": 60 } ], "page_number": 10 }, { "tools": [ { "id": 118, "slug": "action-titles", "layer": "Slide", "evidence": "Title states the so-what: 'Only 7% of organizations are AI Achievers'.", "confidence": 90 }, { "id": 132, "slug": "visual-hierarchy", "layer": "Slide", "evidence": "Big colored % per quadrant dominates the chart.", "confidence": 75 }, { "id": 138, "slug": "annotation", "layer": "Slide", "evidence": "Each quadrant labelled with name, % and short descriptor.", "confidence": 80 }, { "id": 130, "slug": "color-strategy", "layer": "Slide", "evidence": "Achievers tinted in signature purple, others muted.", "confidence": 70 }, { "id": 154, "slug": "concrete-language", "layer": "Slide", "evidence": "7%, 10%, 8%, 75% sized as headline numbers.", "confidence": 85 }, { "id": 65, "slug": "scarcity", "layer": "Block", "evidence": "Only 7% framing makes Achiever status feel scarce and aspirational.", "confidence": 75 } ], "page_number": 11 }, { "tools": [ { "id": 118, "slug": "action-titles", "layer": "Slide", "evidence": "Subhead asserts gap will narrow by 2024.", "confidence": 65 }, { "id": 154, "slug": "concrete-language", "layer": "Slide", "evidence": "Industry-level maturity scores quoted (e.g. '60').", "confidence": 70 }, { "id": 129, "slug": "chart-selection-guide", "layer": "Slide", "evidence": "Industry comparison chart shows current vs 2024 spread.", "confidence": 65 } ], "page_number": 12 }, { "tools": [ { "id": 122, "slug": "story-moments", "layer": "Slide", "evidence": "Apparel COVID e-commerce case as a concrete win moment.", "confidence": 75 }, { "id": 154, "slug": "concrete-language", "layer": "Slide", "evidence": "Callout: '50% of revenue, up from 15%'.", "confidence": 80 }, { "id": 224, "slug": "singularity-effect", "layer": "Slide", "evidence": "Single named retailer humanizes the industry-trend abstraction.", "confidence": 70 }, { "id": 70, "slug": "storytelling-effect", "layer": "Block", "evidence": "First in a sequence of company vignettes used as memory hooks.", "confidence": 70 } ], "page_number": 13 }, { "tools": [ { "id": 118, "slug": "action-titles", "layer": "Slide", "evidence": "'AI Achievers advance from practice to performance' states the verdict.", "confidence": 85 }, { "id": 154, "slug": "concrete-language", "layer": "Slide", "evidence": "'50% greater revenue growth' anchors the gap.", "confidence": 85 }, { "id": 133, "slug": "small-multiples", "layer": "Slide", "evidence": "Fig 5 grid of 17 capabilities x 4 archetypes for at-a-glance compare.", "confidence": 85 }, { "id": 130, "slug": "color-strategy", "layer": "Slide", "evidence": "Filled vs hollow squares encode out- vs under-performing.", "confidence": 75 }, { "id": 78, "slug": "contrast-pairs", "layer": "Loop", "evidence": "Sets up Achievers<->Experimenters contrast that drives the loop.", "confidence": 80 }, { "id": 80, "slug": "data-story-arc", "layer": "Loop", "evidence": "Opens benchmarking arc: context, conflict (gap), insight.", "confidence": 70 } ], "page_number": 15 }, { "tools": [ { "id": 118, "slug": "action-titles", "layer": "Slide", "evidence": "Title 'Turning pilots into production' delivers a verb-led message.", "confidence": 80 }, { "id": 154, "slug": "concrete-language", "layer": "Slide", "evidence": "60 vs 44 scale-rate, 5% more likely to scale.", "confidence": 80 } ], "page_number": 16 }, { "tools": [ { "id": 118, "slug": "action-titles", "layer": "Slide", "evidence": "'Focusing beyond financial metrics' signals the next dimension.", "confidence": 75 }, { "id": 154, "slug": "concrete-language", "layer": "Slide", "evidence": "70% reduced emissions via AI; 8% stat in body.", "confidence": 80 }, { "id": 169, "slug": "authority-bias", "layer": "Slide", "evidence": "Cites Accenture's Sustainable Technology survey of 500+ multinationals.", "confidence": 65 } ], "page_number": 17 }, { "tools": [ { "id": 118, "slug": "action-titles", "layer": "Slide", "evidence": "Action title 'Champion AI as a strategic priority...' states the rec.", "confidence": 90 }, { "id": 155, "slug": "credibility-transfer", "layer": "Slide", "evidence": "Pull quote from Stephen Squeri, CEO of American Express.", "confidence": 90 }, { "id": 169, "slug": "authority-bias", "layer": "Slide", "evidence": "Named Fortune-500 CEO as the validating voice.", "confidence": 85 }, { "id": 154, "slug": "concrete-language", "layer": "Slide", "evidence": "85% of NA Achievers vs 53% Builders, 57% Experimenters.", "confidence": 85 }, { "id": 87, "slug": "parallel-structure", "layer": "Loop", "evidence": "Opens 'Success Factor 01-05' template repeated through p28.", "confidence": 85 }, { "id": 2, "slug": "mece-principle", "layer": "Block", "evidence": "Five labelled, non-overlapping success factors structure the section.", "confidence": 80 } ], "page_number": 20 }, { "tools": [ { "id": 154, "slug": "concrete-language", "layer": "Slide", "evidence": "Callout cites US$70M and 4% vs 3% comparison.", "confidence": 75 }, { "id": 122, "slug": "story-moments", "layer": "Slide", "evidence": "Vignette of a NA Achiever embracing collaboration tools.", "confidence": 70 } ], "page_number": 21 }, { "tools": [ { "id": 118, "slug": "action-titles", "layer": "Slide", "evidence": "Action title 'Invest heavily in talent...' is the recommendation.", "confidence": 90 }, { "id": 154, "slug": "concrete-language", "layer": "Slide", "evidence": "56% with mandatory training; 35% NA stat.", "confidence": 85 } ], "page_number": 22 }, { "tools": [ { "id": 154, "slug": "concrete-language", "layer": "Slide", "evidence": "35% Achievers vs 33% Innovators vs 27% Experimenters.", "confidence": 80 }, { "id": 122, "slug": "story-moments", "layer": "Slide", "evidence": "Case illustration of AI talent depth across firm.", "confidence": 65 } ], "page_number": 23 }, { "tools": [ { "id": 118, "slug": "action-titles", "layer": "Slide", "evidence": "Action title 'Industrialize AI tools and teams to create an AI core'.", "confidence": 90 }, { "id": 154, "slug": "concrete-language", "layer": "Slide", "evidence": "80% callout; 72% more likely vs Experimenters.", "confidence": 85 } ], "page_number": 24 }, { "tools": [ { "id": 154, "slug": "concrete-language", "layer": "Slide", "evidence": "5% Y1 efficiency, $100M annual savings target.", "confidence": 85 }, { "id": 122, "slug": "story-moments", "layer": "Slide", "evidence": "Industrialization case quantified with savings figure.", "confidence": 70 } ], "page_number": 25 }, { "tools": [ { "id": 118, "slug": "action-titles", "layer": "Slide", "evidence": "Action title 'Design AI responsibly, from the start'.", "confidence": 90 }, { "id": 154, "slug": "concrete-language", "layer": "Slide", "evidence": "97% expect regulatory impact; 77% say company-wide priority.", "confidence": 85 } ], "page_number": 26 }, { "tools": [ { "id": 154, "slug": "concrete-language", "layer": "Slide", "evidence": "Only 3% have responsible AI today vs 45% targeting it by 2024.", "confidence": 85 }, { "id": 79, "slug": "tension-management", "layer": "Loop", "evidence": "Contrasts current 3% with aspirational 45% to manufacture urgency.", "confidence": 60 } ], "page_number": 27 }, { "tools": [ { "id": 118, "slug": "action-titles", "layer": "Slide", "evidence": "Action title 'Prioritize long- and short-term AI investments'.", "confidence": 90 }, { "id": 154, "slug": "concrete-language", "layer": "Slide", "evidence": "Budget share trajectory 11% -> 25% -> 31%.", "confidence": 85 } ], "page_number": 28 }, { "tools": [ { "id": 156, "slug": "emotional-appeal", "layer": "Slide", "evidence": "Full-bleed silhouette with arms raised under the 7%->20% claim.", "confidence": 80 }, { "id": 124, "slug": "closing-techniques", "layer": "Slide", "evidence": "Vision statement designed as the deck's emotional crescendo.", "confidence": 75 }, { "id": 96, "slug": "the-turn", "layer": "Loop", "evidence": "Pivot from past data to forward-looking 2024 trajectory.", "confidence": 75 }, { "id": 100, "slug": "payoff", "layer": "Loop", "evidence": "Delivers on the 7%->20% promise foreshadowed back on p5.", "confidence": 70 }, { "id": 165, "slug": "picture-superiority-effect", "layer": "Slide", "evidence": "Single hero image carries the whole vision statement.", "confidence": 70 } ], "page_number": 29 }, { "tools": [ { "id": 118, "slug": "action-titles", "layer": "Slide", "evidence": "'Practice makes progress' is a memorable verbal hook.", "confidence": 75 }, { "id": 124, "slug": "closing-techniques", "layer": "Slide", "evidence": "Coined phrase plus 'cloud as enabler, data as driver, AI as differentiator' tricolon.", "confidence": 75 }, { "id": 92, "slug": "tricolon", "layer": "Loop", "evidence": "Three parallel clauses: cloud-enabler / data-driver / AI-differentiator.", "confidence": 80 }, { "id": 153, "slug": "core-message-extraction", "layer": "Slide", "evidence": "Synthesises the deck thesis in a single sentence.", "confidence": 70 } ], "page_number": 31 }, { "tools": [ { "id": 118, "slug": "action-titles", "layer": "Slide", "evidence": "Figure 7 framed as 'sample questions for C-suite leaders'.", "confidence": 70 }, { "id": 131, "slug": "gestalt-principles", "layer": "Slide", "evidence": "Coloured row labels group questions by capability category.", "confidence": 70 }, { "id": 116, "slug": "chunking", "layer": "Loop", "evidence": "Questions chunked into four MECE capability buckets.", "confidence": 70 }, { "id": 174, "slug": "nudge", "layer": "Slide", "evidence": "Self-diagnostic questions nudge readers toward an internal audit.", "confidence": 60 } ], "page_number": 32 }, { "tools": [ { "id": 154, "slug": "concrete-language", "layer": "Slide", "evidence": "Median maturity index of 36/100 quoted in callout.", "confidence": 70 } ], "page_number": 35 }, { "tools": [ { "id": 154, "slug": "concrete-language", "layer": "Slide", "evidence": "p < 0.01 significance for CX and sustainability differences.", "confidence": 70 }, { "id": 169, "slug": "authority-bias", "layer": "Slide", "evidence": "Statistical-significance language adds methodological credibility.", "confidence": 65 } ], "page_number": 36 } ], "slides_seen": 40, "deck_summary": "Textbook Accenture thought-leadership: a Consultant's Gambit dressed in a 2x2 segmentation, a benchmark gap, and a MECE list of five success factors - high alignment with Storymakers on action titles, concrete numbers, and the 7%->20% payoff, weaker on emotional arc until the closing vision slide.", "secondary_arcs": [ { "id": 11, "slug": "triple-take", "beats": [ { "name": "The Facts (What)", "end_page": 13, "evidence": "AI adoption stats and segmentation of the 2,000-firm sample.", "position": 1, "start_page": 3 }, { "name": "The Implications (So What)", "end_page": 17, "evidence": "Achievers outperform peers on revenue and sustainability.", "position": 2, "start_page": 14 }, { "name": "The Action (Now What)", "end_page": 32, "evidence": "Five success factors plus C-suite self-assessment.", "position": 3, "start_page": 18 } ], "evidence": "Facts (AI is here, 7% are Achievers) -> Implications (Achievers outperform) -> Action (5 factors + assess yourself).", "confidence": 60 } ], "images_inspected": 7, "slide_frameworks": [ { "frameworks": [ { "name": "S-Curve / Diffusion Curve", "slug": "s-curve-diffusion", "evidence": "Two overlaid S-curves comparing AI vs digital transformation adoption.", "confidence": 75 } ], "page_number": 7 }, { "frameworks": [ { "name": "2x2 Matrix", "slug": "2x2-matrix", "evidence": "Axes labelled 'AI Foundation' (x) and 'AI Differentiation' (y); four named quadrants.", "confidence": 95 } ], "page_number": 11 }, { "frameworks": [ { "name": "Capability Heatmap", "slug": "capability-heatmap", "evidence": "17 capabilities x 4 archetypes grid with filled/hollow performance markers.", "confidence": 80 } ], "page_number": 15 }, { "frameworks": [ { "name": "AI Maturity Model", "slug": "ai-maturity-model", "evidence": "Four named pillars: Strategy & Sponsorship, Data & AI Core, Talent & Culture, Responsible AI.", "confidence": 85 } ], "page_number": 32 } ] }, "matchedAt": "2026-04-26 01:12:53+00", "slidesSeen": 40, "deckSummary": "Textbook Accenture thought-leadership: a Consultant's Gambit dressed in a 2x2 segmentation, a benchmark gap, and a MECE list of five success factors - high alignment with Storymakers on action titles, concrete numbers, and the 7%->20% payoff, weaker on emotional arc until the closing vision slide.", "imagesInspected": 7, "extractionSeconds": 375.90997 }, "score": { "backend": null, "scoredAt": "2026-04-24 09:23:24+00", "subScores": { "mece_pillars": 41, "scqa_opening": 100, "slide_type_mix": 55, "lead_with_answer": 100, "narrative_pacing": 81.25, "action_title_density": 66.66666666666667 }, "totalScore": 74.2, "coveragePct": 100, "explanations": { "mece_pillars": "7 pillars, balance=0.27", "scqa_opening": "first-third narrative: SCSAS", "slide_type_mix": "N8% · S58% · W25% · W10%", "lead_with_answer": "executive_summary on page 4", "narrative_pacing": "12% filler/appendix, middle density 77%", "action_title_density": "16/30 substantive slides have action titles (53%)" }, "slidesAnalyzed": 40 }, "review": { "backend": null, "verdict": "A disciplined, well-architected thought-leadership deck whose five-recommendation 'How' section (p.20-28) is a clean Storymakers exemplar of imperative action titles, but the deck buries its answer for 15 pages and ends on theme rather than call-to-action — use the middle, not the opening or close, as a teaching reference.", "reviewedAt": "2026-04-24 11:02:58+00", "slidesSeen": 40, "suggestions": [ "Reframe p.32 as a titled 'Where to start Monday: five diagnostic questions' recommendation slide so the close carries an explicit CTA instead of a figure caption", "Collapse the duplicated dividers at p.18/19 and p.29/30 into a single divider each to tighten the arc and reclaim two pages for an executive summary up front", "Rewrite the context-section titles as declarative findings — e.g. p.8 'AI-influenced revenue will triple by 2024' instead of 'Figure 2: Evolution of companies' AI-influenced revenue share', and p.17 'Achievers use AI to cut emissions, not just cost' instead of 'Focusing beyond financial metrics'" ], "closingScore": 58, "openingScore": 62, "topStrengths": [ "Imperative, insight-bearing action titles across the five recommendations (p.20-28) — a textbook Storymakers pattern for a 'How' section", "Strong anchoring statistic (7% Achievers → 20% by 2024) repeated on p.4, p.5, and p.29 to make the thesis memorable", "Explicit MECE-shaped divider sequence (Why/What/How) on p.6, 9, 14, 18 that signals the architecture of the argument" ], "topWeaknesses": [ "No true call-to-action close — the deck ends on a thematic p.31 and an assessment figure (p.32) rather than an explicit 'next steps' recommendation slide", "Duplicate section dividers (p.18 = p.19, and p.29-30 pair) that break the discipline of the pillar structure", "Central question posed on p.5 ('What do AI Achievers do differently?') is not answered until p.20 — 15 slides of context before payoff", "Context-section titles are topic labels ('AI, applied' p.12, 'Focusing beyond financial metrics' p.17) rather than declarative insights" ], "narrativeScore": 72, "pillarCritique": "Dividers are genuinely MECE-shaped (Why it matters → What it is → Advance from practice to performance → How Achievers master their craft) rather than topic dumps, but execution is sloppy: p.18 and p.19 are both dividers with the same title, and p.29/30 repeat the pattern, undermining the structural discipline.", "closingCritique": "The close softens into a thematic p.31 ('Practice makes progress') and a useful but tucked-away self-assessment on p.32 before author bios — there is no explicit 'what to do Monday' recommendation slide or call-to-action. The assessment table is the de facto CTA but is labeled as a figure, not framed as next steps.", "openingCritique": "Cover + TOC + context slide consume the first three pages before the thesis lands on p.4 ('7% of firms have advanced their AI maturity') and the central question ('What do AI Achievers do differently?') on p.5. Stakes are established but answer-first would have meant leading p.3 with the 7%/20% tripling hook, not the softer '16 months faster' framing.", "extractionSeconds": 72.34996, "narrativeCritique": "Clear Why-matters / What-is / How-to-master arc carried by four section dividers (p.6, 9, 14, 18) with a Situation (AI essential), Complication (only 7% Achievers), Answer (five recommendations p.20-28), and resolution (p.31 'Practice makes progress'). The arc is legible but padded — two duplicate dividers (p.18/19 and p.29/30) and a question posed on p.5 that isn't answered until p.20 diffuse the tension.", "titleQualityScore": 70, "titleQualityCritique": "The five recommendation slides (p.20, 22, 24, 26, 28) are exemplary imperative action titles — 'Champion AI as a strategic priority…', 'Invest heavily in talent…', 'Industrialize AI tools and teams…', 'Design AI responsibly, from the start'. But the context and case-study halves lean on topic labels ('AI, applied' p.12, 'AI maturity: What it is' p.10, 'Focusing beyond financial metrics' p.17) or figure-number captions ('Figure 2: Evolution of…' p.8)." }, "activistThesis": null, "pitchdeck": { "metadata": null, "profile": null }, "slides": [ { "page": 1, "type": "setup", "function": "front_matter", "imagePath": "https://imgproxy.kitesheet.com/6tmAdWZ83A2AlYwtQd_68minqcYUWIU1zdUXgmDkq2I/rs:fit:1200:1200:0/q:82/f:webp/czM6Ly9raXRlc2hlZXQvY29ycHVzL3NsaWRlcy80YzhjOTJkYWQ2NDBiZjNmL3AwMDEuanBn", "rawType": "cover", "block": null, "metadata": { "slideType": "cover", "slideTypeCanon": { "name": "Cover", "slug": "cover", "status": "active", "canonId": "019de52d-05f2-729d-9f93-e0504f0a2410", "version": 1, "description": null }, "function": "front_matter", "functionCanon": { "name": "Front matter", "slug": "front_matter", "status": "active", "canonId": "019de52d-133d-73f0-9e26-201eda96b098", "version": 1, "description": null }, "density": "sparse", "densityScore": 23, "componentCount": 5, "textChars": 211, "nDataPoints": 0, "notes": null, "elementsJson": [ "headline_text", "subtitle_text", "photo" ], "confidence": 1, "extraction": { "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "at": "2026-05-02 19:49:06.806+00", "seconds": 4.394, "promptVersion": "v2-canon-conditioned" } }, "links": { "slide": "/slides/019dd923-5ca1-7489-b633-7fa84bbf490b/1", "deck": "/decks/019dd923-5ca1-7489-b633-7fa84bbf490b", "deckAnchor": "/decks/019dd923-5ca1-7489-b633-7fa84bbf490b#slide-1", "deckJson": "/decks/019dd923-5ca1-7489-b633-7fa84bbf490b.json" }, "components": [ { "bbox": null, "kind": "callout", "text": "From insights to action, the path to extraordinary value starts here.", "attrs": null, "canon": { "kind": { "name": "Callout", "slug": "callout", "status": "active", "canonId": "019de52c-f8d3-761a-8953-7d37080de5e2", "version": 1, "description": "Highlighted callout box." }, "tool": { "name": "Visual emphasis", "slug": "visual-emphasis", "status": "active", "bestFor": null, "canonId": "019dd9e1-474b-736b-a8eb-a794dd88241c", "version": 1, "bodyDocId": null, "description": "Drawing the eye to one element above the rest of the slide.", "familyLabel": null }, "subkind": null, "framework": null }, "subkind": null, "groupRole": null, "confidence": null, "extraction": { "at": "2026-04-23 22:41:05+00", "model": "claude-code-default", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "019dd951-9f64-72ba-b3fc-926300a7c7a4", "parentComponentId": null }, { "bbox": { "h": 0.016, "w": 0.398, "x": 0.301, "y": 0.931 }, "kind": "paragraph", "text": "From insights to action, the path to extraordinary value starts here.", "attrs": null, "canon": { "kind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "5f2affc0-941d-4d07-959d-4bfc1930cea4", "version": 1, "description": "Single prose block in the body of a slide." }, "tool": null, "subkind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "019de52c-fb80-75af-aa5c-a7a4bfac2433", "version": 1, "description": null }, "framework": null }, "subkind": "paragraph", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:49:06.806+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "c7f879de-e0a7-4a1b-a08b-2e75fa2152c9", "parentComponentId": null }, { "bbox": { "h": 0.05, "w": 0.606, "x": 0.197, "y": 0.398 }, "kind": "title", "text": "The art of AI maturity", "attrs": null, "canon": { "kind": { "name": "Title", "slug": "title", "status": "active", "canonId": "019de52c-f7dd-76d9-b848-b1f12bd85cf4", "version": 1, "description": "Slide title or headline." }, "tool": null, "subkind": { "name": "Headline", "slug": "headline", "status": "active", "canonId": "019de52c-fae1-7463-9a7c-d60668eced0d", "version": 1, "description": null }, "framework": null }, "subkind": "headline", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:49:06.806+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "e7f91ef7-a610-472c-93fa-ef6a40a826ae", "parentComponentId": null }, { "bbox": { "h": 0.028, "w": 0.492, "x": 0.254, "y": 0.516 }, "kind": "title", "text": "Advancing from practice to performance", "attrs": null, "canon": { "kind": { "name": "Title", "slug": "title", "status": "active", "canonId": "019de52c-f7dd-76d9-b848-b1f12bd85cf4", "version": 1, "description": "Slide title or headline." }, "tool": null, "subkind": { "name": "Subtitle", "slug": "subtitle", "status": "active", "canonId": "019de52c-fb09-739d-900c-815b0d9ac526", "version": 1, "description": null }, "framework": null }, "subkind": "subtitle", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:49:06.806+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "6dc2ade7-d669-465b-a2d8-fee926cea21a", "parentComponentId": null }, { "bbox": { "h": 0.022, "w": 0.118, "x": 0.441, "y": 0.586 }, "kind": "title", "text": "North America", "attrs": null, "canon": { "kind": { "name": "Title", "slug": "title", "status": "active", "canonId": "019de52c-f7dd-76d9-b848-b1f12bd85cf4", "version": 1, "description": "Slide title or headline." }, "tool": null, "subkind": { "name": "Subtitle", "slug": "subtitle", "status": "active", "canonId": "019de52c-fb09-739d-900c-815b0d9ac526", "version": 1, "description": null }, "framework": null }, "subkind": "subtitle", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:49:06.806+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "a89d0f65-65f1-4efd-980f-622da5146e3a", "parentComponentId": null } ], "metrics": [], "tools": [ { "tool": { "name": "Slide recipe: Cover", "slug": "cover-slide", "status": "active", "bestFor": null, "canonId": "019df269-2a08-767d-9128-e7431e6fe8a3", "version": 1, "bodyDocId": "019df269-29e5-7738-b5fa-6892e5dc8e65", "description": "The first ten seconds. Build it deliberately.", "familyLabel": "slide-recipe", "categoryName": "Slide", "categorySlug": "slide" }, "agent": "designer", "layer": "slide", "agents": [ "designer" ], "matchId": "7d6c6f14-a1de-4260-8e41-d092b097e7d6", "evidence": "This slide is a cover slide with a title, subtitle, and callout.", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 0.9, "extraction": { "at": "2026-07-16 21:02:22.342639+00", "model": "or:meta-llama/llama-4-scout", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 1, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null } ], "frameworks": [], "arcBeats": [], "loops": [], "thumbSrc": "https://imgproxy.kitesheet.com/FcxSs3p0bThxJsoOUaEAoJQtFnGwhYiayLmudM_tFR4/rs:fit:480:480:0/q:78/f:webp/czM6Ly9raXRlc2hlZXQvY29ycHVzL3NsaWRlcy80YzhjOTJkYWQ2NDBiZjNmL3AwMDEuanBn", "imagePathAlt": "https://imgproxy.kitesheet.com/Z6-tRBnqTNWou2xRF87yyN7vZYLxCC9kYW8JMsOyfQk/rs:fit:1200:1200:0/q:82/f:webp/czM6Ly9raXRlc2hlZXQvY29ycHVzL3NsaWRlcy80YzhjOTJkYWQ2NDBiZjNmL3AwMDEucG5n", "thumbSrcAlt": "https://imgproxy.kitesheet.com/WMtl19fX8NLQyvq1C-sB-Z3kz_8HWuzjxk_qnfGKUt0/rs:fit:480:480:0/q:78/f:webp/czM6Ly9raXRlc2hlZXQvY29ycHVzL3NsaWRlcy80YzhjOTJkYWQ2NDBiZjNmL3AwMDEucG5n" }, { "page": 2, "type": "setup", "function": "front_matter", "rawType": "table_of_contents", "block": null, "metadata": { "slideType": "table_of_contents", "slideTypeCanon": { "name": "Table of contents", "slug": "table_of_contents", "status": "active", "canonId": "019de52d-0643-721b-9b85-69676bb85cf8", "version": 1, "description": null }, "function": "front_matter", "functionCanon": { "name": "Front matter", "slug": "front_matter", "status": "active", "canonId": "019de52d-133d-73f0-9e26-201eda96b098", "version": 1, "description": null }, "density": "sparse", "densityScore": 10, "componentCount": 2, "textChars": 236, "nDataPoints": 0, "notes": null, "elementsJson": [ "headline_text", "icon_grid" ], "confidence": 1, "extraction": { "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "at": "2026-05-02 19:49:04.822+00", "seconds": 2.08, "promptVersion": "v2-canon-conditioned" } }, "links": { "slide": "/slides/019dd923-5ca1-7489-b633-7fa84bbf490b/2", "deck": "/decks/019dd923-5ca1-7489-b633-7fa84bbf490b", "deckAnchor": "/decks/019dd923-5ca1-7489-b633-7fa84bbf490b#slide-2", "deckJson": "/decks/019dd923-5ca1-7489-b633-7fa84bbf490b.json" }, "components": [ { "bbox": { "h": 0.69, "w": 0.884, "x": 0.058, "y": 0.189 }, "kind": "list", "text": "Foreword 03, Executive summary 04, AI maturity: Why it matters 06, AI maturity: What it is 09, AI Achievers advance from practice to performance 14, How AI Achievers master their craft 18, Practice makes progress 30, Appendix 35", "attrs": null, "canon": { "kind": { "name": "List", "slug": "list", "status": "active", "canonId": "019de52c-f94b-779b-a53b-fd4904a5f4d2", "version": 1, "description": "Bullet or numbered list." }, "tool": null, "subkind": { "name": "Bullet list", "slug": "bullet", "status": "active", "canonId": "019de52c-fc98-7169-a083-5cab805076ca", "version": 1, "description": null }, "framework": null }, "subkind": "bullet", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:49:04.822+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "8e3d9bf3-6303-4791-bf77-c52bedc1fcbf", "parentComponentId": null }, { "bbox": { "h": 0.06, "w": 0.187, "x": 0.063, "y": 0.105 }, "kind": "title", "text": "Contents", "attrs": null, "canon": { "kind": { "name": "Title", "slug": "title", "status": "active", "canonId": "019de52c-f7dd-76d9-b848-b1f12bd85cf4", "version": 1, "description": "Slide title or headline." }, "tool": null, "subkind": { "name": "Headline", "slug": "headline", "status": "active", "canonId": "019de52c-fae1-7463-9a7c-d60668eced0d", "version": 1, "description": null }, "framework": null }, "subkind": "headline", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:49:04.822+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "f7b1215a-6cb1-47d2-866e-5797a647ab33", "parentComponentId": null } ], "metrics": [], "tools": [], "frameworks": [], "arcBeats": [], "loops": [], "locked": true }, { "page": 3, "type": "setup", "title": "Includes a headshot and bio of Arnab Chakraborty.", "function": "summarize", "rawType": "executive_summary", "block": null, "metadata": { "slideType": "executive_summary", "slideTypeCanon": { "name": "Executive summary", "slug": "executive_summary", "status": "active", "canonId": "019de52d-06be-73ff-81b3-f99fe7f0025e", "version": 1, "description": null }, "function": "summarize", "functionCanon": { "name": "Summarize", "slug": "summarize", "status": "active", "canonId": "019de52d-1541-704f-b86f-bf7b75056373", "version": 1, "description": null }, "density": "overcrowded", "densityScore": 92, "componentCount": 11, "textChars": 2807, "nDataPoints": 3, "notes": "Includes a headshot and bio of Arnab Chakraborty.", "elementsJson": [ "headline_text", "subtitle_text", "paragraph", "headshot" ], "confidence": 1, "extraction": { "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "at": "2026-05-02 19:49:07.392+00", "seconds": 4.48, "promptVersion": "v2-canon-conditioned" } }, "links": { "slide": "/slides/019dd923-5ca1-7489-b633-7fa84bbf490b/3", "deck": "/decks/019dd923-5ca1-7489-b633-7fa84bbf490b", "deckAnchor": "/decks/019dd923-5ca1-7489-b633-7fa84bbf490b#slide-3", "deckJson": "/decks/019dd923-5ca1-7489-b633-7fa84bbf490b.json" }, "components": [ { "bbox": { "h": 0.135, "w": 0.258, "x": 0.632, "y": 0.295 }, "kind": "callout", "text": "The question now, for enterprises in all sectors, is: How will you use AI to differentiate your business? The answer will either lead companies to build the future or ultimately play by someone else’s rules.", "attrs": null, "canon": { "kind": { "name": "Callout", "slug": "callout", "status": "active", "canonId": "019de52c-f8d3-761a-8953-7d37080de5e2", "version": 1, "description": "Highlighted callout box." }, "tool": null, "subkind": { "name": "Primary callout", "slug": "primary", "status": "active", "canonId": "019de52c-fbd1-70eb-a9ce-8997f8674c1d", "version": 1, "description": null }, "framework": null }, "subkind": "primary", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:49:07.392+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "ba1a8863-3c69-431f-8d6b-25768af96e84", "parentComponentId": null }, { "bbox": null, "kind": "callout", "text": "The pace of AI transformation is expected to be 16 months faster than digital transformation.", "attrs": null, "canon": { "kind": { "name": "Callout", "slug": "callout", "status": "active", "canonId": "019de52c-f8d3-761a-8953-7d37080de5e2", "version": 1, "description": "Highlighted callout box." }, "tool": { "name": "Visual emphasis", "slug": "visual-emphasis", "status": "active", "bestFor": null, "canonId": "019dd9e1-474b-736b-a8eb-a794dd88241c", "version": 1, "bodyDocId": null, "description": "Drawing the eye to one element above the rest of the slide.", "familyLabel": null }, "subkind": null, "framework": null }, "subkind": null, "groupRole": null, "confidence": null, "extraction": { "at": "2026-04-23 22:41:13+00", "model": "claude-code-default", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "019dd951-9f64-72ba-b3fc-b0c22dfb7003", "parentComponentId": null }, { "bbox": { "h": 0.085, "w": 0.055, "x": 0.632, "y": 0.748 }, "kind": "image", "text": null, "attrs": null, "canon": { "kind": { "name": "Image", "slug": "image", "status": "active", "canonId": "019de52c-f978-701f-a720-51d029d769e7", "version": 1, "description": "Photo, illustration, screenshot or icon." }, "tool": null, "subkind": { "name": "Headshot", "slug": "headshot", "status": "active", "canonId": "019de52c-fd5f-765c-9282-38b54f61bbbf", "version": 1, "description": null }, "framework": null }, "subkind": "headshot", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:49:07.392+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "df0ae577-feed-442e-a36d-7b0edec04dfe", "parentComponentId": null }, { "bbox": null, "kind": "metric", "text": "North America share of global AI market: 43%", "attrs": null, "canon": { "kind": { "name": "Metric", "slug": "metric", "status": "active", "canonId": "019de52c-f923-73bf-8081-d0b1a8c5264d", "version": 1, "description": "Big-number or KPI value." }, "tool": { "name": "Quantification", "slug": "quantification", "status": "active", "bestFor": null, "canonId": "019dd9e1-47ab-72ce-a079-aab1f5299e88", "version": 1, "bodyDocId": null, "description": "Translating a claim into numbers, charts, or tables.", "familyLabel": null }, "subkind": null, "framework": null }, "subkind": "primary", "groupRole": null, "confidence": null, "extraction": { "at": "2026-04-23 22:41:13+00", "model": "claude-code-default", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "019dd951-9f64-72ba-b3fc-b8c9ba24a183", "parentComponentId": null }, { "bbox": { "h": 0.155, "w": 0.258, "x": 0.632, "y": 0.503 }, "kind": "paragraph", "text": "What’s more, we found that the share of company revenue that was “AI-influenced” more than doubled between 2018 and 2021. That percentage is expected to roughly triple by 2024. And while there is no one-size- fits-all approach, today’s AI Achievers have set the standard for companies willing to advance and invest in their AI maturity.", "attrs": null, "canon": { "kind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "5f2affc0-941d-4d07-959d-4bfc1930cea4", "version": 1, "description": "Single prose block in the body of a slide." }, "tool": null, "subkind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "019de52c-fb80-75af-aa5c-a7a4bfac2433", "version": 1, "description": null }, "framework": null }, "subkind": "paragraph", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:49:07.392+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "1bd55646-cc52-4631-a593-48cd3abde29a", "parentComponentId": null }, { "bbox": { "h": 0.555, "w": 0.258, "x": 0.345, "y": 0.295 }, "kind": "paragraph", "text": "And while currently only 7% of organizations in North America are AI Achievers, there are tremendous growth opportunities on the horizon. Already, the AI industry landscape is shifting. In February 2019, the US government launched the American AI Initiative as the nation’s strategy for promoting leadership in artificial intelligence. As part of this initiative, federal agencies attempted to foster public trust in AI-based systems by establishing guidelines for its development and real-life implementation across different industrial sectors. In response, several financial institutions have switched over to monitoring transactions with AI. The US healthcare has also increased its use of AI and is at the forefront of drug discovery, medical diagnostics, bio-engineering designs, precision surgeries, and the use of algorithms to improve diagnoses and treatments. In retail, computer vision that uses cameras to automate inventory management will revolutionize the shopping experience for brands and consumers alike.", "attrs": null, "canon": { "kind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "5f2affc0-941d-4d07-959d-4bfc1930cea4", "version": 1, "description": "Single prose block in the body of a slide." }, "tool": null, "subkind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "019de52c-fb80-75af-aa5c-a7a4bfac2433", "version": 1, "description": null }, "framework": null }, "subkind": "paragraph", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:49:07.392+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "418b7352-31de-442f-bbe7-6b03a7fc338f", "parentComponentId": null }, { "bbox": { "h": 0.085, "w": 0.15, "x": 0.695, "y": 0.748 }, "kind": "paragraph", "text": "Arnab Chakraborty\nSenior Managing Director, North America Lead, Applied Intelligence", "attrs": null, "canon": { "kind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "5f2affc0-941d-4d07-959d-4bfc1930cea4", "version": 1, "description": "Single prose block in the body of a slide." }, "tool": null, "subkind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "019de52c-fb80-75af-aa5c-a7a4bfac2433", "version": 1, "description": null }, "framework": null }, "subkind": "paragraph", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:49:07.392+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "8b1e6495-84cd-4c37-9960-bf2faa2b3013", "parentComponentId": null }, { "bbox": { "h": 0.415, "w": 0.258, "x": 0.058, "y": 0.295 }, "kind": "paragraph", "text": "Today, AI is essential to gaining a competitive advantage in the marketplace. That’s especially true in North America, which led the global AI market last year, accounting for about 43% of the overall revenue—a number that is estimated to triple by 2024. As enterprises gain confidence in AI as a value driver, it will be full speed ahead: The pace of AI transformation is expected to be 16 months faster than digital transformation. In this report, we reveal the secrets behind the early success of “AI Achievers.” These companies have foundational AI capabilities, such as cloud platforms and governance structures, that provide competitive differentiation. AI Achievers also have strong C-suite sponsorship for their AI strategies and support a culture of innovation.", "attrs": null, "canon": { "kind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "5f2affc0-941d-4d07-959d-4bfc1930cea4", "version": 1, "description": "Single prose block in the body of a slide." }, "tool": null, "subkind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "019de52c-fb80-75af-aa5c-a7a4bfac2433", "version": 1, "description": null }, "framework": null }, "subkind": "paragraph", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:49:07.392+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "a93ffbc9-225a-4862-8316-f13619ebb958", "parentComponentId": null }, { "bbox": null, "kind": "quote", "text": "The question now, for enterprises in all sectors, is: How will you use AI to differentiate your business? — Arnab Chakraborty, Senior Managing Director, North America Lead, Applied Intelligence", "attrs": null, "canon": { "kind": { "name": "Quote", "slug": "quote", "status": "active", "canonId": "019de52c-f8fb-751e-8bc6-d58e2d59562a", "version": 1, "description": "Pull quote or testimonial." }, "tool": { "name": "Authority citation", "slug": "authority-citation", "status": "active", "bestFor": null, "canonId": "019dd9e1-49ae-7557-89ad-3fca70469b45", "version": 1, "bodyDocId": null, "description": "Quoting an authority figure, study, or precedent to lend weight.", "familyLabel": null }, "subkind": null, "framework": null }, "subkind": null, "groupRole": null, "confidence": null, "extraction": { "at": "2026-04-23 22:41:13+00", "model": "claude-code-default", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "019dd951-9f64-72ba-b3fc-b53370f4ee02", "parentComponentId": null }, { "bbox": { "h": 0.038, "w": 0.691, "x": 0.058, "y": 0.143 }, "kind": "title", "text": "The art of AI maturity – North America perspective", "attrs": null, "canon": { "kind": { "name": "Title", "slug": "title", "status": "active", "canonId": "019de52c-f7dd-76d9-b848-b1f12bd85cf4", "version": 1, "description": "Slide title or headline." }, "tool": null, "subkind": { "name": "Headline", "slug": "headline", "status": "active", "canonId": "019de52c-fae1-7463-9a7c-d60668eced0d", "version": 1, "description": null }, "framework": null }, "subkind": "headline", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:49:07.392+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "ad5a0940-3faf-4efd-ba47-0c9cc190ccb7", "parentComponentId": null }, { "bbox": { "h": 0.025, "w": 0.085, "x": 0.058, "y": 0.208 }, "kind": "title", "text": "Foreword", "attrs": null, "canon": { "kind": { "name": "Title", "slug": "title", "status": "active", "canonId": "019de52c-f7dd-76d9-b848-b1f12bd85cf4", "version": 1, "description": "Slide title or headline." }, "tool": null, "subkind": { "name": "Subtitle", "slug": "subtitle", "status": "active", "canonId": "019de52c-fb09-739d-900c-815b0d9ac526", "version": 1, "description": null }, "framework": null }, "subkind": "subtitle", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:49:07.392+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "857161fd-6c84-4ead-b7f0-5da701e91bf7", "parentComponentId": null } ], "metrics": [ { "metricRaw": "North America share of global AI market", "numberRaw": "43%", "numberKind": "percent", "actionTitle": null, "calloutText": "The pace of AI transformation is expected to be 16 months faster than digital transformation.", "numberScale": null, "numberValue": 43, "metricFamily": "share_penetration", "numberCurrency": null } ], "tools": [ { "tool": { "name": "Anchoring Bias", "slug": "anchoring-bias", "status": "active", "bestFor": null, "canonId": "019dd956-9254-73de-8f1b-c7250f8f4c9c", "version": 1, "bodyDocId": null, "description": "First piece of information becomes reference point for all subsequent judgments", "familyLabel": null, "categoryName": "Block", "categorySlug": "block" }, "agent": "Architect", "layer": "block", "agents": [ "Architect", "Storyteller" ], "matchId": "019dd95a-0f08-73d3-987c-4ad436a3aaaa", "evidence": "Sets '16 months faster' as the framing anchor for the deck.", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 65, "extraction": { "at": "2026-04-29 13:07:31.336924+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 3, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "Pyramid Principle", "slug": "pyramid-principle", "status": "active", "bestFor": "When the document has a single governing decision or recommendation the reader is asked to accept, and the case can be decomposed into a small number of clean groups. Strategy decks, board memos, investment committee papers.", "canonId": "019dd956-7cbd-7219-a477-c871e2bc1aff", "version": 1, "bodyDocId": "88b6ac56-b880-46f9-8621-ef3491ab6235", "description": "Lead with the answer; group three to five MECE supports beneath it; recurse one level down. Top-down hierarchical structure for any document with a single recommendation.", "familyLabel": null, "categoryName": "Block", "categorySlug": "block" }, "agent": "Architect", "layer": "block", "agents": [ "Architect" ], "matchId": "019dd95a-0f08-73d3-987c-4d3407f92a6b", "evidence": "Top-line answer (NA perspective on AI maturity) precedes supporting data.", "pageRefs": null, "priority": "Core", "whenToUse": "When the document has a single governing decision or recommendation the reader is asked to accept, and the case can be decomposed into a small number of clean groups. Strategy decks, board memos, investment committee papers.", "confidence": 60, "extraction": { "at": "2026-04-29 13:07:31.336924+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 3, "whyItWorks": "Solves the two failure modes of expert communication at once: (1) the long climb where readers wait pages for the answer, and (2) logical mush from non-MECE groupings. Progressive disclosure lets a reader stop at any depth and get the right information.", "antipattern": "Chronological structure (\"what we did, what we found, what we conclude\") instead of logical hierarchy. Top-of-pyramid that is a topic (\"strategic options\") instead of an answer (\"pursue Option B because...\"). Non-MECE supports that overlap or fail to cover the universe.", "cardinality": null, "narrativePurpose": "Transfer conviction with minimum reader effort by mirroring how decision-makers consume information: answer first, scaffolding behind." }, { "tool": { "name": "Information Gap Theory", "slug": "information-gap-theory", "status": "active", "bestFor": null, "canonId": "019dd956-a856-765e-88bc-f703bdfec762", "version": 1, "bodyDocId": null, "description": "Curiosity arises from gap between what we know and want to know", "familyLabel": null, "categoryName": "Loop", "categorySlug": "loop" }, "agent": "Storyteller", "layer": "loop", "agents": [ "Storyteller" ], "matchId": "019dd95a-0f08-73d3-987c-446a4fc7d98e", "evidence": "Opens loop by raising the AI-maturity question without answering.", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 70, "extraction": { "at": "2026-04-29 13:07:31.336924+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 3, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "Action Titles", "slug": "action-titles", "status": "active", "bestFor": "Any decision-grade deliverable — strategy recommendation, board update, investment memo, M&A review, post-mortem — where the reader is being asked to agree, decide, or act and will skim the title bar at speed.", "canonId": "019dd956-ac70-700b-a608-ba58e78f5dcc", "version": 1, "bodyDocId": "816dad3c-9983-41c1-a86e-978ebd582841", "description": "The McKinsey-bred discipline of writing every slide title as a complete declarative sentence with a verb and an insight, not a topic label. Each title is a sub-claim that ladders up to the deck's governing thought; read in sequence, the titles reconstruct the executive summary.", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Architect", "layer": "slide", "agents": [ "Architect" ], "matchId": "019dd95a-0f08-73d3-987c-3cc7233b8c60", "evidence": "Subhead frames the so-what about NA pace of AI.", "pageRefs": null, "priority": "Core", "whenToUse": "Any decision-grade deliverable — strategy recommendation, board update, investment memo, M&A review, post-mortem — where the reader is being asked to agree, decide, or act and will skim the title bar at speed.", "confidence": 70, "extraction": { "at": "2026-04-29 13:07:31.336924+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 3, "whyItWorks": "Solves two failure modes at once. (1) The buried claim: action titles place the conclusion on the page before any analysis is read, so a busy reader doesn't reverse-engineer it from the chart. (2) The spineless deck: because each title is a claim, slides have to ladder up to the governing thought; logical gaps become visible as topic-shaped titles in a sequence that no longer reads as a story.", "antipattern": "Topic labels disguised as titles — Volume by quarter, Key findings, Pricing strategy, Margins have been impacted. No verb, or a passive verb with no agent, or a fact (Revenue grew 12%) without the so-what. Also: titles that overreach the chart's evidence, multi-claim X-grew-but-Y-fell welded titles, and mechanical repetition of the same X-drove-Y template across the deck.", "cardinality": null, "narrativePurpose": "Forces the deck to carry its argument in the title bar so a senior reader can extract the recommendation without opening a single slide; converts a binder of topics into a navigable pyramid where every slide is a node defending the apex." }, { "tool": { "name": "Concrete Language", "slug": "concrete-language", "status": "active", "bestFor": null, "canonId": "019dd956-bcd4-7398-9723-6aa72346170b", "version": 1, "bodyDocId": null, "description": "Using specific sensory details instead of abstract terms", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Storyteller", "layer": "slide", "agents": [ "Storyteller" ], "matchId": "019dd95a-0f08-73d3-987c-411b26009db8", "evidence": "Callout: '16 months faster than digital transformation'.", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 85, "extraction": { "at": "2026-04-29 13:07:31.336924+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 3, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "Executive summary", "slug": "executive-summary", "status": "active", "bestFor": null, "canonId": "019dd9e1-4b63-72d5-9734-da757d91ca61", "version": 1, "bodyDocId": null, "description": "A condensed view of the entire argument on a single slide / block.", "familyLabel": null, "categoryName": null, "categorySlug": null }, "agent": null, "layer": "slide", "agents": null, "matchId": "b85a6189-b3a0-4f38-b847-6838ff852d1c", "evidence": "This slide is an executive summary with a title, paragraphs, and metrics.", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 0.9, "extraction": { "at": "2026-07-16 21:02:22.465468+00", "model": "or:meta-llama/llama-4-scout", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 3, "whyItWorks": null, "antipattern": null, "cardinality": "common", "narrativePurpose": null } ], "frameworks": [], "arcBeats": [ { "to": 8, "arc": { "name": "The Consultant's Gambit", "slug": "consultants-gambit", "status": "active", "bestFor": "Business cases, project proposals, strategic recommendations", "canonId": "019dd956-5e0a-73c8-b305-81c38c959e9c", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "Situation & Context -> Problem & Complication -> Solution & Approach -> Evidence & Proof -> Impact & Next Steps", "description": null, "familyLabel": null }, "from": 3, "name": "Situation & Context", "beatId": "019dd95a-0682-776c-8e32-88fc09ca9afe", "matchId": "019dd95a-0542-7728-a78e-666792080e8f", "beatType": { "name": "Situation & Context", "slug": "consultants-gambit-situation-context", "status": "active", "canonId": "019dd9b8-05ae-741b-992d-65ee83c639b3", "version": 1, "description": null }, "evidence": "AI is essential, transformation 16 months faster than digital.", "position": 1, "isPrimaryArc": true, "parentBeatType": { "name": "Setup", "slug": "setup", "status": "active", "canonId": "019dd9b8-020e-7505-af9b-d9b9a4679bcc", "version": 1, "description": "Where the deck grounds the reader before doing anything else. Almost every arc opens here." }, "alignedBlockIds": null, "matchConfidence": 88 }, { "to": 13, "arc": { "name": "The Triple Take", "slug": "triple-take", "status": "active", "bestFor": "Data-driven presentations, research findings", "canonId": "019dd956-6221-73ad-bc12-378f8eb1f018", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "The Facts (What) -> The Implications (So What) -> The Action (Now What)", "description": null, "familyLabel": null }, "from": 3, "name": "The Facts (What)", "beatId": "019dd95a-0682-776c-8e32-9ee324fcf070", "matchId": "019dd95a-0542-7728-a78e-68cfbfb51150", "beatType": { "name": "The Facts (What)", "slug": "triple-take-the-facts-what", "status": "active", "canonId": "019dd9b8-092b-754c-8eaa-ede3ffdcb060", "version": 1, "description": null }, "evidence": "AI adoption stats and segmentation of the 2,000-firm sample.", "position": 1, "isPrimaryArc": false, "parentBeatType": { "name": "Setup", "slug": "setup", "status": "active", "canonId": "019dd9b8-020e-7505-af9b-d9b9a4679bcc", "version": 1, "description": "Where the deck grounds the reader before doing anything else. Almost every arc opens here." }, "alignedBlockIds": null, "matchConfidence": 60 } ], "loops": [ { "to": 5, "from": 3, "loop": { "name": "03_aha_moment", "slug": "03-aha-moment", "status": "active", "bestFor": "Data-heavy sections, research findings, analytical arguments", "canonId": "019dd956-66f4-7668-ab25-cec9c996c0bc", "version": 1, "bodyDocId": "019df22a-2420-77be-bc41-ded96d08cb21", "structure": "The Problem/Question -> What the Data Shows -> The Insight", "description": "Establish a tension, present data, then deliver the insight that changes everything", "familyLabel": null }, "matchId": "019dd95a-07fe-70ce-8d3a-516cbcb3d4fa", "evidence": "Problem framing (AI ubiquity) -> data (7% Achievers) -> insight (5 differentiators).", "position": 1, "objective": "Open with the question and the 7%/20% reveal", "confidence": 75, "extraction": { "at": "2026-04-29 13:07:29.547081+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null } } ], "locked": true }, { "page": 4, "type": "setup", "function": "summarize", "rawType": "executive_summary", "block": null, "metadata": { "slideType": "executive_summary", "slideTypeCanon": { "name": "Executive summary", "slug": "executive_summary", "status": "active", "canonId": "019de52d-06be-73ff-81b3-f99fe7f0025e", "version": 1, "description": null }, "function": "summarize", "functionCanon": { "name": "Summarize", "slug": "summarize", "status": "active", "canonId": "019de52d-1541-704f-b86f-bf7b75056373", "version": 1, "description": null }, "density": "overcrowded", "densityScore": 88, "componentCount": 12, "textChars": 997, "nDataPoints": 7, "notes": null, "elementsJson": [ "headline_text", "subtitle_text", "paragraph", "big_number" ], "confidence": 1, "extraction": { "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "at": "2026-05-02 19:49:07.189+00", "seconds": 4.226, "promptVersion": "v2-canon-conditioned" } }, "links": { "slide": "/slides/019dd923-5ca1-7489-b633-7fa84bbf490b/4", "deck": "/decks/019dd923-5ca1-7489-b633-7fa84bbf490b", "deckAnchor": "/decks/019dd923-5ca1-7489-b633-7fa84bbf490b#slide-4", "deckJson": "/decks/019dd923-5ca1-7489-b633-7fa84bbf490b.json" }, "components": [ { "bbox": null, "kind": "callout", "text": "7% of firms have advanced their AI maturity enough to achieve superior performance and growth.", "attrs": null, "canon": { "kind": { "name": "Callout", "slug": "callout", "status": "active", "canonId": "019de52c-f8d3-761a-8953-7d37080de5e2", "version": 1, "description": "Highlighted callout box." }, "tool": { "name": "Visual emphasis", "slug": "visual-emphasis", "status": "active", "bestFor": null, "canonId": "019dd9e1-474b-736b-a8eb-a794dd88241c", "version": 1, "bodyDocId": null, "description": "Drawing the eye to one element above the rest of the slide.", "familyLabel": null }, "subkind": null, "framework": null }, "subkind": null, "groupRole": null, "confidence": null, "extraction": { "at": "2026-04-23 22:41:17+00", "model": "claude-code-default", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "019dd951-9f64-72ba-b3fc-d4e91ba6351d", "parentComponentId": null }, { "bbox": { "h": 0.08, "w": 0.07, "x": 0.514, "y": 0.652 }, "kind": "metric", "text": "75%", "attrs": null, "canon": { "kind": { "name": "Metric", "slug": "metric", "status": "active", "canonId": "019de52c-f923-73bf-8081-d0b1a8c5264d", "version": 1, "description": "Big-number or KPI value." }, "tool": null, "subkind": { "name": "Big number", "slug": "big-number", "status": "active", "canonId": "019de52c-fc70-70c8-b965-0584548a9204", "version": 1, "description": null }, "framework": null }, "subkind": "big-number", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:49:07.189+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "5bd17047-4fa0-4f91-82be-e0aca8755dd5", "parentComponentId": null }, { "bbox": { "h": 0.08, "w": 0.07, "x": 0.742, "y": 0.296 }, "kind": "metric", "text": "7%", "attrs": null, "canon": { "kind": { "name": "Metric", "slug": "metric", "status": "active", "canonId": "019de52c-f923-73bf-8081-d0b1a8c5264d", "version": 1, "description": "Big-number or KPI value." }, "tool": null, "subkind": { "name": "Big number", "slug": "big-number", "status": "active", "canonId": "019de52c-fc70-70c8-b965-0584548a9204", "version": 1, "description": null }, "framework": null }, "subkind": "big-number", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:49:07.189+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "7a88a52d-a271-41e7-91f2-27445c1b1579", "parentComponentId": null }, { "bbox": null, "kind": "metric", "text": "Share of firms that have advanced their AI maturity enough to achieve superior performance and growth: 7%", "attrs": null, "canon": { "kind": { "name": "Metric", "slug": "metric", "status": "active", "canonId": "019de52c-f923-73bf-8081-d0b1a8c5264d", "version": 1, "description": "Big-number or KPI value." }, "tool": { "name": "Quantification", "slug": "quantification", "status": "active", "bestFor": null, "canonId": "019dd9e1-47ab-72ce-a079-aab1f5299e88", "version": 1, "bodyDocId": null, "description": "Translating a claim into numbers, charts, or tables.", "familyLabel": null }, "subkind": null, "framework": null }, "subkind": "primary", "groupRole": null, "confidence": null, "extraction": { "at": "2026-04-23 22:41:17+00", "model": "claude-code-default", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "019dd951-9f64-72ba-b3fc-df3cc599032e", "parentComponentId": null }, { "bbox": { "h": 0.455, "w": 0.215, "x": 0.286, "y": 0.296 }, "kind": "paragraph", "text": "Despite these ever-expanding use cases... [text continues] ...the majority) are still mostly testing the waters.", "attrs": null, "canon": { "kind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "5f2affc0-941d-4d07-959d-4bfc1930cea4", "version": 1, "description": "Single prose block in the body of a slide." }, "tool": null, "subkind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "019de52c-fb80-75af-aa5c-a7a4bfac2433", "version": 1, "description": null }, "framework": null }, "subkind": "paragraph", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:49:07.189+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "5e291261-f630-4489-8e18-a2cad1c51b6e", "parentComponentId": null }, { "bbox": { "h": 0.05, "w": 0.15, "x": 0.514, "y": 0.755 }, "kind": "paragraph", "text": "of firms are still testing the AI waters.", "attrs": null, "canon": { "kind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "5f2affc0-941d-4d07-959d-4bfc1930cea4", "version": 1, "description": "Single prose block in the body of a slide." }, "tool": null, "subkind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "019de52c-fb80-75af-aa5c-a7a4bfac2433", "version": 1, "description": null }, "framework": null }, "subkind": "paragraph", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:49:07.189+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "76b17986-120d-4fa6-969a-3c7dd88ac5fb", "parentComponentId": null }, { "bbox": { "h": 0.08, "w": 0.2, "x": 0.742, "y": 0.399 }, "kind": "paragraph", "text": "of firms have advanced their AI maturity enough to achieve superior performance and growth.", "attrs": null, "canon": { "kind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "5f2affc0-941d-4d07-959d-4bfc1930cea4", "version": 1, "description": "Single prose block in the body of a slide." }, "tool": null, "subkind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "019de52c-fb80-75af-aa5c-a7a4bfac2433", "version": 1, "description": null }, "framework": null }, "subkind": "paragraph", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:49:07.189+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "d0b8eb4c-acc6-4c95-a45f-b8839f2241e7", "parentComponentId": null }, { "bbox": { "h": 0.455, "w": 0.215, "x": 0.058, "y": 0.296 }, "kind": "paragraph", "text": "Computer scientist John McCarthy coined the term “artificial intelligence” in 1955... [text continues] ...empower employees and so much more.", "attrs": null, "canon": { "kind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "5f2affc0-941d-4d07-959d-4bfc1930cea4", "version": 1, "description": "Single prose block in the body of a slide." }, "tool": null, "subkind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "019de52c-fb80-75af-aa5c-a7a4bfac2433", "version": 1, "description": null }, "framework": null }, "subkind": "paragraph", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:49:07.189+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "d530e567-68c8-494c-80af-7b3e9e096a18", "parentComponentId": null }, { "bbox": { "h": 0.455, "w": 0.215, "x": 0.514, "y": 0.296 }, "kind": "paragraph", "text": "This journey to AI maturity has been in high gear for years because the business case is clear... [text continues] ...according to our analysis.", "attrs": null, "canon": { "kind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "5f2affc0-941d-4d07-959d-4bfc1930cea4", "version": 1, "description": "Single prose block in the body of a slide." }, "tool": null, "subkind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "019de52c-fb80-75af-aa5c-a7a4bfac2433", "version": 1, "description": null }, "framework": null }, "subkind": "paragraph", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:49:07.189+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "f96b8bd9-dc50-49f7-97b9-13e2463307b9", "parentComponentId": null }, { "bbox": null, "kind": "quote", "text": "every aspect of learning can in principle be so precisely described that a machine can be made to simulate it. — John McCarthy (1955)", "attrs": null, "canon": { "kind": { "name": "Quote", "slug": "quote", "status": "active", "canonId": "019de52c-f8fb-751e-8bc6-d58e2d59562a", "version": 1, "description": "Pull quote or testimonial." }, "tool": { "name": "Authority citation", "slug": "authority-citation", "status": "active", "bestFor": null, "canonId": "019dd9e1-49ae-7557-89ad-3fca70469b45", "version": 1, "bodyDocId": null, "description": "Quoting an authority figure, study, or precedent to lend weight.", "familyLabel": null }, "subkind": null, "framework": null }, "subkind": null, "groupRole": null, "confidence": null, "extraction": { "at": "2026-04-23 22:41:17+00", "model": "claude-code-default", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "019dd951-9f64-72ba-b3fc-d84e879f8336", "parentComponentId": null }, { "bbox": { "h": 0.071, "w": 0.435, "x": 0.058, "y": 0.211 }, "kind": "title", "text": "In fewer than 70 years, artificial intelligence (AI) has evolved from a scientific concept to a societal constant.", "attrs": null, "canon": { "kind": { "name": "Title", "slug": "title", "status": "active", "canonId": "019de52c-f7dd-76d9-b848-b1f12bd85cf4", "version": 1, "description": "Slide title or headline." }, "tool": null, "subkind": { "name": "Action title", "slug": "action-title", "status": "active", "canonId": "019de52c-fb31-734c-a0f5-a3935b73135d", "version": 1, "description": null }, "framework": null }, "subkind": "action-title", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:49:07.189+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "eb4ac3d1-99d5-4ba2-aa6d-e51a4ed696ed", "parentComponentId": null }, { "bbox": { "h": 0.045, "w": 0.235, "x": 0.058, "y": 0.144 }, "kind": "title", "text": "Executive summary", "attrs": null, "canon": { "kind": { "name": "Title", "slug": "title", "status": "active", "canonId": "019de52c-f7dd-76d9-b848-b1f12bd85cf4", "version": 1, "description": "Slide title or headline." }, "tool": null, "subkind": { "name": "Headline", "slug": "headline", "status": "active", "canonId": "019de52c-fae1-7463-9a7c-d60668eced0d", "version": 1, "description": null }, "framework": null }, "subkind": "headline", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:49:07.189+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "851723f9-c0ee-4e48-adf9-6f12289b2ceb", "parentComponentId": null } ], "metrics": [ { "metricRaw": "Share of firms that have advanced their AI maturity enough to achieve superior performance and growth", "numberRaw": "7%", "numberKind": "percent", "actionTitle": "In fewer than 70 years, artificial intelligence (AI) has evolved from a scientific concept to a societal constant.", "calloutText": "7% of firms have advanced their AI maturity enough to achieve superior performance and growth.", "numberScale": null, "numberValue": 7, "metricFamily": "growth_rate", "numberCurrency": null } ], "tools": [ { "tool": { "name": "Concrete Language", "slug": "concrete-language", "status": "active", "bestFor": null, "canonId": "019dd956-bcd4-7398-9723-6aa72346170b", "version": 1, "bodyDocId": null, "description": "Using specific sensory details instead of abstract terms", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Storyteller", "layer": "slide", "agents": [ "Storyteller" ], "matchId": "019dd95a-0f08-73d3-987c-55e495c7c15b", "evidence": "Callout quantifies '7% of firms have advanced their AI maturity'.", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 85, "extraction": { "at": "2026-04-29 13:07:31.336924+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 4, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "Core Message Extraction", "slug": "core-message-extraction", "status": "active", "bestFor": "Any slide that carries an argument or finding. The diagnostic: if the slide has a chart on it, it needs a core message. Run extraction whenever the current title is a topic (Q3 performance, Customer satisfaction) rather than a claim, or when a reader could reasonably draw more than one conclusion from the visible evidence.", "canonId": "019dd956-bc71-707d-8867-1b2e810175cf", "version": 1, "bodyDocId": "f85613cb-4b77-462f-bfe6-3b862516e1a6", "description": "The discipline of distilling raw analysis, data, or content into a single declarative sentence — the slide's core message — that the audience would walk away with if they remembered nothing else. Process, not artefact: extraction questions run on the raw content until one sentence falls out.", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Architect", "layer": "slide", "agents": [ "Architect" ], "matchId": "019dd95a-0f08-73d3-987c-5a2c44e477d2", "evidence": "Distils whole report into the 7% Achievers thesis.", "pageRefs": null, "priority": null, "whenToUse": "Any slide that carries an argument or finding. The diagnostic: if the slide has a chart on it, it needs a core message. Run extraction whenever the current title is a topic (Q3 performance, Customer satisfaction) rather than a claim, or when a reader could reasonably draw more than one conclusion from the visible evidence.", "confidence": 70, "extraction": { "at": "2026-04-29 13:07:31.336924+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 4, "whyItWorks": "Solves the two failure modes of slide writing simultaneously: the topic title (which outsources interpretation to the audience and produces three different conclusions in three different heads) and the multi-thesis stapler (which exceeds working memory and gets remembered as fragments). Aligns with how readers actually consume decks — Heath & Heath's Find the Core, the journalist's nut graf, and Minto's governing thought all converge on the same cognitive economics.", "antipattern": "Topic titles disguised as core messages (Customer satisfaction, no verb, no stake); multi-thesis sentences stapled with and; hedged sentences (may show signs of possible softening); chart-caption titles (Revenue fell 4%) that restate what the chart already shows instead of naming the so-what; meta-commentary (this slide explores...) that describes the slide rather than concluding it.", "cardinality": null, "narrativePurpose": "Forces the slide author to do the interpretive work before the slide ships, so the audience does not have to do it during the meeting. Wins the WYSIATI battle on purpose — the loudest fragment on the page becomes the author's chosen sentence rather than whichever chart label happens to be largest." }, { "tool": { "name": "Executive summary", "slug": "executive-summary", "status": "active", "bestFor": null, "canonId": "019dd9e1-4b63-72d5-9734-da757d91ca61", "version": 1, "bodyDocId": null, "description": "A condensed view of the entire argument on a single slide / block.", "familyLabel": null, "categoryName": null, "categorySlug": null }, "agent": null, "layer": "slide", "agents": null, "matchId": "6f8d1bc3-95b4-4403-97cb-eb94af3418c1", "evidence": "This slide is an executive summary with a title, paragraphs, and metrics.", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 0.9, "extraction": { "at": "2026-07-16 21:02:22.55519+00", "model": "or:meta-llama/llama-4-scout", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 4, "whyItWorks": null, "antipattern": null, "cardinality": "common", "narrativePurpose": null }, { "tool": { "name": "Opening Hooks", "slug": "opening-hooks", "status": "active", "bestFor": null, "canonId": "019dd956-aeb0-77d5-bfbd-9cd9a6be8186", "version": 1, "bodyDocId": null, "description": "Techniques to capture attention: Startling statistic, provocative question, short story, analogy, contrast", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Storyteller", "layer": "slide", "agents": [ "Storyteller" ], "matchId": "019dd95a-0f08-73d3-987c-51a8a2b475ec", "evidence": "'In fewer than 70 years...' opens with a startling time-scale frame.", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 80, "extraction": { "at": "2026-04-29 13:07:31.336924+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 4, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null } ], "frameworks": [], "arcBeats": [ { "to": 8, "arc": { "name": "The Consultant's Gambit", "slug": "consultants-gambit", "status": "active", "bestFor": "Business cases, project proposals, strategic recommendations", "canonId": "019dd956-5e0a-73c8-b305-81c38c959e9c", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "Situation & Context -> Problem & Complication -> Solution & Approach -> Evidence & Proof -> Impact & Next Steps", "description": null, "familyLabel": null }, "from": 3, "name": "Situation & Context", "beatId": "019dd95a-0682-776c-8e32-88fc09ca9afe", "matchId": "019dd95a-0542-7728-a78e-666792080e8f", "beatType": { "name": "Situation & Context", "slug": "consultants-gambit-situation-context", "status": "active", "canonId": "019dd9b8-05ae-741b-992d-65ee83c639b3", "version": 1, "description": null }, "evidence": "AI is essential, transformation 16 months faster than digital.", "position": 1, "isPrimaryArc": true, "parentBeatType": { "name": "Setup", "slug": "setup", "status": "active", "canonId": "019dd9b8-020e-7505-af9b-d9b9a4679bcc", "version": 1, "description": "Where the deck grounds the reader before doing anything else. Almost every arc opens here." }, "alignedBlockIds": null, "matchConfidence": 88 }, { "to": 13, "arc": { "name": "The Triple Take", "slug": "triple-take", "status": "active", "bestFor": "Data-driven presentations, research findings", "canonId": "019dd956-6221-73ad-bc12-378f8eb1f018", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "The Facts (What) -> The Implications (So What) -> The Action (Now What)", "description": null, "familyLabel": null }, "from": 3, "name": "The Facts (What)", "beatId": "019dd95a-0682-776c-8e32-9ee324fcf070", "matchId": "019dd95a-0542-7728-a78e-68cfbfb51150", "beatType": { "name": "The Facts (What)", "slug": "triple-take-the-facts-what", "status": "active", "canonId": "019dd9b8-092b-754c-8eaa-ede3ffdcb060", "version": 1, "description": null }, "evidence": "AI adoption stats and segmentation of the 2,000-firm sample.", "position": 1, "isPrimaryArc": false, "parentBeatType": { "name": "Setup", "slug": "setup", "status": "active", "canonId": "019dd9b8-020e-7505-af9b-d9b9a4679bcc", "version": 1, "description": "Where the deck grounds the reader before doing anything else. Almost every arc opens here." }, "alignedBlockIds": null, "matchConfidence": 60 } ], "loops": [ { "to": 5, "from": 3, "loop": { "name": "03_aha_moment", "slug": "03-aha-moment", "status": "active", "bestFor": "Data-heavy sections, research findings, analytical arguments", "canonId": "019dd956-66f4-7668-ab25-cec9c996c0bc", "version": 1, "bodyDocId": "019df22a-2420-77be-bc41-ded96d08cb21", "structure": "The Problem/Question -> What the Data Shows -> The Insight", "description": "Establish a tension, present data, then deliver the insight that changes everything", "familyLabel": null }, "matchId": "019dd95a-07fe-70ce-8d3a-516cbcb3d4fa", "evidence": "Problem framing (AI ubiquity) -> data (7% Achievers) -> insight (5 differentiators).", "position": 1, "objective": "Open with the question and the 7%/20% reveal", "confidence": 75, "extraction": { "at": "2026-04-29 13:07:29.547081+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null } } ], "locked": true }, { "page": 5, "type": "resolution", "function": "summarize", "rawType": "key_takeaways", "block": null, "metadata": { "slideType": "key_takeaways", "slideTypeCanon": { "name": "Key takeaways", "slug": "key_takeaways", "status": "active", "canonId": "019de52d-06e7-7674-a891-9f7de3b11b6d", "version": 1, "description": null }, "function": "summarize", "functionCanon": { "name": "Summarize", "slug": "summarize", "status": "active", "canonId": "019de52d-1541-704f-b86f-bf7b75056373", "version": 1, "description": null }, "density": "overcrowded", "densityScore": 78, "componentCount": 8, "textChars": 1177, "nDataPoints": 2, "notes": null, "elementsJson": [ "headline_text", "numbered_list", "paragraph", "photo" ], "confidence": 1, "extraction": { "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "at": "2026-05-02 19:49:05.723+00", "seconds": 2.749, "promptVersion": "v2-canon-conditioned" } }, "links": { "slide": "/slides/019dd923-5ca1-7489-b633-7fa84bbf490b/5", "deck": "/decks/019dd923-5ca1-7489-b633-7fa84bbf490b", "deckAnchor": "/decks/019dd923-5ca1-7489-b633-7fa84bbf490b#slide-5", "deckJson": "/decks/019dd923-5ca1-7489-b633-7fa84bbf490b.json" }, "components": [ { "bbox": null, "kind": "callout", "text": "Our own machine learning analysis models suggest that the share of AI Achievers in North America will increase rapidly and significantly, nearly tripling from the current 7% to 20% by 2024.", "attrs": null, "canon": { "kind": { "name": "Callout", "slug": "callout", "status": "active", "canonId": "019de52c-f8d3-761a-8953-7d37080de5e2", "version": 1, "description": "Highlighted callout box." }, "tool": { "name": "Visual emphasis", "slug": "visual-emphasis", "status": "active", "bestFor": null, "canonId": "019dd9e1-474b-736b-a8eb-a794dd88241c", "version": 1, "bodyDocId": null, "description": "Drawing the eye to one element above the rest of the slide.", "familyLabel": null }, "subkind": null, "framework": null }, "subkind": null, "groupRole": null, "confidence": null, "extraction": { "at": "2026-04-23 22:41:28+00", "model": "claude-code-default", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "019dd951-9f64-72ba-b3fc-fc07d9b6cac6", "parentComponentId": null }, { "bbox": { "h": 0.86, "w": 0.45, "x": 0.03, "y": 0.06 }, "kind": "image", "text": null, "attrs": null, "canon": { "kind": { "name": "Image", "slug": "image", "status": "active", "canonId": "019de52c-f978-701f-a720-51d029d769e7", "version": 1, "description": "Photo, illustration, screenshot or icon." }, "tool": null, "subkind": { "name": "Photo", "slug": "photo", "status": "active", "canonId": "019de52c-fd37-757f-b4a8-ca26d4888875", "version": 1, "description": null }, "framework": null }, "subkind": "photo", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:49:05.723+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "36ed1b6e-f727-4b95-b8a3-cc186e0f46fc", "parentComponentId": null }, { "bbox": { "h": 0.25, "w": 0.43, "x": 0.515, "y": 0.29 }, "kind": "list", "text": "1. Their top leaders champion AI as a strategic priority for the entire organization.\n2. They invest heavily in talent to get more from their AI investments.\n3. They industrialize AI tools and teams to create a strong AI core.\n4. They design AI responsibly, from the start.\n5. They prioritize long- and short-term AI investments.", "attrs": null, "canon": { "kind": { "name": "List", "slug": "list", "status": "active", "canonId": "019de52c-f94b-779b-a53b-fd4904a5f4d2", "version": 1, "description": "Bullet or numbered list." }, "tool": null, "subkind": { "name": "Numbered list", "slug": "numbered", "status": "active", "canonId": "019de52c-fcc0-7718-a284-a4250c805df2", "version": 1, "description": null }, "framework": null }, "subkind": "numbered", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:49:05.723+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "a3ea5ba5-6e78-4aac-a212-c78437e7c490", "parentComponentId": null }, { "bbox": null, "kind": "metric", "text": "AI Achievers share, North America: 7% to 20% by 2024", "attrs": null, "canon": { "kind": { "name": "Metric", "slug": "metric", "status": "active", "canonId": "019de52c-f923-73bf-8081-d0b1a8c5264d", "version": 1, "description": "Big-number or KPI value." }, "tool": { "name": "Quantification", "slug": "quantification", "status": "active", "bestFor": null, "canonId": "019dd9e1-47ab-72ce-a079-aab1f5299e88", "version": 1, "bodyDocId": null, "description": "Translating a claim into numbers, charts, or tables.", "familyLabel": null }, "subkind": null, "framework": null }, "subkind": "primary", "groupRole": null, "confidence": null, "extraction": { "at": "2026-04-23 22:41:28+00", "model": "claude-code-default", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "019dd951-9f64-72ba-b3fd-018d6b4c8425", "parentComponentId": null }, { "bbox": { "h": 0.04, "w": 0.43, "x": 0.515, "y": 0.76 }, "kind": "paragraph", "text": "In short, advancing AI maturity is no longer a choice. It’s an opportunity facing every industry, every organization and every leader.", "attrs": null, "canon": { "kind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "5f2affc0-941d-4d07-959d-4bfc1930cea4", "version": 1, "description": "Single prose block in the body of a slide." }, "tool": null, "subkind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "019de52c-fb80-75af-aa5c-a7a4bfac2433", "version": 1, "description": null }, "framework": null }, "subkind": "paragraph", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:49:05.723+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "51023701-cfe2-4275-988a-c1af995a3294", "parentComponentId": null }, { "bbox": { "h": 0.07, "w": 0.43, "x": 0.515, "y": 0.185 }, "kind": "paragraph", "text": "While there’s clearly science behind AI, our findings suggest there is an art to AI maturity. AI Achievers are not defined by the sophistication of any one capability, but by their ability to combine strengths across strategy, processes and people.", "attrs": null, "canon": { "kind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "5f2affc0-941d-4d07-959d-4bfc1930cea4", "version": 1, "description": "Single prose block in the body of a slide." }, "tool": null, "subkind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "019de52c-fb80-75af-aa5c-a7a4bfac2433", "version": 1, "description": null }, "framework": null }, "subkind": "paragraph", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:49:05.723+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "884884db-ea2b-4c9d-96ed-d66b50c7e148", "parentComponentId": null }, { "bbox": { "h": 0.07, "w": 0.43, "x": 0.515, "y": 0.66 }, "kind": "paragraph", "text": "Our own machine learning analysis models suggest that the share of AI Achievers in North America will increase rapidly and significantly, nearly tripling from the current 7% to 20% by 2024.", "attrs": null, "canon": { "kind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "5f2affc0-941d-4d07-959d-4bfc1930cea4", "version": 1, "description": "Single prose block in the body of a slide." }, "tool": null, "subkind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "019de52c-fb80-75af-aa5c-a7a4bfac2433", "version": 1, "description": null }, "framework": null }, "subkind": "paragraph", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:49:05.723+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "a2d09035-0eb5-4f7c-b3ed-14aca7fa8cc9", "parentComponentId": null }, { "bbox": { "h": 0.04, "w": 0.43, "x": 0.515, "y": 0.125 }, "kind": "title", "text": "What do AI Achievers do differently?", "attrs": null, "canon": { "kind": { "name": "Title", "slug": "title", "status": "active", "canonId": "019de52c-f7dd-76d9-b848-b1f12bd85cf4", "version": 1, "description": "Slide title or headline." }, "tool": null, "subkind": { "name": "Headline", "slug": "headline", "status": "active", "canonId": "019de52c-fae1-7463-9a7c-d60668eced0d", "version": 1, "description": null }, "framework": null }, "subkind": "headline", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:49:05.723+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "1228b56b-e660-4f37-a5c9-91987748af64", "parentComponentId": null } ], "metrics": [ { "metricRaw": "AI Achievers share, North America", "numberRaw": "7% to 20% by 2024", "numberKind": "percent", "actionTitle": null, "calloutText": "Our own machine learning analysis models suggest that the share of AI Achievers in North America will increase rapidly and significantly, nearly tripling from the current 7% to 20% by 2024.", "numberScale": null, "numberValue": 7, "metricFamily": "share_penetration", "numberCurrency": null } ], "tools": [ { "tool": { "name": "Curiosity Gap", "slug": "curiosity-gap", "status": "active", "bestFor": null, "canonId": "019dd956-9703-74ef-8b85-96dfd8525025", "version": 1, "bodyDocId": null, "description": "People seek missing information - create open questions that demand resolution", "familyLabel": null, "categoryName": "Block", "categorySlug": "block" }, "agent": "Storyteller", "layer": "block", "agents": [ "Storyteller" ], "matchId": "019dd95a-0f08-73d3-987c-6ba60a6140df", "evidence": "Question title plus enumerated answers create resolution-seeking tension.", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 75, "extraction": { "at": "2026-04-29 13:07:31.336924+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 5, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "Chunking", "slug": "chunking", "status": "active", "bestFor": null, "canonId": "019dd956-abab-72ce-b64c-2924cc83cf39", "version": 1, "bodyDocId": null, "description": "Information grouped into chunks is remembered better - structure content in digestible units", "familyLabel": null, "categoryName": "Loop", "categorySlug": "loop" }, "agent": "Architect", "layer": "loop", "agents": [ "Architect" ], "matchId": "019dd95a-0f08-73d3-987c-62e9b857db7f", "evidence": "Five numbered success factors presented as a memorable list.", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 80, "extraction": { "at": "2026-04-29 13:07:31.336924+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 5, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "Foreshadowing", "slug": "foreshadowing", "status": "active", "bestFor": null, "canonId": "019dd956-a406-7159-bb8c-aeef05df2563", "version": 1, "bodyDocId": null, "description": "Planting hints of what's to come for later payoff", "familyLabel": null, "categoryName": "Loop", "categorySlug": "loop" }, "agent": "Storyteller", "layer": "loop", "agents": [ "Storyteller" ], "matchId": "019dd95a-0f08-73d3-987c-673e1809a76b", "evidence": "Lists the five factors that Section 4 will unpack one by one.", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 80, "extraction": { "at": "2026-04-29 13:07:31.336924+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 5, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "Action Titles", "slug": "action-titles", "status": "active", "bestFor": "Any decision-grade deliverable — strategy recommendation, board update, investment memo, M&A review, post-mortem — where the reader is being asked to agree, decide, or act and will skim the title bar at speed.", "canonId": "019dd956-ac70-700b-a608-ba58e78f5dcc", "version": 1, "bodyDocId": "816dad3c-9983-41c1-a86e-978ebd582841", "description": "The McKinsey-bred discipline of writing every slide title as a complete declarative sentence with a verb and an insight, not a topic label. Each title is a sub-claim that ladders up to the deck's governing thought; read in sequence, the titles reconstruct the executive summary.", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Architect", "layer": "slide", "agents": [ "Architect" ], "matchId": "019dd95a-0f08-73d3-987c-5d6eed0e25d8", "evidence": "Provocative question title: 'What do AI Achievers do differently?'", "pageRefs": null, "priority": "Core", "whenToUse": "Any decision-grade deliverable — strategy recommendation, board update, investment memo, M&A review, post-mortem — where the reader is being asked to agree, decide, or act and will skim the title bar at speed.", "confidence": 80, "extraction": { "at": "2026-04-29 13:07:31.336924+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 5, "whyItWorks": "Solves two failure modes at once. (1) The buried claim: action titles place the conclusion on the page before any analysis is read, so a busy reader doesn't reverse-engineer it from the chart. (2) The spineless deck: because each title is a claim, slides have to ladder up to the governing thought; logical gaps become visible as topic-shaped titles in a sequence that no longer reads as a story.", "antipattern": "Topic labels disguised as titles — Volume by quarter, Key findings, Pricing strategy, Margins have been impacted. No verb, or a passive verb with no agent, or a fact (Revenue grew 12%) without the so-what. Also: titles that overreach the chart's evidence, multi-claim X-grew-but-Y-fell welded titles, and mechanical repetition of the same X-drove-Y template across the deck.", "cardinality": null, "narrativePurpose": "Forces the deck to carry its argument in the title bar so a senior reader can extract the recommendation without opening a single slide; converts a binder of topics into a navigable pyramid where every slide is a node defending the apex." } ], "frameworks": [], "arcBeats": [ { "to": 8, "arc": { "name": "The Consultant's Gambit", "slug": "consultants-gambit", "status": "active", "bestFor": "Business cases, project proposals, strategic recommendations", "canonId": "019dd956-5e0a-73c8-b305-81c38c959e9c", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "Situation & Context -> Problem & Complication -> Solution & Approach -> Evidence & Proof -> Impact & Next Steps", "description": null, "familyLabel": null }, "from": 3, "name": "Situation & Context", "beatId": "019dd95a-0682-776c-8e32-88fc09ca9afe", "matchId": "019dd95a-0542-7728-a78e-666792080e8f", "beatType": { "name": "Situation & Context", "slug": "consultants-gambit-situation-context", "status": "active", "canonId": "019dd9b8-05ae-741b-992d-65ee83c639b3", "version": 1, "description": null }, "evidence": "AI is essential, transformation 16 months faster than digital.", "position": 1, "isPrimaryArc": true, "parentBeatType": { "name": "Setup", "slug": "setup", "status": "active", "canonId": "019dd9b8-020e-7505-af9b-d9b9a4679bcc", "version": 1, "description": "Where the deck grounds the reader before doing anything else. Almost every arc opens here." }, "alignedBlockIds": null, "matchConfidence": 88 }, { "to": 13, "arc": { "name": "The Triple Take", "slug": "triple-take", "status": "active", "bestFor": "Data-driven presentations, research findings", "canonId": "019dd956-6221-73ad-bc12-378f8eb1f018", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "The Facts (What) -> The Implications (So What) -> The Action (Now What)", "description": null, "familyLabel": null }, "from": 3, "name": "The Facts (What)", "beatId": "019dd95a-0682-776c-8e32-9ee324fcf070", "matchId": "019dd95a-0542-7728-a78e-68cfbfb51150", "beatType": { "name": "The Facts (What)", "slug": "triple-take-the-facts-what", "status": "active", "canonId": "019dd9b8-092b-754c-8eaa-ede3ffdcb060", "version": 1, "description": null }, "evidence": "AI adoption stats and segmentation of the 2,000-firm sample.", "position": 1, "isPrimaryArc": false, "parentBeatType": { "name": "Setup", "slug": "setup", "status": "active", "canonId": "019dd9b8-020e-7505-af9b-d9b9a4679bcc", "version": 1, "description": "Where the deck grounds the reader before doing anything else. Almost every arc opens here." }, "alignedBlockIds": null, "matchConfidence": 60 } ], "loops": [ { "to": 5, "from": 3, "loop": { "name": "03_aha_moment", "slug": "03-aha-moment", "status": "active", "bestFor": "Data-heavy sections, research findings, analytical arguments", "canonId": "019dd956-66f4-7668-ab25-cec9c996c0bc", "version": 1, "bodyDocId": "019df22a-2420-77be-bc41-ded96d08cb21", "structure": "The Problem/Question -> What the Data Shows -> The Insight", "description": "Establish a tension, present data, then deliver the insight that changes everything", "familyLabel": null }, "matchId": "019dd95a-07fe-70ce-8d3a-516cbcb3d4fa", "evidence": "Problem framing (AI ubiquity) -> data (7% Achievers) -> insight (5 differentiators).", "position": 1, "objective": "Open with the question and the 7%/20% reveal", "confidence": 75, "extraction": { "at": "2026-04-29 13:07:29.547081+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null } } ], "locked": true }, { "page": 6, "type": "setup", "title": "The slide uses a metaphorical image of painting to represent the 'art' of AI maturity.", "function": "transition", "rawType": "section_divider", "block": null, "metadata": { "slideType": "section_divider", "slideTypeCanon": { "name": "Section divider", "slug": "section_divider", "status": "active", "canonId": "019de52d-066a-7402-9554-6ae504999041", "version": 1, "description": null }, "function": "transition", "functionCanon": { "name": "Transition", "slug": "transition", "status": "active", "canonId": "019de52d-1365-7149-92aa-66df859e75fd", "version": 1, "description": null }, "density": "sparse", "densityScore": 6, "componentCount": 3, "textChars": 49, "nDataPoints": 0, "notes": "The slide uses a metaphorical image of painting to represent the 'art' of AI maturity.", "elementsJson": [ "headline_text", "photo" ], "confidence": 1, "extraction": { "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "at": "2026-05-02 19:49:05.238+00", "seconds": 2.18, "promptVersion": "v2-canon-conditioned" } }, "links": { "slide": "/slides/019dd923-5ca1-7489-b633-7fa84bbf490b/6", "deck": "/decks/019dd923-5ca1-7489-b633-7fa84bbf490b", "deckAnchor": "/decks/019dd923-5ca1-7489-b633-7fa84bbf490b#slide-6", "deckJson": "/decks/019dd923-5ca1-7489-b633-7fa84bbf490b.json" }, "components": [ { "bbox": { "h": 1, "w": 1, "x": 0, "y": 0 }, "kind": "image", "text": null, "attrs": null, "canon": { "kind": { "name": "Image", "slug": "image", "status": "active", "canonId": "019de52c-f978-701f-a720-51d029d769e7", "version": 1, "description": "Photo, illustration, screenshot or icon." }, "tool": null, "subkind": { "name": "Illustration", "slug": "illustration", "status": "active", "canonId": "019de52c-fe76-7772-a5ac-c0b7294d7615", "version": 1, "description": null }, "framework": null }, "subkind": "illustration", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:49:05.238+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "3b15ea45-9a0a-44b3-9b6e-97c1fd46e9eb", "parentComponentId": null }, { "bbox": { "h": 0.08, "w": 0.62, "x": 0.19, "y": 0.48 }, "kind": "title", "text": "AI maturity: Why it matters", "attrs": null, "canon": { "kind": { "name": "Title", "slug": "title", "status": "active", "canonId": "019de52c-f7dd-76d9-b848-b1f12bd85cf4", "version": 1, "description": "Slide title or headline." }, "tool": null, "subkind": { "name": "Headline", "slug": "headline", "status": "active", "canonId": "019de52c-fae1-7463-9a7c-d60668eced0d", "version": 1, "description": null }, "framework": null }, "subkind": "headline", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:49:05.238+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "4ab9deb6-7c32-4b4a-a5cb-351a37968e59", "parentComponentId": null }, { "bbox": { "h": 0.03, "w": 0.18, "x": 0.06, "y": 0.1 }, "kind": "title", "text": "The art of AI maturity", "attrs": null, "canon": { "kind": { "name": "Title", "slug": "title", "status": "active", "canonId": "019de52c-f7dd-76d9-b848-b1f12bd85cf4", "version": 1, "description": "Slide title or headline." }, "tool": null, "subkind": { "name": "Subtitle", "slug": "subtitle", "status": "active", "canonId": "019de52c-fb09-739d-900c-815b0d9ac526", "version": 1, "description": null }, "framework": null }, "subkind": "subtitle", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:49:05.238+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "a4a3d151-b1ab-436f-a0a5-89d1f6a3ea8d", "parentComponentId": null } ], "metrics": [], "tools": [], "frameworks": [], "arcBeats": [ { "to": 8, "arc": { "name": "The Consultant's Gambit", "slug": "consultants-gambit", "status": "active", "bestFor": "Business cases, project proposals, strategic recommendations", "canonId": "019dd956-5e0a-73c8-b305-81c38c959e9c", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "Situation & Context -> Problem & Complication -> Solution & Approach -> Evidence & Proof -> Impact & Next Steps", "description": null, "familyLabel": null }, "from": 3, "name": "Situation & Context", "beatId": "019dd95a-0682-776c-8e32-88fc09ca9afe", "matchId": "019dd95a-0542-7728-a78e-666792080e8f", "beatType": { "name": "Situation & Context", "slug": "consultants-gambit-situation-context", "status": "active", "canonId": "019dd9b8-05ae-741b-992d-65ee83c639b3", "version": 1, "description": null }, "evidence": "AI is essential, transformation 16 months faster than digital.", "position": 1, "isPrimaryArc": true, "parentBeatType": { "name": "Setup", "slug": "setup", "status": "active", "canonId": "019dd9b8-020e-7505-af9b-d9b9a4679bcc", "version": 1, "description": "Where the deck grounds the reader before doing anything else. Almost every arc opens here." }, "alignedBlockIds": null, "matchConfidence": 88 }, { "to": 13, "arc": { "name": "The Triple Take", "slug": "triple-take", "status": "active", "bestFor": "Data-driven presentations, research findings", "canonId": "019dd956-6221-73ad-bc12-378f8eb1f018", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "The Facts (What) -> The Implications (So What) -> The Action (Now What)", "description": null, "familyLabel": null }, "from": 3, "name": "The Facts (What)", "beatId": "019dd95a-0682-776c-8e32-9ee324fcf070", "matchId": "019dd95a-0542-7728-a78e-68cfbfb51150", "beatType": { "name": "The Facts (What)", "slug": "triple-take-the-facts-what", "status": "active", "canonId": "019dd9b8-092b-754c-8eaa-ede3ffdcb060", "version": 1, "description": null }, "evidence": "AI adoption stats and segmentation of the 2,000-firm sample.", "position": 1, "isPrimaryArc": false, "parentBeatType": { "name": "Setup", "slug": "setup", "status": "active", "canonId": "019dd9b8-020e-7505-af9b-d9b9a4679bcc", "version": 1, "description": "Where the deck grounds the reader before doing anything else. Almost every arc opens here." }, "alignedBlockIds": null, "matchConfidence": 60 } ], "loops": [], "locked": true }, { "page": 7, "type": "analysis", "title": "Includes a comparative area chart showing adoption timelines for AI vs Digital transformation.", "function": "establish_context", "rawType": "industry_trends", "block": null, "metadata": { "slideType": "industry_trends", "slideTypeCanon": { "name": "Industry trends", "slug": "industry_trends", "status": "active", "canonId": "019de52d-0b1d-7705-a0e0-c663199cd1fa", "version": 1, "description": null }, "function": "establish_context", "functionCanon": { "name": "Establish context", "slug": "establish_context", "status": "active", "canonId": "019de52d-1314-74e6-9074-d213dc0bdcdf", "version": 1, "description": null }, "density": "overcrowded", "densityScore": 88, "componentCount": 10, "textChars": 1201, "nDataPoints": 8, "notes": "Includes a comparative area chart showing adoption timelines for AI vs Digital transformation.", "elementsJson": [ "headline_text", "action_title", "subtitle_text", "paragraph", "area_chart", "callout_box", "footnote" ], "confidence": 1, "extraction": { "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "at": "2026-05-02 19:49:06.539+00", "seconds": 3.273, "promptVersion": "v2-canon-conditioned" } }, "links": { "slide": "/slides/019dd923-5ca1-7489-b633-7fa84bbf490b/7", "deck": "/decks/019dd923-5ca1-7489-b633-7fa84bbf490b", "deckAnchor": "/decks/019dd923-5ca1-7489-b633-7fa84bbf490b#slide-7", "deckJson": "/decks/019dd923-5ca1-7489-b633-7fa84bbf490b.json" }, "components": [ { "bbox": null, "kind": "callout", "text": "With early successes building confidence in AI as a value driver, we estimate that AI transformation will happen much faster than digital transformation—16 months faster, on average (Figure 1).", "attrs": null, "canon": { "kind": { "name": "Callout", "slug": "callout", "status": "active", "canonId": "019de52c-f8d3-761a-8953-7d37080de5e2", "version": 1, "description": "Highlighted callout box." }, "tool": { "name": "Visual emphasis", "slug": "visual-emphasis", "status": "active", "bestFor": null, "canonId": "019dd9e1-474b-736b-a8eb-a794dd88241c", "version": 1, "bodyDocId": null, "description": "Drawing the eye to one element above the rest of the slide.", "familyLabel": null }, "subkind": null, "framework": null }, "subkind": null, "groupRole": null, "confidence": null, "extraction": { "at": "2026-04-23 22:41:32+00", "model": "claude-code-default", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "019dd951-9f64-72ba-b3fd-1cbab1dc042f", "parentComponentId": null }, { "bbox": { "h": 0.65, "w": 0.41, "x": 0.53, "y": 0.14 }, "kind": "chart", "text": "Figure 1: We project that AI transformation will take less time than digital transformation", "attrs": null, "canon": { "kind": { "name": "Chart", "slug": "chart", "status": "active", "canonId": "019de52c-f9a0-76ef-adc6-0b859109d1f8", "version": 1, "description": "Quantitative chart." }, "tool": null, "subkind": { "name": "Area chart", "slug": "area", "status": "active", "canonId": "019de52c-ff89-71e0-911e-5cab78b90f53", "version": 1, "description": null }, "framework": null }, "subkind": "area", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:49:06.539+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "9e71aa9b-82b2-4505-9a1c-5838b173a928", "parentComponentId": null }, { "bbox": null, "kind": "metric", "text": "Time advantage of AI vs digital transformation: 16 months", "attrs": null, "canon": { "kind": { "name": "Metric", "slug": "metric", "status": "active", "canonId": "019de52c-f923-73bf-8081-d0b1a8c5264d", "version": 1, "description": "Big-number or KPI value." }, "tool": { "name": "Quantification", "slug": "quantification", "status": "active", "bestFor": null, "canonId": "019dd9e1-47ab-72ce-a079-aab1f5299e88", "version": 1, "bodyDocId": null, "description": "Translating a claim into numbers, charts, or tables.", "familyLabel": null }, "subkind": null, "framework": null }, "subkind": "primary", "groupRole": null, "confidence": null, "extraction": { "at": "2026-04-23 22:41:32+00", "model": "claude-code-default", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "019dd951-9f64-72ba-b3fd-2262b39045be", "parentComponentId": null }, { "bbox": { "h": 0.25, "w": 0.22, "x": 0.06, "y": 0.31 }, "kind": "paragraph", "text": "So, it's no surprise that in 2021, 46% of CEOs... mentioned AI on their earnings calls. More directly, our survey... found that nearly 75% of companies have integrated AI into their business strategies...", "attrs": null, "canon": { "kind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "5f2affc0-941d-4d07-959d-4bfc1930cea4", "version": 1, "description": "Single prose block in the body of a slide." }, "tool": null, "subkind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "019de52c-fb80-75af-aa5c-a7a4bfac2433", "version": 1, "description": null }, "framework": null }, "subkind": "paragraph", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:49:06.539+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "ae1cdbb8-3bf9-4f36-bbcd-91e76fd67a5d", "parentComponentId": null }, { "bbox": { "h": 0.15, "w": 0.22, "x": 0.29, "y": 0.31 }, "kind": "paragraph", "text": "In North America, the companies leading the way are already seeing the results—51% said that the return on their AI initiatives exceeded their expectations, while only 0.4% said the ROI fell short of expectations.", "attrs": null, "canon": { "kind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "5f2affc0-941d-4d07-959d-4bfc1930cea4", "version": 1, "description": "Single prose block in the body of a slide." }, "tool": null, "subkind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "019de52c-fb80-75af-aa5c-a7a4bfac2433", "version": 1, "description": null }, "framework": null }, "subkind": "paragraph", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:49:06.539+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "dfaceac8-e741-42c3-a929-80696c7a5f30", "parentComponentId": null }, { "bbox": { "h": 0.12, "w": 0.22, "x": 0.29, "y": 0.57 }, "kind": "paragraph", "text": "With early successes building confidence in AI as a value driver, we estimate that AI transformation will happen much faster than digital transformation—16 months faster, on average (Figure 1).", "attrs": null, "canon": { "kind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "5f2affc0-941d-4d07-959d-4bfc1930cea4", "version": 1, "description": "Single prose block in the body of a slide." }, "tool": null, "subkind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "019de52c-fb80-75af-aa5c-a7a4bfac2433", "version": 1, "description": null }, "framework": null }, "subkind": "paragraph", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:49:06.539+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "fa97afb2-9e79-4cda-aae6-8d04c71b477b", "parentComponentId": null }, { "bbox": { "h": 0.15, "w": 0.41, "x": 0.53, "y": 0.66 }, "kind": "source-note", "text": "Source: Accenture Research. Note: Our estimate is derived from a natural language processing analysis of investor calls...", "attrs": null, "canon": { "kind": { "name": "Source note", "slug": "source-note", "status": "active", "canonId": "23484952-494b-4a5e-b1ad-550d0d70e948", "version": 1, "description": "Attribution / source / caveat placed at the slide footer. Numbered footnotes use attrs.numbered." }, "tool": null, "subkind": null, "framework": null }, "subkind": null, "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:49:06.539+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "954ec7a3-c5ab-4446-ac06-8c4d83afb864", "parentComponentId": null }, { "bbox": { "h": 0.06, "w": 0.4, "x": 0.06, "y": 0.21 }, "kind": "title", "text": "There is a growing consensus that AI is absolutely essential to competitive advantage.", "attrs": null, "canon": { "kind": { "name": "Title", "slug": "title", "status": "active", "canonId": "019de52c-f7dd-76d9-b848-b1f12bd85cf4", "version": 1, "description": "Slide title or headline." }, "tool": null, "subkind": { "name": "Action title", "slug": "action-title", "status": "active", "canonId": "019de52c-fb31-734c-a0f5-a3935b73135d", "version": 1, "description": null }, "framework": null }, "subkind": "action-title", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:49:06.539+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "15d36351-6d35-4e29-93a5-68ae6387dd0b", "parentComponentId": null }, { "bbox": { "h": 0.04, "w": 0.35, "x": 0.06, "y": 0.14 }, "kind": "title", "text": "AI maturity: Why it matters", "attrs": null, "canon": { "kind": { "name": "Title", "slug": "title", "status": "active", "canonId": "019de52c-f7dd-76d9-b848-b1f12bd85cf4", "version": 1, "description": "Slide title or headline." }, "tool": null, "subkind": { "name": "Headline", "slug": "headline", "status": "active", "canonId": "019de52c-fae1-7463-9a7c-d60668eced0d", "version": 1, "description": null }, "framework": null }, "subkind": "headline", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:49:06.539+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "b562c4f4-5248-47b1-97ef-4b996653ab3e", "parentComponentId": null }, { "bbox": { "h": 0.03, "w": 0.15, "x": 0.29, "y": 0.51 }, "kind": "title", "text": "AI, accelerated", "attrs": null, "canon": { "kind": { "name": "Title", "slug": "title", "status": "active", "canonId": "019de52c-f7dd-76d9-b848-b1f12bd85cf4", "version": 1, "description": "Slide title or headline." }, "tool": null, "subkind": { "name": "Subtitle", "slug": "subtitle", "status": "active", "canonId": "019de52c-fb09-739d-900c-815b0d9ac526", "version": 1, "description": null }, "framework": null }, "subkind": "subtitle", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:49:06.539+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "09d0848a-24dc-4664-9c29-b8a3a8861a46", "parentComponentId": null } ], "metrics": [ { "metricRaw": "Time advantage of AI vs digital transformation", "numberRaw": "16 months", "numberKind": "plain", "actionTitle": "There is a growing consensus that AI is absolutely essential to competitive advantage.", "calloutText": "With early successes building confidence in AI as a value driver, we estimate that AI transformation will happen much faster than digital transformation—16 months faster, on average (Figure 1).", "numberScale": null, "numberValue": 16, "metricFamily": "other", "numberCurrency": null } ], "tools": [ { "tool": { "name": "Causal Chain", "slug": "causal-chain", "status": "active", "bestFor": null, "canonId": "019dd956-9e98-7269-907b-8cf727e9499d", "version": 1, "bodyDocId": null, "description": "Showing how one event leads to another in sequence", "familyLabel": null, "categoryName": "Loop", "categorySlug": "loop" }, "agent": "Architect", "layer": "loop", "agents": [ "Architect" ], "matchId": "019dd95a-0f08-73d3-987c-7d59e527aa7f", "evidence": "Early ROI -> confidence -> faster adoption -> 16-month lead.", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 65, "extraction": { "at": "2026-04-29 13:07:31.336924+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 7, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "Action Titles", "slug": "action-titles", "status": "active", "bestFor": "Any decision-grade deliverable — strategy recommendation, board update, investment memo, M&A review, post-mortem — where the reader is being asked to agree, decide, or act and will skim the title bar at speed.", "canonId": "019dd956-ac70-700b-a608-ba58e78f5dcc", "version": 1, "bodyDocId": "816dad3c-9983-41c1-a86e-978ebd582841", "description": "The McKinsey-bred discipline of writing every slide title as a complete declarative sentence with a verb and an insight, not a topic label. Each title is a sub-claim that ladders up to the deck's governing thought; read in sequence, the titles reconstruct the executive summary.", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Architect", "layer": "slide", "agents": [ "Architect" ], "matchId": "019dd95a-0f08-73d3-987c-6c4500121f00", "evidence": "Subhead asserts insight: 'AI is absolutely essential to competitive advantage'.", "pageRefs": null, "priority": "Core", "whenToUse": "Any decision-grade deliverable — strategy recommendation, board update, investment memo, M&A review, post-mortem — where the reader is being asked to agree, decide, or act and will skim the title bar at speed.", "confidence": 85, "extraction": { "at": "2026-04-29 13:07:31.336924+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 7, "whyItWorks": "Solves two failure modes at once. (1) The buried claim: action titles place the conclusion on the page before any analysis is read, so a busy reader doesn't reverse-engineer it from the chart. (2) The spineless deck: because each title is a claim, slides have to ladder up to the governing thought; logical gaps become visible as topic-shaped titles in a sequence that no longer reads as a story.", "antipattern": "Topic labels disguised as titles — Volume by quarter, Key findings, Pricing strategy, Margins have been impacted. No verb, or a passive verb with no agent, or a fact (Revenue grew 12%) without the so-what. Also: titles that overreach the chart's evidence, multi-claim X-grew-but-Y-fell welded titles, and mechanical repetition of the same X-drove-Y template across the deck.", "cardinality": null, "narrativePurpose": "Forces the deck to carry its argument in the title bar so a senior reader can extract the recommendation without opening a single slide; converts a binder of topics into a navigable pyramid where every slide is a node defending the apex." }, { "tool": { "name": "Annotation", "slug": "annotation", "status": "active", "bestFor": null, "canonId": "019dd956-b5b9-7668-bf0e-3af99823ec5c", "version": 1, "bodyDocId": null, "description": "Adding explanatory labels to highlight key data points", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Designer", "layer": "slide", "agents": [ "Designer" ], "matchId": "019dd95a-0f08-73d3-987c-740c57a9f707", "evidence": "Callout '16 months (13%)' annotates the gap between curves.", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 85, "extraction": { "at": "2026-04-29 13:07:31.336924+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 7, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "Chart Selection Guide", "slug": "chart-selection-guide", "status": "active", "bestFor": null, "canonId": "019dd956-b1a0-700b-ba17-0e16c4d5bcae", "version": 1, "bodyDocId": null, "description": "Choosing the right chart type for your data and message", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Designer", "layer": "slide", "agents": [ "Designer" ], "matchId": "019dd95a-0f08-73d3-987c-722664bfbbf0", "evidence": "S-curve compares AI vs digital transformation diffusion.", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 80, "extraction": { "at": "2026-04-29 13:07:31.336924+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 7, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "Chart Selection Guide", "slug": "chart-selection-guide", "status": "active", "bestFor": null, "canonId": "019dd956-b1a0-700b-ba17-0e16c4d5bcae", "version": 1, "bodyDocId": null, "description": "Choosing the right chart type for your data and message", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Designer", "layer": "slide", "agents": [ "Designer" ], "matchId": "889056d0-fb51-4cb6-b03d-455414e589b5", "evidence": "This slide includes a chart (Figure 1) that supports the discussion of industry trends.", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 0.5, "extraction": { "at": "2026-07-16 21:02:22.717023+00", "model": "or:meta-llama/llama-4-scout", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 7, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "Concrete Language", "slug": "concrete-language", "status": "active", "bestFor": null, "canonId": "019dd956-bcd4-7398-9723-6aa72346170b", "version": 1, "bodyDocId": null, "description": "Using specific sensory details instead of abstract terms", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Storyteller", "layer": "slide", "agents": [ "Storyteller" ], "matchId": "019dd95a-0f08-73d3-987c-792d0dddc71e", "evidence": "46% of CEOs, 75% integration, 26% scaled pilots.", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 85, "extraction": { "at": "2026-04-29 13:07:31.336924+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 7, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null } ], "frameworks": [ { "matchId": "c612ce1d-1232-4ca0-8e9c-a46233784537", "evidence": "Slide title references AI maturity", "framework": null, "confidence": 0.7, "extraction": { "at": "2026-05-02 19:49:06.539+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 7, "frameworkName": "maturity-model" }, { "matchId": "019dd95a-1ca5-70bb-bb9f-4dfad538ddcc", "evidence": "Two overlaid S-curves comparing AI vs digital transformation adoption.", "framework": null, "confidence": 75, "extraction": { "at": "2026-04-29 13:07:34.826634+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 7, "frameworkName": "S-Curve / Diffusion Curve" } ], "arcBeats": [ { "to": 8, "arc": { "name": "The Consultant's Gambit", "slug": "consultants-gambit", "status": "active", "bestFor": "Business cases, project proposals, strategic recommendations", "canonId": "019dd956-5e0a-73c8-b305-81c38c959e9c", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "Situation & Context -> Problem & Complication -> Solution & Approach -> Evidence & Proof -> Impact & Next Steps", "description": null, "familyLabel": null }, "from": 3, "name": "Situation & Context", "beatId": "019dd95a-0682-776c-8e32-88fc09ca9afe", "matchId": "019dd95a-0542-7728-a78e-666792080e8f", "beatType": { "name": "Situation & Context", "slug": "consultants-gambit-situation-context", "status": "active", "canonId": "019dd9b8-05ae-741b-992d-65ee83c639b3", "version": 1, "description": null }, "evidence": "AI is essential, transformation 16 months faster than digital.", "position": 1, "isPrimaryArc": true, "parentBeatType": { "name": "Setup", "slug": "setup", "status": "active", "canonId": "019dd9b8-020e-7505-af9b-d9b9a4679bcc", "version": 1, "description": "Where the deck grounds the reader before doing anything else. Almost every arc opens here." }, "alignedBlockIds": null, "matchConfidence": 88 }, { "to": 13, "arc": { "name": "The Triple Take", "slug": "triple-take", "status": "active", "bestFor": "Data-driven presentations, research findings", "canonId": "019dd956-6221-73ad-bc12-378f8eb1f018", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "The Facts (What) -> The Implications (So What) -> The Action (Now What)", "description": null, "familyLabel": null }, "from": 3, "name": "The Facts (What)", "beatId": "019dd95a-0682-776c-8e32-9ee324fcf070", "matchId": "019dd95a-0542-7728-a78e-68cfbfb51150", "beatType": { "name": "The Facts (What)", "slug": "triple-take-the-facts-what", "status": "active", "canonId": "019dd9b8-092b-754c-8eaa-ede3ffdcb060", "version": 1, "description": null }, "evidence": "AI adoption stats and segmentation of the 2,000-firm sample.", "position": 1, "isPrimaryArc": false, "parentBeatType": { "name": "Setup", "slug": "setup", "status": "active", "canonId": "019dd9b8-020e-7505-af9b-d9b9a4679bcc", "version": 1, "description": "Where the deck grounds the reader before doing anything else. Almost every arc opens here." }, "alignedBlockIds": null, "matchConfidence": 60 } ], "loops": [ { "to": 8, "from": 7, "loop": { "name": "15_why_now", "slug": "15-why-now", "status": "active", "bestFor": "Sales pitches, fundraising, requesting immediate budget approval", "canonId": "019dd956-6c00-70cd-bd42-6bacc4af726f", "version": 1, "bodyDocId": "019df22a-2420-77be-bc41-ded96d08cb21", "structure": "The Context (Trends) -> The Trigger Event -> The Window of Opportunity", "description": "Create temporal urgency by proving that the window of opportunity is opening or closing", "familyLabel": null }, "matchId": "019dd95a-07fe-70ce-8d3a-55ad19dc92c8", "evidence": "Trends (CEO mentions, 75% integration), trigger (early ROI), 16-month window vs digital.", "position": 2, "objective": "Justify urgency of acting on AI maturity", "confidence": 80, "extraction": { "at": "2026-04-29 13:07:29.547081+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null } } ], "locked": true }, { "page": 8, "type": "analysis", "title": "The chart illustrates the migration of companies between low, medium, and high AI-influenced revenue tiers over time.", "function": "analyze_data", "rawType": "data_table", "block": null, "metadata": { "slideType": "data_table", "slideTypeCanon": { "name": "Data table", "slug": "data_table", "status": "active", "canonId": "019de52d-0bbd-71b9-9918-417f904abbf8", "version": 1, "description": null }, "function": "analyze_data", "functionCanon": { "name": "Analyze data", "slug": "analyze_data", "status": "active", "canonId": "019de52d-1590-7413-8c82-cc218cff40b4", "version": 1, "description": null }, "density": "overcrowded", "densityScore": 79, "componentCount": 8, "textChars": 1161, "nDataPoints": 6, "notes": "The chart illustrates the migration of companies between low, medium, and high AI-influenced revenue tiers over time.", "elementsJson": [ "paragraph", "sankey", "footnote" ], "confidence": 1, "extraction": { "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "at": "2026-05-02 19:49:06.866+00", "seconds": 3.227, "promptVersion": "v2-canon-conditioned" } }, "links": { "slide": "/slides/019dd923-5ca1-7489-b633-7fa84bbf490b/8", "deck": "/decks/019dd923-5ca1-7489-b633-7fa84bbf490b", "deckAnchor": "/decks/019dd923-5ca1-7489-b633-7fa84bbf490b#slide-8", "deckJson": "/decks/019dd923-5ca1-7489-b633-7fa84bbf490b.json" }, "components": [ { "bbox": null, "kind": "callout", "text": "The share of companies' revenue that is \"AI-influenced\" in North America more than doubled between 2018 and 2021, and is expected to roughly triple between 2018 and 2024.", "attrs": null, "canon": { "kind": { "name": "Callout", "slug": "callout", "status": "active", "canonId": "019de52c-f8d3-761a-8953-7d37080de5e2", "version": 1, "description": "Highlighted callout box." }, "tool": { "name": "Visual emphasis", "slug": "visual-emphasis", "status": "active", "bestFor": null, "canonId": "019dd9e1-474b-736b-a8eb-a794dd88241c", "version": 1, "bodyDocId": null, "description": "Drawing the eye to one element above the rest of the slide.", "familyLabel": null }, "subkind": null, "framework": null }, "subkind": null, "groupRole": null, "confidence": null, "extraction": { "at": "2026-04-23 22:41:38+00", "model": "claude-code-default", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "019dd951-9f64-72ba-b3fd-4c3d7cdbdda5", "parentComponentId": null }, { "bbox": { "h": 0.45, "w": 0.55, "x": 0.378, "y": 0.2 }, "kind": "chart", "text": "Sankey diagram showing revenue share evolution", "attrs": null, "canon": { "kind": { "name": "Chart", "slug": "chart", "status": "active", "canonId": "019de52c-f9a0-76ef-adc6-0b859109d1f8", "version": 1, "description": "Quantitative chart." }, "tool": null, "subkind": { "name": "Sankey diagram", "slug": "sankey", "status": "active", "canonId": "019de52d-0145-711d-a871-198a7a06733b", "version": 1, "description": null }, "framework": null }, "subkind": "sankey", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:49:06.866+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "0cdc3b8e-f064-406d-93e1-592a1eabddba", "parentComponentId": null }, { "bbox": { "h": 0.1, "w": 0.55, "x": 0.378, "y": 0.82 }, "kind": "disclaimer", "text": "*Definition of “AI-influenced” revenues: a. Sales of existing products and services made possible through better AI-driven insights on customers, supply chain, channels; b. Sales of new products and services made possible through human + AI, c. Higher prices through dynamic pricing ML algorithms.", "attrs": null, "canon": { "kind": { "name": "Disclaimer", "slug": "disclaimer", "status": "active", "canonId": "91173477-d91f-4024-bbaf-d4f93e3f82dc", "version": 1, "description": "Legal/cautionary text that occupies most of the body of its slide." }, "tool": null, "subkind": null, "framework": null }, "subkind": null, "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:49:06.866+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "97a2d3ee-b9d2-4c60-a543-daaed33ca493", "parentComponentId": null }, { "bbox": null, "kind": "metric", "text": "Average AI-influenced revenue share: 30%", "attrs": null, "canon": { "kind": { "name": "Metric", "slug": "metric", "status": "active", "canonId": "019de52c-f923-73bf-8081-d0b1a8c5264d", "version": 1, "description": "Big-number or KPI value." }, "tool": { "name": "Quantification", "slug": "quantification", "status": "active", "bestFor": null, "canonId": "019dd9e1-47ab-72ce-a079-aab1f5299e88", "version": 1, "bodyDocId": null, "description": "Translating a claim into numbers, charts, or tables.", "familyLabel": null }, "subkind": null, "framework": null }, "subkind": "primary", "groupRole": null, "confidence": null, "extraction": { "at": "2026-04-23 22:41:38+00", "model": "claude-code-default", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "019dd951-9f64-72ba-b3fd-5397d408bb7f", "parentComponentId": null }, { "bbox": { "h": 0.15, "w": 0.3, "x": 0.058, "y": 0.14 }, "kind": "paragraph", "text": "There is great incentive to move quickly. We found, for example, that the share of companies' revenue that is “AI-influenced” in North America more than doubled between 2018 and 2021, and is expected to roughly triple between 2018 and 2024 (Figure 2).", "attrs": null, "canon": { "kind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "5f2affc0-941d-4d07-959d-4bfc1930cea4", "version": 1, "description": "Single prose block in the body of a slide." }, "tool": null, "subkind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "019de52c-fb80-75af-aa5c-a7a4bfac2433", "version": 1, "description": null }, "framework": null }, "subkind": "paragraph", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:49:06.866+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "7cf157fa-a00b-4342-9dc0-5a2cddd442fa", "parentComponentId": null }, { "bbox": { "h": 0.15, "w": 0.3, "x": 0.058, "y": 0.295 }, "kind": "paragraph", "text": "Given the evidence, it’s easy to see why companies plan to increase and accelerate their AI investments. In 2021, Achievers in the region devoted 25% of their total technology budgets to AI. By 2024, they expect to devote 31%.", "attrs": null, "canon": { "kind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "5f2affc0-941d-4d07-959d-4bfc1930cea4", "version": 1, "description": "Single prose block in the body of a slide." }, "tool": null, "subkind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "019de52c-fb80-75af-aa5c-a7a4bfac2433", "version": 1, "description": null }, "framework": null }, "subkind": "paragraph", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:49:06.866+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "c9d32969-e656-4dd7-8703-3a06d4672cc7", "parentComponentId": null }, { "bbox": { "h": 0.05, "w": 0.2, "x": 0.378, "y": 0.735 }, "kind": "source-note", "text": "Source: Accenture Research. Note: *2024 = projected", "attrs": null, "canon": { "kind": { "name": "Source note", "slug": "source-note", "status": "active", "canonId": "23484952-494b-4a5e-b1ad-550d0d70e948", "version": 1, "description": "Attribution / source / caveat placed at the slide footer. Numbered footnotes use attrs.numbered." }, "tool": null, "subkind": null, "framework": null }, "subkind": null, "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:49:06.866+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "77c5c8a9-da5d-4102-9aef-b01b9883b912", "parentComponentId": null }, { "bbox": { "h": 0.03, "w": 0.55, "x": 0.378, "y": 0.14 }, "kind": "title", "text": "Figure 2: Evolution of companies' AI-influenced revenue share from 2018 to 2024*", "attrs": null, "canon": { "kind": { "name": "Title", "slug": "title", "status": "active", "canonId": "019de52c-f7dd-76d9-b848-b1f12bd85cf4", "version": 1, "description": "Slide title or headline." }, "tool": null, "subkind": { "name": "Headline", "slug": "headline", "status": "active", "canonId": "019de52c-fae1-7463-9a7c-d60668eced0d", "version": 1, "description": null }, "framework": null }, "subkind": "headline", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:49:06.866+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "d7265b4d-ee98-4f8e-87a5-bcf965cef319", "parentComponentId": null } ], "metrics": [ { "metricRaw": "Average AI-influenced revenue share", "numberRaw": "30%", "numberKind": "percent", "actionTitle": "Figure 2: Evolution of companies' AI-influenced revenue share from 2018 to 2024*", "calloutText": "The share of companies' revenue that is \"AI-influenced\" in North America more than doubled between 2018 and 2021, and is expected to roughly triple between 2018 and 2024.", "numberScale": null, "numberValue": 30, "metricFamily": "share_penetration", "numberCurrency": null } ], "tools": [ { "tool": { "name": "Annotation", "slug": "annotation", "status": "active", "bestFor": null, "canonId": "019dd956-b5b9-7668-bf0e-3af99823ec5c", "version": 1, "bodyDocId": null, "description": "Adding explanatory labels to highlight key data points", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Designer", "layer": "slide", "agents": [ "Designer" ], "matchId": "019dd95a-0f08-73d3-987c-8803ca43a868", "evidence": "Endpoint labels 9%/21%/30% pinpoint the trajectory.", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 75, "extraction": { "at": "2026-04-29 13:07:31.336924+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 8, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "Chart Selection Guide", "slug": "chart-selection-guide", "status": "active", "bestFor": null, "canonId": "019dd956-b1a0-700b-ba17-0e16c4d5bcae", "version": 1, "bodyDocId": null, "description": "Choosing the right chart type for your data and message", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Designer", "layer": "slide", "agents": [ "Designer" ], "matchId": "019dd95a-0f08-73d3-987c-8026b9df577a", "evidence": "Sankey-style flow shows revenue-share migration 9%->21%->30%.", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 80, "extraction": { "at": "2026-04-29 13:07:31.336924+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 8, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "Color Strategy", "slug": "color-strategy", "status": "active", "bestFor": null, "canonId": "019dd956-b202-77cf-8a6e-f445b08c0fd3", "version": 1, "bodyDocId": null, "description": "Using color for emphasis, categories, sentiment, and hierarchy", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Designer", "layer": "slide", "agents": [ "Designer" ], "matchId": "019dd95a-0f08-73d3-987c-8619607a2053", "evidence": "Purple gradient encodes High/Medium/Low AI-influenced bands.", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 75, "extraction": { "at": "2026-04-29 13:07:31.336924+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 8, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "Concrete Language", "slug": "concrete-language", "status": "active", "bestFor": null, "canonId": "019dd956-bcd4-7398-9723-6aa72346170b", "version": 1, "bodyDocId": null, "description": "Using specific sensory details instead of abstract terms", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Storyteller", "layer": "slide", "agents": [ "Storyteller" ], "matchId": "019dd95a-0f08-73d3-987c-8da6a1113acb", "evidence": "Specific percentages and 31% 2024 budget figure in body.", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 85, "extraction": { "at": "2026-04-29 13:07:31.336924+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 8, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null } ], "frameworks": [], "arcBeats": [ { "to": 8, "arc": { "name": "The Consultant's Gambit", "slug": "consultants-gambit", "status": "active", "bestFor": "Business cases, project proposals, strategic recommendations", "canonId": "019dd956-5e0a-73c8-b305-81c38c959e9c", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "Situation & Context -> Problem & Complication -> Solution & Approach -> Evidence & Proof -> Impact & Next Steps", "description": null, "familyLabel": null }, "from": 3, "name": "Situation & Context", "beatId": "019dd95a-0682-776c-8e32-88fc09ca9afe", "matchId": "019dd95a-0542-7728-a78e-666792080e8f", "beatType": { "name": "Situation & Context", "slug": "consultants-gambit-situation-context", "status": "active", "canonId": "019dd9b8-05ae-741b-992d-65ee83c639b3", "version": 1, "description": null }, "evidence": "AI is essential, transformation 16 months faster than digital.", "position": 1, "isPrimaryArc": true, "parentBeatType": { "name": "Setup", "slug": "setup", "status": "active", "canonId": "019dd9b8-020e-7505-af9b-d9b9a4679bcc", "version": 1, "description": "Where the deck grounds the reader before doing anything else. Almost every arc opens here." }, "alignedBlockIds": null, "matchConfidence": 88 }, { "to": 13, "arc": { "name": "The Triple Take", "slug": "triple-take", "status": "active", "bestFor": "Data-driven presentations, research findings", "canonId": "019dd956-6221-73ad-bc12-378f8eb1f018", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "The Facts (What) -> The Implications (So What) -> The Action (Now What)", "description": null, "familyLabel": null }, "from": 3, "name": "The Facts (What)", "beatId": "019dd95a-0682-776c-8e32-9ee324fcf070", "matchId": "019dd95a-0542-7728-a78e-68cfbfb51150", "beatType": { "name": "The Facts (What)", "slug": "triple-take-the-facts-what", "status": "active", "canonId": "019dd9b8-092b-754c-8eaa-ede3ffdcb060", "version": 1, "description": null }, "evidence": "AI adoption stats and segmentation of the 2,000-firm sample.", "position": 1, "isPrimaryArc": false, "parentBeatType": { "name": "Setup", "slug": "setup", "status": "active", "canonId": "019dd9b8-020e-7505-af9b-d9b9a4679bcc", "version": 1, "description": "Where the deck grounds the reader before doing anything else. Almost every arc opens here." }, "alignedBlockIds": null, "matchConfidence": 60 } ], "loops": [ { "to": 8, "from": 7, "loop": { "name": "15_why_now", "slug": "15-why-now", "status": "active", "bestFor": "Sales pitches, fundraising, requesting immediate budget approval", "canonId": "019dd956-6c00-70cd-bd42-6bacc4af726f", "version": 1, "bodyDocId": "019df22a-2420-77be-bc41-ded96d08cb21", "structure": "The Context (Trends) -> The Trigger Event -> The Window of Opportunity", "description": "Create temporal urgency by proving that the window of opportunity is opening or closing", "familyLabel": null }, "matchId": "019dd95a-07fe-70ce-8d3a-55ad19dc92c8", "evidence": "Trends (CEO mentions, 75% integration), trigger (early ROI), 16-month window vs digital.", "position": 2, "objective": "Justify urgency of acting on AI maturity", "confidence": 80, "extraction": { "at": "2026-04-29 13:07:29.547081+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null } } ], "locked": true }, { "page": 9, "type": "setup", "function": "transition", "rawType": "section_divider", "block": null, "metadata": { "slideType": "section_divider", "slideTypeCanon": { "name": "Section divider", "slug": "section_divider", "status": "active", "canonId": "019de52d-066a-7402-9554-6ae504999041", "version": 1, "description": null }, "function": "transition", "functionCanon": { "name": "Transition", "slug": "transition", "status": "active", "canonId": "019de52d-1365-7149-92aa-66df859e75fd", "version": 1, "description": null }, "density": "sparse", "densityScore": 6, "componentCount": 3, "textChars": 45, "nDataPoints": 0, "notes": null, "elementsJson": [ "headline_text", "photo" ], "confidence": 1, "extraction": { "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "at": "2026-05-02 19:49:05.971+00", "seconds": 2.261, "promptVersion": "v2-canon-conditioned" } }, "links": { "slide": "/slides/019dd923-5ca1-7489-b633-7fa84bbf490b/9", "deck": "/decks/019dd923-5ca1-7489-b633-7fa84bbf490b", "deckAnchor": "/decks/019dd923-5ca1-7489-b633-7fa84bbf490b#slide-9", "deckJson": "/decks/019dd923-5ca1-7489-b633-7fa84bbf490b.json" }, "components": [ { "bbox": { "h": 1, "w": 1, "x": 0, "y": 0 }, "kind": "image", "text": null, "attrs": null, "canon": { "kind": { "name": "Image", "slug": "image", "status": "active", "canonId": "019de52c-f978-701f-a720-51d029d769e7", "version": 1, "description": "Photo, illustration, screenshot or icon." }, "tool": null, "subkind": { "name": "Illustration", "slug": "illustration", "status": "active", "canonId": "019de52c-fe76-7772-a5ac-c0b7294d7615", "version": 1, "description": null }, "framework": null }, "subkind": "illustration", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:49:05.971+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "33263a53-01a3-41b8-ae0e-cf1237c3d814", "parentComponentId": null }, { "bbox": { "h": 0.1, "w": 0.5, "x": 0.25, "y": 0.45 }, "kind": "title", "text": "AI maturity: What it is", "attrs": null, "canon": { "kind": { "name": "Title", "slug": "title", "status": "active", "canonId": "019de52c-f7dd-76d9-b848-b1f12bd85cf4", "version": 1, "description": "Slide title or headline." }, "tool": null, "subkind": { "name": "Headline", "slug": "headline", "status": "active", "canonId": "019de52c-fae1-7463-9a7c-d60668eced0d", "version": 1, "description": null }, "framework": null }, "subkind": "headline", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:49:05.971+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "eb5f395b-2c77-4439-8aa3-7b786c3dd50a", "parentComponentId": null }, { "bbox": { "h": 0.05, "w": 0.2, "x": 0.05, "y": 0.1 }, "kind": "title", "text": "The art of AI maturity", "attrs": null, "canon": { "kind": { "name": "Title", "slug": "title", "status": "active", "canonId": "019de52c-f7dd-76d9-b848-b1f12bd85cf4", "version": 1, "description": "Slide title or headline." }, "tool": null, "subkind": { "name": "Subtitle", "slug": "subtitle", "status": "active", "canonId": "019de52c-fb09-739d-900c-815b0d9ac526", "version": 1, "description": null }, "framework": null }, "subkind": "subtitle", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:49:05.971+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "a06353cf-9e0b-4585-ba20-bd43e5896577", "parentComponentId": null } ], "metrics": [], "tools": [], "frameworks": [], "arcBeats": [ { "to": 13, "arc": { "name": "The Consultant's Gambit", "slug": "consultants-gambit", "status": "active", "bestFor": "Business cases, project proposals, strategic recommendations", "canonId": "019dd956-5e0a-73c8-b305-81c38c959e9c", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "Situation & Context -> Problem & Complication -> Solution & Approach -> Evidence & Proof -> Impact & Next Steps", "description": null, "familyLabel": null }, "from": 9, "name": "Problem & Complication", "beatId": "019dd95a-0682-776c-8e32-8d747bbd76a7", "matchId": "019dd95a-0542-7728-a78e-666792080e8f", "beatType": { "name": "Problem & Complication", "slug": "consultants-gambit-problem-complication", "status": "active", "canonId": "019dd9b8-064a-777f-a374-e9a8c43dedd4", "version": 1, "description": null }, "evidence": "AI maturity defined; only 7% qualify as Achievers (Fig 3 2x2).", "position": 2, "isPrimaryArc": true, "parentBeatType": { "name": "Complication", "slug": "complication", "status": "active", "canonId": "019dd9b8-0275-7709-b2d6-4f77c3fc7579", "version": 1, "description": "The point in the narrative where the audience should feel discomfort. Required for argumentative arcs." }, "alignedBlockIds": null, "matchConfidence": 88 }, { "to": 13, "arc": { "name": "The Triple Take", "slug": "triple-take", "status": "active", "bestFor": "Data-driven presentations, research findings", "canonId": "019dd956-6221-73ad-bc12-378f8eb1f018", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "The Facts (What) -> The Implications (So What) -> The Action (Now What)", "description": null, "familyLabel": null }, "from": 3, "name": "The Facts (What)", "beatId": "019dd95a-0682-776c-8e32-9ee324fcf070", "matchId": "019dd95a-0542-7728-a78e-68cfbfb51150", "beatType": { "name": "The Facts (What)", "slug": "triple-take-the-facts-what", "status": "active", "canonId": "019dd9b8-092b-754c-8eaa-ede3ffdcb060", "version": 1, "description": null }, "evidence": "AI adoption stats and segmentation of the 2,000-firm sample.", "position": 1, "isPrimaryArc": false, "parentBeatType": { "name": "Setup", "slug": "setup", "status": "active", "canonId": "019dd9b8-020e-7505-af9b-d9b9a4679bcc", "version": 1, "description": "Where the deck grounds the reader before doing anything else. Almost every arc opens here." }, "alignedBlockIds": null, "matchConfidence": 60 } ], "loops": [], "locked": true }, { "page": 10, "type": "setup", "title": "The slide introduces the concept of AI maturity as a strategic framework for competitive advantage.", "function": "present_framework", "rawType": "key_messages", "block": null, "metadata": { "slideType": "key_messages", "slideTypeCanon": { "name": "Key messages", "slug": "key_messages", "status": "active", "canonId": "019de52d-0712-703f-89f5-bda6688faf3f", "version": 1, "description": null }, "function": "present_framework", "functionCanon": { "name": "Present framework", "slug": "present_framework", "status": "active", "canonId": "019de52d-1403-7667-9100-d2ac6709f750", "version": 1, "description": null }, "density": "balanced", "densityScore": 45, "componentCount": 4, "textChars": 1339, "nDataPoints": 0, "notes": "The slide introduces the concept of AI maturity as a strategic framework for competitive advantage.", "elementsJson": [ "headline_text", "subtitle_text", "paragraph", "callout_box" ], "confidence": 0.95, "extraction": { "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "at": "2026-05-02 19:49:11.107+00", "seconds": 7.226, "promptVersion": "v2-canon-conditioned" } }, "links": { "slide": "/slides/019dd923-5ca1-7489-b633-7fa84bbf490b/10", "deck": "/decks/019dd923-5ca1-7489-b633-7fa84bbf490b", "deckAnchor": "/decks/019dd923-5ca1-7489-b633-7fa84bbf490b#slide-10", "deckJson": "/decks/019dd923-5ca1-7489-b633-7fa84bbf490b.json" }, "components": [ { "bbox": { "h": 0.65, "w": 0.38, "x": 0.55, "y": 0.16 }, "kind": "callout", "text": "AI maturity measures the degree to which organizations have mastered AI-related capabilities in the right combination to achieve high performance for customers, shareholders and employees.", "attrs": null, "canon": { "kind": { "name": "Callout", "slug": "callout", "status": "active", "canonId": "019de52c-f8d3-761a-8953-7d37080de5e2", "version": 1, "description": "Highlighted callout box." }, "tool": null, "subkind": { "name": "Primary callout", "slug": "primary", "status": "active", "canonId": "019de52c-fbd1-70eb-a9ce-8997f8674c1d", "version": 1, "description": null }, "framework": null }, "subkind": "primary", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:49:11.107+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "4621aebe-bf71-472f-a232-1225d6d23141", "parentComponentId": null }, { "bbox": { "h": 0.5, "w": 0.4, "x": 0.06, "y": 0.34 }, "kind": "paragraph", "text": "To uncover strategies for AI success, Accenture designed a holistic AI-maturity framework. Fittingly, our analysis itself was conducted using AI. We applied machine learning models to unravel massive survey datasets and uncover drivers of AI maturity that would have been impossible to detect using more traditional analytical methods (more on the methodology appears in the Appendix). Our research found that AI maturity comes down to mastering a set of key capabilities in the right combinations—not only in data and AI, but also in organizational strategy, talent and culture. Together, these capabilities give companies a strong competitive advantage. (See pages 37 and 38 for key capability descriptions.) Foundational AI capabilities—like cloud platforms and tools, data platforms, architecture and governance—are required to keep pace with competitors. But those are incomplete without “differentiation” AI capabilities, like AI strategy and C-suite sponsorship, combined with a culture of innovation that can set companies apart.", "attrs": null, "canon": { "kind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "5f2affc0-941d-4d07-959d-4bfc1930cea4", "version": 1, "description": "Single prose block in the body of a slide." }, "tool": null, "subkind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "019de52c-fb80-75af-aa5c-a7a4bfac2433", "version": 1, "description": null }, "framework": null }, "subkind": "paragraph", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:49:11.107+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "4ac0aa90-bb00-4cec-918a-3f6f87e6ba4d", "parentComponentId": null }, { "bbox": { "h": 0.08, "w": 0.4, "x": 0.06, "y": 0.22 }, "kind": "title", "text": "If most organizations are racing to embrace AI, why are some seeing more value than others?", "attrs": null, "canon": { "kind": { "name": "Title", "slug": "title", "status": "active", "canonId": "019de52c-f7dd-76d9-b848-b1f12bd85cf4", "version": 1, "description": "Slide title or headline." }, "tool": null, "subkind": { "name": "Action title", "slug": "action-title", "status": "active", "canonId": "019de52c-fb31-734c-a0f5-a3935b73135d", "version": 1, "description": null }, "framework": null }, "subkind": "action-title", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:49:11.107+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "08fe0895-153d-441f-ae87-ee0b601709e4", "parentComponentId": null }, { "bbox": { "h": 0.05, "w": 0.3, "x": 0.06, "y": 0.16 }, "kind": "title", "text": "AI maturity: What it is", "attrs": null, "canon": { "kind": { "name": "Title", "slug": "title", "status": "active", "canonId": "019de52c-f7dd-76d9-b848-b1f12bd85cf4", "version": 1, "description": "Slide title or headline." }, "tool": null, "subkind": { "name": "Headline", "slug": "headline", "status": "active", "canonId": "019de52c-fae1-7463-9a7c-d60668eced0d", "version": 1, "description": null }, "framework": null }, "subkind": "headline", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:49:11.107+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "41d574fd-89d3-4609-83f8-8be17e930683", "parentComponentId": null } ], "metrics": [], "tools": [ { "tool": { "name": "Concrete Language", "slug": "concrete-language", "status": "active", "bestFor": null, "canonId": "019dd956-bcd4-7398-9723-6aa72346170b", "version": 1, "bodyDocId": null, "description": "Using specific sensory details instead of abstract terms", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Storyteller", "layer": "slide", "agents": [ "Storyteller" ], "matchId": "019dd95a-0f08-73d3-987c-9777c430d9ef", "evidence": "Customers, shareholders, employees named as outcome dimensions.", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 60, "extraction": { "at": "2026-04-29 13:07:31.336924+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 10, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "Core Message Extraction", "slug": "core-message-extraction", "status": "active", "bestFor": "Any slide that carries an argument or finding. The diagnostic: if the slide has a chart on it, it needs a core message. Run extraction whenever the current title is a topic (Q3 performance, Customer satisfaction) rather than a claim, or when a reader could reasonably draw more than one conclusion from the visible evidence.", "canonId": "019dd956-bc71-707d-8867-1b2e810175cf", "version": 1, "bodyDocId": "f85613cb-4b77-462f-bfe6-3b862516e1a6", "description": "The discipline of distilling raw analysis, data, or content into a single declarative sentence — the slide's core message — that the audience would walk away with if they remembered nothing else. Process, not artefact: extraction questions run on the raw content until one sentence falls out.", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Architect", "layer": "slide", "agents": [ "Architect" ], "matchId": "019dd95a-0f08-73d3-987c-91cfe0408de9", "evidence": "Defines AI maturity as the central concept for the whole report.", "pageRefs": null, "priority": null, "whenToUse": "Any slide that carries an argument or finding. The diagnostic: if the slide has a chart on it, it needs a core message. Run extraction whenever the current title is a topic (Q3 performance, Customer satisfaction) rather than a claim, or when a reader could reasonably draw more than one conclusion from the visible evidence.", "confidence": 80, "extraction": { "at": "2026-04-29 13:07:31.336924+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 10, "whyItWorks": "Solves the two failure modes of slide writing simultaneously: the topic title (which outsources interpretation to the audience and produces three different conclusions in three different heads) and the multi-thesis stapler (which exceeds working memory and gets remembered as fragments). Aligns with how readers actually consume decks — Heath & Heath's Find the Core, the journalist's nut graf, and Minto's governing thought all converge on the same cognitive economics.", "antipattern": "Topic titles disguised as core messages (Customer satisfaction, no verb, no stake); multi-thesis sentences stapled with and; hedged sentences (may show signs of possible softening); chart-caption titles (Revenue fell 4%) that restate what the chart already shows instead of naming the so-what; meta-commentary (this slide explores...) that describes the slide rather than concluding it.", "cardinality": null, "narrativePurpose": "Forces the slide author to do the interpretive work before the slide ships, so the audience does not have to do it during the meeting. Wins the WYSIATI battle on purpose — the loudest fragment on the page becomes the author's chosen sentence rather than whichever chart label happens to be largest." } ], "frameworks": [ { "matchId": "f9a265ce-9abd-47d5-bcb5-2c2a8d99fa98", "evidence": "The slide explicitly discusses an 'AI-maturity framework' and defines the concept of maturity.", "framework": null, "confidence": 0.9, "extraction": { "at": "2026-05-02 19:49:11.107+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 10, "frameworkName": "maturity-model" } ], "arcBeats": [ { "to": 13, "arc": { "name": "The Consultant's Gambit", "slug": "consultants-gambit", "status": "active", "bestFor": "Business cases, project proposals, strategic recommendations", "canonId": "019dd956-5e0a-73c8-b305-81c38c959e9c", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "Situation & Context -> Problem & Complication -> Solution & Approach -> Evidence & Proof -> Impact & Next Steps", "description": null, "familyLabel": null }, "from": 9, "name": "Problem & Complication", "beatId": "019dd95a-0682-776c-8e32-8d747bbd76a7", "matchId": "019dd95a-0542-7728-a78e-666792080e8f", "beatType": { "name": "Problem & Complication", "slug": "consultants-gambit-problem-complication", "status": "active", "canonId": "019dd9b8-064a-777f-a374-e9a8c43dedd4", "version": 1, "description": null }, "evidence": "AI maturity defined; only 7% qualify as Achievers (Fig 3 2x2).", "position": 2, "isPrimaryArc": true, "parentBeatType": { "name": "Complication", "slug": "complication", "status": "active", "canonId": "019dd9b8-0275-7709-b2d6-4f77c3fc7579", "version": 1, "description": "The point in the narrative where the audience should feel discomfort. Required for argumentative arcs." }, "alignedBlockIds": null, "matchConfidence": 88 }, { "to": 13, "arc": { "name": "The Triple Take", "slug": "triple-take", "status": "active", "bestFor": "Data-driven presentations, research findings", "canonId": "019dd956-6221-73ad-bc12-378f8eb1f018", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "The Facts (What) -> The Implications (So What) -> The Action (Now What)", "description": null, "familyLabel": null }, "from": 3, "name": "The Facts (What)", "beatId": "019dd95a-0682-776c-8e32-9ee324fcf070", "matchId": "019dd95a-0542-7728-a78e-68cfbfb51150", "beatType": { "name": "The Facts (What)", "slug": "triple-take-the-facts-what", "status": "active", "canonId": "019dd9b8-092b-754c-8eaa-ede3ffdcb060", "version": 1, "description": null }, "evidence": "AI adoption stats and segmentation of the 2,000-firm sample.", "position": 1, "isPrimaryArc": false, "parentBeatType": { "name": "Setup", "slug": "setup", "status": "active", "canonId": "019dd9b8-020e-7505-af9b-d9b9a4679bcc", "version": 1, "description": "Where the deck grounds the reader before doing anything else. Almost every arc opens here." }, "alignedBlockIds": null, "matchConfidence": 60 } ], "loops": [ { "to": 13, "from": 10, "loop": { "name": "30_2x2_matrix", "slug": "30-2x2-matrix", "status": "active", "bestFor": "Portfolio analysis, prioritization, strategic positioning", "canonId": "019dd956-7225-756a-9cc7-1e6d3f039818", "version": 1, "bodyDocId": "019df22a-2420-77be-bc41-ded96d08cb21", "structure": "Dimension 1 (X-axis) -> Dimension 2 (Y-axis) -> The Four Quadrants -> The Sweet Spot", "description": "Plot options on two critical dimensions to reveal the optimal quadrant", "familyLabel": null }, "matchId": "019dd95a-07fe-70ce-8d3a-5987e0314b42", "evidence": "Fig 3 2x2 with axes AI Foundation/Differentiation defines Achievers/Innovators/Builders/Experimenters.", "position": 3, "objective": "Segment firms via the AI Foundation x Differentiation 2x2", "confidence": 92, "extraction": { "at": "2026-04-29 13:07:29.547081+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null } } ], "locked": true }, { "page": 11, "type": "setup", "title": "The slide uses a scatter plot overlaid on a 2x2 matrix to visualize the distribution of companies.", "function": "present_framework", "rawType": "segmentation", "block": null, "metadata": { "slideType": "segmentation", "slideTypeCanon": { "name": "Segmentation", "slug": "segmentation", "status": "active", "canonId": "019de52d-0917-75d5-9172-1b3b3c2f6400", "version": 1, "description": null }, "function": "present_framework", "functionCanon": { "name": "Present framework", "slug": "present_framework", "status": "active", "canonId": "019de52d-1403-7667-9100-d2ac6709f750", "version": 1, "description": null }, "density": "dense", "densityScore": 74, "componentCount": 7, "textChars": 1486, "nDataPoints": 4, "notes": "The slide uses a scatter plot overlaid on a 2x2 matrix to visualize the distribution of companies.", "elementsJson": [ "headline_text", "paragraph", "quadrant_chart", "scatter_plot", "matrix_2x2", "footnote" ], "confidence": 1, "extraction": { "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "at": "2026-05-02 19:49:12.308+00", "seconds": 8.419, "promptVersion": "v2-canon-conditioned" } }, "links": { "slide": "/slides/019dd923-5ca1-7489-b633-7fa84bbf490b/11", "deck": "/decks/019dd923-5ca1-7489-b633-7fa84bbf490b", "deckAnchor": "/decks/019dd923-5ca1-7489-b633-7fa84bbf490b#slide-11", "deckJson": "/decks/019dd923-5ca1-7489-b633-7fa84bbf490b.json" }, "components": [ { "bbox": null, "kind": "callout", "text": "Even so, only 7% of the world's 2,000 largest firms by market cap can be classified as Achievers.", "attrs": null, "canon": { "kind": { "name": "Callout", "slug": "callout", "status": "active", "canonId": "019de52c-f8d3-761a-8953-7d37080de5e2", "version": 1, "description": "Highlighted callout box." }, "tool": { "name": "Visual emphasis", "slug": "visual-emphasis", "status": "active", "bestFor": null, "canonId": "019dd9e1-474b-736b-a8eb-a794dd88241c", "version": 1, "bodyDocId": null, "description": "Drawing the eye to one element above the rest of the slide.", "familyLabel": null }, "subkind": null, "framework": null }, "subkind": null, "groupRole": null, "confidence": null, "extraction": { "at": "2026-04-23 22:41:43+00", "model": "claude-code-default", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "019dd951-9f64-72ba-b3fd-6ea76d5eff74", "parentComponentId": null }, { "bbox": { "h": 0.645, "w": 0.537, "x": 0.415, "y": 0.205 }, "kind": "chart", "text": "Scatter plot of organizations by AI Foundation and AI Differentiation", "attrs": null, "canon": { "kind": { "name": "Chart", "slug": "chart", "status": "active", "canonId": "019de52c-f9a0-76ef-adc6-0b859109d1f8", "version": 1, "description": "Quantitative chart." }, "tool": null, "subkind": { "name": "Scatter plot", "slug": "scatter", "status": "active", "canonId": "019de52d-007d-72ec-8689-c79fb78e21a2", "version": 1, "description": null }, "framework": null }, "subkind": "scatter", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:49:12.308+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "5dc82f30-1d8d-41d9-a0e1-253796c6b511", "parentComponentId": null }, { "bbox": { "h": 0.685, "w": 0.595, "x": 0.357, "y": 0.185 }, "kind": "framework", "text": "2x2 Matrix", "attrs": null, "canon": { "kind": { "name": "Framework", "slug": "framework", "status": "active", "canonId": "019de52c-fa18-77c6-b10a-ccb8277ac0fa", "version": 1, "description": "Named conceptual framework instance." }, "tool": null, "subkind": { "name": "Framework instance", "slug": "instance", "status": "active", "canonId": "019de52d-05a2-72af-be0b-7edc60708a03", "version": 1, "description": null }, "framework": null }, "subkind": "instance", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:49:12.308+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "b217abcc-ff62-4052-b541-c7a515d8b7fa", "parentComponentId": null }, { "bbox": null, "kind": "metric", "text": "Share of organizations classified as AI Achievers: 7%", "attrs": null, "canon": { "kind": { "name": "Metric", "slug": "metric", "status": "active", "canonId": "019de52c-f923-73bf-8081-d0b1a8c5264d", "version": 1, "description": "Big-number or KPI value." }, "tool": { "name": "Quantification", "slug": "quantification", "status": "active", "bestFor": null, "canonId": "019dd9e1-47ab-72ce-a079-aab1f5299e88", "version": 1, "bodyDocId": null, "description": "Translating a claim into numbers, charts, or tables.", "familyLabel": null }, "subkind": null, "framework": null }, "subkind": "primary", "groupRole": null, "confidence": null, "extraction": { "at": "2026-04-23 22:41:43+00", "model": "claude-code-default", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "019dd951-9f64-72ba-b3fd-71b00206cb80", "parentComponentId": null }, { "bbox": { "h": 0.718, "w": 0.297, "x": 0.058, "y": 0.141 }, "kind": "paragraph", "text": "The companies that scored best in both categories are the AI Achievers and deliver high performance for customers, shareholders and employees. Meanwhile, AI Builders show strong foundational capabilities and average differentiation capabilities, and AI Innovators show strong differentiation capabilities and average foundational capabilities. Achievers, Builders and Innovators collectively represent just 25% of surveyed organizations (Figure 3). A fourth group we’re calling AI Experimenters—those with average capabilities in both categories—make up the majority (75%) of those surveyed. Achievers, Builders and Innovators tend to have more resources (such as technology, talent and patents) than Experimenters to deliver on their AI visions and to transform their organizations. Examples can be found across a wide range of industries: healthcare, financial services, life sciences, utilities, retail, energy and more. Even so, only 7% of the world’s 2,000 largest firms by market cap can be classified as Achievers. This suggests that even with strategic investments large firms may struggle to make the large foundational and cultural shifts needed to become AI Achievers.", "attrs": null, "canon": { "kind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "5f2affc0-941d-4d07-959d-4bfc1930cea4", "version": 1, "description": "Single prose block in the body of a slide." }, "tool": null, "subkind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "019de52c-fb80-75af-aa5c-a7a4bfac2433", "version": 1, "description": null }, "framework": null }, "subkind": "paragraph", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:49:12.308+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "5a98fb27-ec6c-43f5-9fc9-4e2a6a14dc7e", "parentComponentId": null }, { "bbox": { "h": 0.02, "w": 0.15, "x": 0.357, "y": 0.821 }, "kind": "source-note", "text": "Source: Accenture Research.", "attrs": null, "canon": { "kind": { "name": "Source note", "slug": "source-note", "status": "active", "canonId": "23484952-494b-4a5e-b1ad-550d0d70e948", "version": 1, "description": "Attribution / source / caveat placed at the slide footer. Numbered footnotes use attrs.numbered." }, "tool": null, "subkind": null, "framework": null }, "subkind": null, "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:49:12.308+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "7ed20fcf-90ba-4d9d-9d2c-d4df5e6108ba", "parentComponentId": null }, { "bbox": { "h": 0.022, "w": 0.325, "x": 0.357, "y": 0.141 }, "kind": "title", "text": "Figure 3: Only 7% of organizations are AI Achievers", "attrs": null, "canon": { "kind": { "name": "Title", "slug": "title", "status": "active", "canonId": "019de52c-f7dd-76d9-b848-b1f12bd85cf4", "version": 1, "description": "Slide title or headline." }, "tool": null, "subkind": { "name": "Headline", "slug": "headline", "status": "active", "canonId": "019de52c-fae1-7463-9a7c-d60668eced0d", "version": 1, "description": null }, "framework": null }, "subkind": "headline", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:49:12.308+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "59b6b7f3-4be9-4183-beb7-944afdb83cd4", "parentComponentId": null } ], "metrics": [ { "metricRaw": "Share of organizations classified as AI Achievers", "numberRaw": "7%", "numberKind": "percent", "actionTitle": "Figure 3: Only 7% of organizations are AI Achievers", "calloutText": "Even so, only 7% of the world's 2,000 largest firms by market cap can be classified as Achievers.", "numberScale": null, "numberValue": 7, "metricFamily": "survey_sentiment", "numberCurrency": null } ], "tools": [ { "tool": { "name": "Scarcity", "slug": "scarcity", "status": "active", "bestFor": null, "canonId": "019dd956-9610-7038-a580-6ef34d95f742", "version": 1, "bodyDocId": null, "description": "Limited availability increases perceived value - time limits and exclusivity", "familyLabel": null, "categoryName": "Block", "categorySlug": "block" }, "agent": "Storyteller", "layer": "block", "agents": [ "Storyteller" ], "matchId": "019dd95a-0f08-73d3-987c-adda7a47f67d", "evidence": "Only 7% framing makes Achiever status feel scarce and aspirational.", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 75, "extraction": { "at": "2026-04-29 13:07:31.336924+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 11, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "2x2 matrix", "slug": "matrix-2x2", "status": "active", "bestFor": null, "canonId": "019dd9e1-50ab-72d1-8afb-3ab0a38e32a8", "version": 1, "bodyDocId": null, "description": "BCG matrix, importance/urgency, any axes-and-quadrants frame.", "familyLabel": null, "categoryName": null, "categorySlug": null }, "agent": null, "layer": "slide", "agents": null, "matchId": "d75fd6c4-fb15-4386-b4c5-67c186024840", "evidence": "This slide includes a 2x2 matrix that categorizes organizations into AI Achievers, AI Builders, etc.", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 0.8, "extraction": { "at": "2026-07-16 21:02:22.910197+00", "model": "or:meta-llama/llama-4-scout", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 11, "whyItWorks": null, "antipattern": null, "cardinality": "common", "narrativePurpose": null }, { "tool": { "name": "Action Titles", "slug": "action-titles", "status": "active", "bestFor": "Any decision-grade deliverable — strategy recommendation, board update, investment memo, M&A review, post-mortem — where the reader is being asked to agree, decide, or act and will skim the title bar at speed.", "canonId": "019dd956-ac70-700b-a608-ba58e78f5dcc", "version": 1, "bodyDocId": "816dad3c-9983-41c1-a86e-978ebd582841", "description": "The McKinsey-bred discipline of writing every slide title as a complete declarative sentence with a verb and an insight, not a topic label. Each title is a sub-claim that ladders up to the deck's governing thought; read in sequence, the titles reconstruct the executive summary.", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Architect", "layer": "slide", "agents": [ "Architect" ], "matchId": "019dd95a-0f08-73d3-987c-988bbdd684fa", "evidence": "Title states the so-what: 'Only 7% of organizations are AI Achievers'.", "pageRefs": null, "priority": "Core", "whenToUse": "Any decision-grade deliverable — strategy recommendation, board update, investment memo, M&A review, post-mortem — where the reader is being asked to agree, decide, or act and will skim the title bar at speed.", "confidence": 90, "extraction": { "at": "2026-04-29 13:07:31.336924+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 11, "whyItWorks": "Solves two failure modes at once. (1) The buried claim: action titles place the conclusion on the page before any analysis is read, so a busy reader doesn't reverse-engineer it from the chart. (2) The spineless deck: because each title is a claim, slides have to ladder up to the governing thought; logical gaps become visible as topic-shaped titles in a sequence that no longer reads as a story.", "antipattern": "Topic labels disguised as titles — Volume by quarter, Key findings, Pricing strategy, Margins have been impacted. No verb, or a passive verb with no agent, or a fact (Revenue grew 12%) without the so-what. Also: titles that overreach the chart's evidence, multi-claim X-grew-but-Y-fell welded titles, and mechanical repetition of the same X-drove-Y template across the deck.", "cardinality": null, "narrativePurpose": "Forces the deck to carry its argument in the title bar so a senior reader can extract the recommendation without opening a single slide; converts a binder of topics into a navigable pyramid where every slide is a node defending the apex." }, { "tool": { "name": "Annotation", "slug": "annotation", "status": "active", "bestFor": null, "canonId": "019dd956-b5b9-7668-bf0e-3af99823ec5c", "version": 1, "bodyDocId": null, "description": "Adding explanatory labels to highlight key data points", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Designer", "layer": "slide", "agents": [ "Designer" ], "matchId": "019dd95a-0f08-73d3-987c-a13946e009f7", "evidence": "Each quadrant labelled with name, % and short descriptor.", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 80, "extraction": { "at": "2026-04-29 13:07:31.336924+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 11, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "Color Strategy", "slug": "color-strategy", "status": "active", "bestFor": null, "canonId": "019dd956-b202-77cf-8a6e-f445b08c0fd3", "version": 1, "bodyDocId": null, "description": "Using color for emphasis, categories, sentiment, and hierarchy", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Designer", "layer": "slide", "agents": [ "Designer" ], "matchId": "019dd95a-0f08-73d3-987c-a47bf9474550", "evidence": "Achievers tinted in signature purple, others muted.", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 70, "extraction": { "at": "2026-04-29 13:07:31.336924+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 11, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "Concrete Language", "slug": "concrete-language", "status": "active", "bestFor": null, "canonId": "019dd956-bcd4-7398-9723-6aa72346170b", "version": 1, "bodyDocId": null, "description": "Using specific sensory details instead of abstract terms", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Storyteller", "layer": "slide", "agents": [ "Storyteller" ], "matchId": "019dd95a-0f08-73d3-987c-a84ef8da7810", "evidence": "7%, 10%, 8%, 75% sized as headline numbers.", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 85, "extraction": { "at": "2026-04-29 13:07:31.336924+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 11, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "Visual Hierarchy", "slug": "visual-hierarchy", "status": "active", "bestFor": null, "canonId": "019dd956-b2ca-706b-937f-e52441086fd7", "version": 1, "bodyDocId": null, "description": "Order of perception through Size > Color > Position > Weight > Space", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Designer", "layer": "slide", "agents": [ "Designer" ], "matchId": "019dd95a-0f08-73d3-987c-9fc1c5fce2ad", "evidence": "Big colored % per quadrant dominates the chart.", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 75, "extraction": { "at": "2026-04-29 13:07:31.336924+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 11, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null } ], "frameworks": [ { "matchId": "019dd95a-1ca5-70bb-bb9f-51648a4e750f", "evidence": "Axes labelled 'AI Foundation' (x) and 'AI Differentiation' (y); four named quadrants.", "framework": null, "confidence": 95, "extraction": { "at": "2026-04-29 13:07:34.826634+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 11, "frameworkName": "2x2 Matrix" }, { "matchId": "1fc3a0c9-c4cf-4b50-9242-33c1d08ebd78", "evidence": "The slide uses a 2x2 grid to categorize companies based on two axes: AI Foundation and AI Differentiation.", "framework": null, "confidence": 1, "extraction": { "at": "2026-05-02 19:49:12.308+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 11, "frameworkName": "matrix-2x2" } ], "arcBeats": [ { "to": 13, "arc": { "name": "The Consultant's Gambit", "slug": "consultants-gambit", "status": "active", "bestFor": "Business cases, project proposals, strategic recommendations", "canonId": "019dd956-5e0a-73c8-b305-81c38c959e9c", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "Situation & Context -> Problem & Complication -> Solution & Approach -> Evidence & Proof -> Impact & Next Steps", "description": null, "familyLabel": null }, "from": 9, "name": "Problem & Complication", "beatId": "019dd95a-0682-776c-8e32-8d747bbd76a7", "matchId": "019dd95a-0542-7728-a78e-666792080e8f", "beatType": { "name": "Problem & Complication", "slug": "consultants-gambit-problem-complication", "status": "active", "canonId": "019dd9b8-064a-777f-a374-e9a8c43dedd4", "version": 1, "description": null }, "evidence": "AI maturity defined; only 7% qualify as Achievers (Fig 3 2x2).", "position": 2, "isPrimaryArc": true, "parentBeatType": { "name": "Complication", "slug": "complication", "status": "active", "canonId": "019dd9b8-0275-7709-b2d6-4f77c3fc7579", "version": 1, "description": "The point in the narrative where the audience should feel discomfort. Required for argumentative arcs." }, "alignedBlockIds": null, "matchConfidence": 88 }, { "to": 13, "arc": { "name": "The Triple Take", "slug": "triple-take", "status": "active", "bestFor": "Data-driven presentations, research findings", "canonId": "019dd956-6221-73ad-bc12-378f8eb1f018", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "The Facts (What) -> The Implications (So What) -> The Action (Now What)", "description": null, "familyLabel": null }, "from": 3, "name": "The Facts (What)", "beatId": "019dd95a-0682-776c-8e32-9ee324fcf070", "matchId": "019dd95a-0542-7728-a78e-68cfbfb51150", "beatType": { "name": "The Facts (What)", "slug": "triple-take-the-facts-what", "status": "active", "canonId": "019dd9b8-092b-754c-8eaa-ede3ffdcb060", "version": 1, "description": null }, "evidence": "AI adoption stats and segmentation of the 2,000-firm sample.", "position": 1, "isPrimaryArc": false, "parentBeatType": { "name": "Setup", "slug": "setup", "status": "active", "canonId": "019dd9b8-020e-7505-af9b-d9b9a4679bcc", "version": 1, "description": "Where the deck grounds the reader before doing anything else. Almost every arc opens here." }, "alignedBlockIds": null, "matchConfidence": 60 } ], "loops": [ { "to": 13, "from": 10, "loop": { "name": "30_2x2_matrix", "slug": "30-2x2-matrix", "status": "active", "bestFor": "Portfolio analysis, prioritization, strategic positioning", "canonId": "019dd956-7225-756a-9cc7-1e6d3f039818", "version": 1, "bodyDocId": "019df22a-2420-77be-bc41-ded96d08cb21", "structure": "Dimension 1 (X-axis) -> Dimension 2 (Y-axis) -> The Four Quadrants -> The Sweet Spot", "description": "Plot options on two critical dimensions to reveal the optimal quadrant", "familyLabel": null }, "matchId": "019dd95a-07fe-70ce-8d3a-5987e0314b42", "evidence": "Fig 3 2x2 with axes AI Foundation/Differentiation defines Achievers/Innovators/Builders/Experimenters.", "position": 3, "objective": "Segment firms via the AI Foundation x Differentiation 2x2", "confidence": 92, "extraction": { "at": "2026-04-29 13:07:29.547081+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null } } ], "locked": true }, { "page": 12, "type": "analysis", "title": "The chart is a dumbbell plot showing the progression of AI maturity scores by industry.", "function": "analyze_data", "rawType": "industry_trends", "block": null, "metadata": { "slideType": "industry_trends", "slideTypeCanon": { "name": "Industry trends", "slug": "industry_trends", "status": "active", "canonId": "019de52d-0b1d-7705-a0e0-c663199cd1fa", "version": 1, "description": null }, "function": "analyze_data", "functionCanon": { "name": "Analyze data", "slug": "analyze_data", "status": "active", "canonId": "019de52d-1590-7413-8c82-cc218cff40b4", "version": 1, "description": null }, "density": "overcrowded", "densityScore": 83, "componentCount": 8, "textChars": 1302, "nDataPoints": 32, "notes": "The chart is a dumbbell plot showing the progression of AI maturity scores by industry.", "elementsJson": [ "headline_text", "paragraph", "scatter_plot", "footnote" ], "confidence": 1, "extraction": { "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "at": "2026-05-02 19:49:07.307+00", "seconds": 3.177, "promptVersion": "v2-canon-conditioned" } }, "links": { "slide": "/slides/019dd923-5ca1-7489-b633-7fa84bbf490b/12", "deck": "/decks/019dd923-5ca1-7489-b633-7fa84bbf490b", "deckAnchor": "/decks/019dd923-5ca1-7489-b633-7fa84bbf490b#slide-12", "deckJson": "/decks/019dd923-5ca1-7489-b633-7fa84bbf490b.json" }, "components": [ { "bbox": null, "kind": "callout", "text": "While industries like tech are currently far ahead in their respective AI maturity, the gap will likely narrow considerably by 2024.", "attrs": null, "canon": { "kind": { "name": "Callout", "slug": "callout", "status": "active", "canonId": "019de52c-f8d3-761a-8953-7d37080de5e2", "version": 1, "description": "Highlighted callout box." }, "tool": { "name": "Visual emphasis", "slug": "visual-emphasis", "status": "active", "bestFor": null, "canonId": "019dd9e1-474b-736b-a8eb-a794dd88241c", "version": 1, "bodyDocId": null, "description": "Drawing the eye to one element above the rest of the slide.", "familyLabel": null }, "subkind": null, "framework": null }, "subkind": null, "groupRole": null, "confidence": null, "extraction": { "at": "2026-04-23 22:41:49+00", "model": "claude-code-default", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "019dd951-9f64-72ba-b3fd-940099c77782", "parentComponentId": null }, { "bbox": { "h": 0.75, "w": 0.415, "x": 0.528, "y": 0.1 }, "kind": "chart", "text": "Figure 4: Levels of AI maturity by industry, 2021 and 2024*", "attrs": null, "canon": { "kind": { "name": "Chart", "slug": "chart", "status": "active", "canonId": "019de52c-f9a0-76ef-adc6-0b859109d1f8", "version": 1, "description": "Quantitative chart." }, "tool": null, "subkind": { "name": "Horizontal bar chart", "slug": "bar-horizontal", "status": "active", "canonId": "019de52c-fec4-7221-986b-1cb5f5e84b1f", "version": 1, "description": null }, "framework": null }, "subkind": "bar-horizontal", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:49:07.307+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "c442b75d-64fd-4753-8ce2-2324eb9f7bb2", "parentComponentId": null }, { "bbox": { "h": 0.05, "w": 0.415, "x": 0.528, "y": 0.88 }, "kind": "disclaimer", "text": "Note: *2024 = estimated scores. Industries’ AI maturity scores represent the arithmetic average of their respective Foundational and Differentiation index. North America n= 373.", "attrs": null, "canon": { "kind": { "name": "Disclaimer", "slug": "disclaimer", "status": "active", "canonId": "91173477-d91f-4024-bbaf-d4f93e3f82dc", "version": 1, "description": "Legal/cautionary text that occupies most of the body of its slide." }, "tool": null, "subkind": null, "framework": null }, "subkind": null, "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:49:07.307+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "5a1a6e56-5e35-4c35-9d81-cd585d32767f", "parentComponentId": null }, { "bbox": null, "kind": "metric", "text": "Median AI Maturity (0-100): 60", "attrs": null, "canon": { "kind": { "name": "Metric", "slug": "metric", "status": "active", "canonId": "019de52c-f923-73bf-8081-d0b1a8c5264d", "version": 1, "description": "Big-number or KPI value." }, "tool": { "name": "Quantification", "slug": "quantification", "status": "active", "bestFor": null, "canonId": "019dd9e1-47ab-72ce-a079-aab1f5299e88", "version": 1, "bodyDocId": null, "description": "Translating a claim into numbers, charts, or tables.", "familyLabel": null }, "subkind": null, "framework": null }, "subkind": "primary", "groupRole": null, "confidence": null, "extraction": { "at": "2026-04-23 22:41:49+00", "model": "claude-code-default", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "019dd951-9f64-72ba-b3fd-9be49230c84d", "parentComponentId": null }, { "bbox": { "h": 0.405, "w": 0.25, "x": 0.058, "y": 0.192 }, "kind": "paragraph", "text": "While industries like tech are currently far ahead in their respective AI maturity, the gap will likely narrow considerably by 2024 (Figure 4). Automotive is betting on a big surge in sales of AI-powered self-driving vehicles. Aerospace and defense firms anticipate continued demand for AI-enabled remote systems. Retail will keep raising the bar of customer experience with AI. And the life sciences industry will expand its use of AI in efficient drug development. Still, there is enormous room for growth in AI adoption across all industries and an enormous opportunity for those organizations that choose to seize it.", "attrs": null, "canon": { "kind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "5f2affc0-941d-4d07-959d-4bfc1930cea4", "version": 1, "description": "Single prose block in the body of a slide." }, "tool": null, "subkind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "019de52c-fb80-75af-aa5c-a7a4bfac2433", "version": 1, "description": null }, "framework": null }, "subkind": "paragraph", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:49:07.307+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "cfbefb79-5002-4f8e-9337-11a50e1d2340", "parentComponentId": null }, { "bbox": { "h": 0.145, "w": 0.25, "x": 0.325, "y": 0.192 }, "kind": "paragraph", "text": "For industry laggards like financial services and healthcare, a range of factors may be contributing to their relatively low AI maturity—including legal and regulatory challenges, inadequate AI infrastructure and a shortage of AI-trained workers.", "attrs": null, "canon": { "kind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "5f2affc0-941d-4d07-959d-4bfc1930cea4", "version": 1, "description": "Single prose block in the body of a slide." }, "tool": null, "subkind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "019de52c-fb80-75af-aa5c-a7a4bfac2433", "version": 1, "description": null }, "framework": null }, "subkind": "paragraph", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:49:07.307+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "fd3e5987-9bc2-4a8a-8722-d6d28b52bb6e", "parentComponentId": null }, { "bbox": { "h": 0.02, "w": 0.15, "x": 0.528, "y": 0.855 }, "kind": "source-note", "text": "Source: Accenture Research", "attrs": null, "canon": { "kind": { "name": "Source note", "slug": "source-note", "status": "active", "canonId": "23484952-494b-4a5e-b1ad-550d0d70e948", "version": 1, "description": "Attribution / source / caveat placed at the slide footer. Numbered footnotes use attrs.numbered." }, "tool": null, "subkind": null, "framework": null }, "subkind": null, "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:49:07.307+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "d3c6d972-1e08-4bc0-bb4f-4a089087c6cf", "parentComponentId": null }, { "bbox": { "h": 0.035, "w": 0.143, "x": 0.058, "y": 0.128 }, "kind": "title", "text": "AI, applied", "attrs": null, "canon": { "kind": { "name": "Title", "slug": "title", "status": "active", "canonId": "019de52c-f7dd-76d9-b848-b1f12bd85cf4", "version": 1, "description": "Slide title or headline." }, "tool": null, "subkind": { "name": "Headline", "slug": "headline", "status": "active", "canonId": "019de52c-fae1-7463-9a7c-d60668eced0d", "version": 1, "description": null }, "framework": null }, "subkind": "headline", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:49:07.307+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "7f9088d2-14b2-4d2f-b6ca-5a9d364cd1af", "parentComponentId": null } ], "metrics": [ { "metricRaw": "Median AI Maturity (0-100)", "numberRaw": "60", "numberKind": "plain", "actionTitle": null, "calloutText": "While industries like tech are currently far ahead in their respective AI maturity, the gap will likely narrow considerably by 2024.", "numberScale": null, "numberValue": 60, "metricFamily": "other", "numberCurrency": null } ], "tools": [ { "tool": { "name": "Action Titles", "slug": "action-titles", "status": "active", "bestFor": "Any decision-grade deliverable — strategy recommendation, board update, investment memo, M&A review, post-mortem — where the reader is being asked to agree, decide, or act and will skim the title bar at speed.", "canonId": "019dd956-ac70-700b-a608-ba58e78f5dcc", "version": 1, "bodyDocId": "816dad3c-9983-41c1-a86e-978ebd582841", "description": "The McKinsey-bred discipline of writing every slide title as a complete declarative sentence with a verb and an insight, not a topic label. Each title is a sub-claim that ladders up to the deck's governing thought; read in sequence, the titles reconstruct the executive summary.", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Architect", "layer": "slide", "agents": [ "Architect" ], "matchId": "019dd95a-0f08-73d3-987c-b13f84edd1c0", "evidence": "Subhead asserts gap will narrow by 2024.", "pageRefs": null, "priority": "Core", "whenToUse": "Any decision-grade deliverable — strategy recommendation, board update, investment memo, M&A review, post-mortem — where the reader is being asked to agree, decide, or act and will skim the title bar at speed.", "confidence": 65, "extraction": { "at": "2026-04-29 13:07:31.336924+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 12, "whyItWorks": "Solves two failure modes at once. (1) The buried claim: action titles place the conclusion on the page before any analysis is read, so a busy reader doesn't reverse-engineer it from the chart. (2) The spineless deck: because each title is a claim, slides have to ladder up to the governing thought; logical gaps become visible as topic-shaped titles in a sequence that no longer reads as a story.", "antipattern": "Topic labels disguised as titles — Volume by quarter, Key findings, Pricing strategy, Margins have been impacted. No verb, or a passive verb with no agent, or a fact (Revenue grew 12%) without the so-what. Also: titles that overreach the chart's evidence, multi-claim X-grew-but-Y-fell welded titles, and mechanical repetition of the same X-drove-Y template across the deck.", "cardinality": null, "narrativePurpose": "Forces the deck to carry its argument in the title bar so a senior reader can extract the recommendation without opening a single slide; converts a binder of topics into a navigable pyramid where every slide is a node defending the apex." }, { "tool": { "name": "Audience Definition", "slug": "audience-definition", "status": "active", "bestFor": null, "canonId": "019dd956-7f2a-775d-aeee-ff099bcb7756", "version": 1, "bodyDocId": null, "description": "Six key questions: Who are they? What do they know? What do they believe? What do they care about? What do they fear? What decisions can they make?", "familyLabel": null, "categoryName": "Block", "categorySlug": "block" }, "agent": "Storyteller", "layer": "slide", "agents": [ "Storyteller" ], "matchId": "42de0fc3-5228-40e2-89ef-1f53718199c6", "evidence": "The slide mentions 'industries like tech are currently far ahead in their respective AI maturity' implying a consideration of the audience's industry perspective.", "pageRefs": null, "priority": "Core", "whenToUse": null, "confidence": 0.7, "extraction": { "at": "2026-07-16 21:02:29.954701+00", "model": "or:meta-llama/llama-4-scout", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 12, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "Chart Selection Guide", "slug": "chart-selection-guide", "status": "active", "bestFor": null, "canonId": "019dd956-b1a0-700b-ba17-0e16c4d5bcae", "version": 1, "bodyDocId": null, "description": "Choosing the right chart type for your data and message", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Designer", "layer": "slide", "agents": [ "Designer" ], "matchId": "019dd95a-0f08-73d3-987c-ba2aee4088c2", "evidence": "Industry comparison chart shows current vs 2024 spread.", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 65, "extraction": { "at": "2026-04-29 13:07:31.336924+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 12, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "Concrete Language", "slug": "concrete-language", "status": "active", "bestFor": null, "canonId": "019dd956-bcd4-7398-9723-6aa72346170b", "version": 1, "bodyDocId": null, "description": "Using specific sensory details instead of abstract terms", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Storyteller", "layer": "slide", "agents": [ "Storyteller" ], "matchId": "019dd95a-0f08-73d3-987c-b55ac48404c7", "evidence": "Industry-level maturity scores quoted (e.g. '60').", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 70, "extraction": { "at": "2026-04-29 13:07:31.336924+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 12, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null } ], "frameworks": [ { "matchId": "5b97fe21-6bb3-465b-a20a-0d2619218219", "evidence": "The chart tracks the evolution of AI maturity scores over time across industries.", "framework": null, "confidence": 0.9, "extraction": { "at": "2026-05-02 19:49:07.307+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 12, "frameworkName": "maturity-model" } ], "arcBeats": [ { "to": 13, "arc": { "name": "The Consultant's Gambit", "slug": "consultants-gambit", "status": "active", "bestFor": "Business cases, project proposals, strategic recommendations", "canonId": "019dd956-5e0a-73c8-b305-81c38c959e9c", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "Situation & Context -> Problem & Complication -> Solution & Approach -> Evidence & Proof -> Impact & Next Steps", "description": null, "familyLabel": null }, "from": 9, "name": "Problem & Complication", "beatId": "019dd95a-0682-776c-8e32-8d747bbd76a7", "matchId": "019dd95a-0542-7728-a78e-666792080e8f", "beatType": { "name": "Problem & Complication", "slug": "consultants-gambit-problem-complication", "status": "active", "canonId": "019dd9b8-064a-777f-a374-e9a8c43dedd4", "version": 1, "description": null }, "evidence": "AI maturity defined; only 7% qualify as Achievers (Fig 3 2x2).", "position": 2, "isPrimaryArc": true, "parentBeatType": { "name": "Complication", "slug": "complication", "status": "active", "canonId": "019dd9b8-0275-7709-b2d6-4f77c3fc7579", "version": 1, "description": "The point in the narrative where the audience should feel discomfort. Required for argumentative arcs." }, "alignedBlockIds": null, "matchConfidence": 88 }, { "to": 13, "arc": { "name": "The Triple Take", "slug": "triple-take", "status": "active", "bestFor": "Data-driven presentations, research findings", "canonId": "019dd956-6221-73ad-bc12-378f8eb1f018", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "The Facts (What) -> The Implications (So What) -> The Action (Now What)", "description": null, "familyLabel": null }, "from": 3, "name": "The Facts (What)", "beatId": "019dd95a-0682-776c-8e32-9ee324fcf070", "matchId": "019dd95a-0542-7728-a78e-68cfbfb51150", "beatType": { "name": "The Facts (What)", "slug": "triple-take-the-facts-what", "status": "active", "canonId": "019dd9b8-092b-754c-8eaa-ede3ffdcb060", "version": 1, "description": null }, "evidence": "AI adoption stats and segmentation of the 2,000-firm sample.", "position": 1, "isPrimaryArc": false, "parentBeatType": { "name": "Setup", "slug": "setup", "status": "active", "canonId": "019dd9b8-020e-7505-af9b-d9b9a4679bcc", "version": 1, "description": "Where the deck grounds the reader before doing anything else. Almost every arc opens here." }, "alignedBlockIds": null, "matchConfidence": 60 } ], "loops": [ { "to": 13, "from": 10, "loop": { "name": "30_2x2_matrix", "slug": "30-2x2-matrix", "status": "active", "bestFor": "Portfolio analysis, prioritization, strategic positioning", "canonId": "019dd956-7225-756a-9cc7-1e6d3f039818", "version": 1, "bodyDocId": "019df22a-2420-77be-bc41-ded96d08cb21", "structure": "Dimension 1 (X-axis) -> Dimension 2 (Y-axis) -> The Four Quadrants -> The Sweet Spot", "description": "Plot options on two critical dimensions to reveal the optimal quadrant", "familyLabel": null }, "matchId": "019dd95a-07fe-70ce-8d3a-5987e0314b42", "evidence": "Fig 3 2x2 with axes AI Foundation/Differentiation defines Achievers/Innovators/Builders/Experimenters.", "position": 3, "objective": "Segment firms via the AI Foundation x Differentiation 2x2", "confidence": 92, "extraction": { "at": "2026-04-29 13:07:29.547081+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null } } ], "locked": true }, { "page": 13, "type": "evidence", "function": "illustrate_case", "rawType": "client_example", "block": null, "metadata": { "slideType": "client_example", "slideTypeCanon": { "name": "Client example", "slug": "client_example", "status": "active", "canonId": "019de52d-0c87-77cb-9867-613ae22e95ac", "version": 1, "description": null }, "function": "illustrate_case", "functionCanon": { "name": "Illustrate case", "slug": "illustrate_case", "status": "active", "canonId": "019de52d-13b4-772c-bb73-1873612a7463", "version": 1, "description": null }, "density": "overcrowded", "densityScore": 87, "componentCount": 9, "textChars": 2153, "nDataPoints": 4, "notes": null, "elementsJson": [ "headline_text", "bullet_list", "paragraph", "footnote" ], "confidence": 1, "extraction": { "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "at": "2026-05-02 19:49:13.221+00", "seconds": 9.08, "promptVersion": "v2-canon-conditioned" } }, "links": { "slide": "/slides/019dd923-5ca1-7489-b633-7fa84bbf490b/13", "deck": "/decks/019dd923-5ca1-7489-b633-7fa84bbf490b", "deckAnchor": "/decks/019dd923-5ca1-7489-b633-7fa84bbf490b#slide-13", "deckJson": "/decks/019dd923-5ca1-7489-b633-7fa84bbf490b.json" }, "components": [ { "bbox": null, "kind": "callout", "text": "During the COVID-19 pandemic, a major apparel company's e-commerce business grew rapidly—it now makes up more than 50% of their total revenue, up from 15%.", "attrs": null, "canon": { "kind": { "name": "Callout", "slug": "callout", "status": "active", "canonId": "019de52c-f8d3-761a-8953-7d37080de5e2", "version": 1, "description": "Highlighted callout box." }, "tool": { "name": "Visual emphasis", "slug": "visual-emphasis", "status": "active", "bestFor": null, "canonId": "019dd9e1-474b-736b-a8eb-a794dd88241c", "version": 1, "bodyDocId": null, "description": "Drawing the eye to one element above the rest of the slide.", "familyLabel": null }, "subkind": null, "framework": null }, "subkind": null, "groupRole": null, "confidence": null, "extraction": { "at": "2026-04-23 22:41:55+00", "model": "claude-code-default", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "019dd951-9f64-72ba-b3fd-d701edd0d838", "parentComponentId": null }, { "bbox": { "h": 0.222, "w": 0.215, "x": 0.516, "y": 0.201 }, "kind": "list", "text": "A leading US utility company is using AI to deploy zero-emission vehicles to mitigate the effect of climate change and pollution, and meet their sustainability goals. With a cloud-based digital twin model and AI-driven insights, the firm can determine the highest-emitting vehicles in specific communities and then recommend zero-emission vehicle replacements.", "attrs": null, "canon": { "kind": { "name": "List", "slug": "list", "status": "active", "canonId": "019de52c-f94b-779b-a53b-fd4904a5f4d2", "version": 1, "description": "Bullet or numbered list." }, "tool": null, "subkind": { "name": "Bullet list", "slug": "bullet", "status": "active", "canonId": "019de52c-fc98-7169-a083-5cab805076ca", "version": 1, "description": null }, "framework": null }, "subkind": "bullet", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:49:13.221+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "060d8abd-d4bb-4f79-ad8c-a6a5923b309b", "parentComponentId": null }, { "bbox": { "h": 0.111, "w": 0.215, "x": 0.287, "y": 0.505 }, "kind": "list", "text": "A major US-based beverage bottler used AI to consolidate data sources and measure the effect of promotions on different retailers and markets, boosting the bottler's annual sales by 3%.", "attrs": null, "canon": { "kind": { "name": "List", "slug": "list", "status": "active", "canonId": "019de52c-f94b-779b-a53b-fd4904a5f4d2", "version": 1, "description": "Bullet or numbered list." }, "tool": null, "subkind": { "name": "Bullet list", "slug": "bullet", "status": "active", "canonId": "019de52c-fc98-7169-a083-5cab805076ca", "version": 1, "description": null }, "framework": null }, "subkind": "bullet", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:49:13.221+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "0ebfe09e-9972-44b5-be20-280449bf14e0", "parentComponentId": null }, { "bbox": { "h": 0.222, "w": 0.215, "x": 0.058, "y": 0.423 }, "kind": "list", "text": "A leading solar-panel installer is using satellite photos and deep-learning algorithms to create fully automated rooftop installation plans and price estimates. In addition to offering end customers an industry-first ability to self-design their systems, the company expects its AI-led design efforts to ultimately lower the firm's sales costs by 25%.", "attrs": null, "canon": { "kind": { "name": "List", "slug": "list", "status": "active", "canonId": "019de52c-f94b-779b-a53b-fd4904a5f4d2", "version": 1, "description": "Bullet or numbered list." }, "tool": null, "subkind": { "name": "Bullet list", "slug": "bullet", "status": "active", "canonId": "019de52c-fc98-7169-a083-5cab805076ca", "version": 1, "description": null }, "framework": null }, "subkind": "bullet", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:49:13.221+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "106fb654-76b6-4bef-8210-c05f9264b624", "parentComponentId": null }, { "bbox": { "h": 0.185, "w": 0.215, "x": 0.058, "y": 0.201 }, "kind": "list", "text": "A large chemicals and energy firm is using drones and AI-powered surveillance to monitor its equipment and remote locations. The upshot: More frequent inspections at lower cost to the company and fewer safety risks for its maintenance workers.", "attrs": null, "canon": { "kind": { "name": "List", "slug": "list", "status": "active", "canonId": "019de52c-f94b-779b-a53b-fd4904a5f4d2", "version": 1, "description": "Bullet or numbered list." }, "tool": null, "subkind": { "name": "Bullet list", "slug": "bullet", "status": "active", "canonId": "019de52c-fc98-7169-a083-5cab805076ca", "version": 1, "description": null }, "framework": null }, "subkind": "bullet", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:49:13.221+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "2304dea8-0280-404e-b8b3-4c2b6d7bd355", "parentComponentId": null }, { "bbox": { "h": 0.259, "w": 0.215, "x": 0.745, "y": 0.201 }, "kind": "list", "text": "A large social services organization based in the US used AI to better understand the factors affecting the flow-through rates of their programs and take informed decisions on housing funding distribution and youth allocation. An AI-based digital twin process engine was used to execute simulations in different scenarios and generate actionable insights, which helped them develop a strategy and make housing available for the most vulnerable people in the society.", "attrs": null, "canon": { "kind": { "name": "List", "slug": "list", "status": "active", "canonId": "019de52c-f94b-779b-a53b-fd4904a5f4d2", "version": 1, "description": "Bullet or numbered list." }, "tool": null, "subkind": { "name": "Bullet list", "slug": "bullet", "status": "active", "canonId": "019de52c-fc98-7169-a083-5cab805076ca", "version": 1, "description": null }, "framework": null }, "subkind": "bullet", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:49:13.221+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "2435a260-a2a0-4abd-bc3a-91d7f867207a", "parentComponentId": null }, { "bbox": { "h": 0.185, "w": 0.215, "x": 0.287, "y": 0.201 }, "kind": "list", "text": "During the COVID-19 pandemic, a major apparel company's e-commerce business grew rapidly—it now makes up more than 50% of their total revenue, up from 15%. They used AI to drive a 60% improvement and reduction in split shipments. They added millions annually to the bottom line and improved the customer experience.", "attrs": null, "canon": { "kind": { "name": "List", "slug": "list", "status": "active", "canonId": "019de52c-f94b-779b-a53b-fd4904a5f4d2", "version": 1, "description": "Bullet or numbered list." }, "tool": null, "subkind": { "name": "Bullet list", "slug": "bullet", "status": "active", "canonId": "019de52c-fc98-7169-a083-5cab805076ca", "version": 1, "description": null }, "framework": null }, "subkind": "bullet", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:49:13.221+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "c217c81e-61ab-4eaf-816a-cf85d190da7a", "parentComponentId": null }, { "bbox": null, "kind": "metric", "text": "sales cost reduction (solar-panel installer): 25%", "attrs": null, "canon": { "kind": { "name": "Metric", "slug": "metric", "status": "active", "canonId": "019de52c-f923-73bf-8081-d0b1a8c5264d", "version": 1, "description": "Big-number or KPI value." }, "tool": { "name": "Quantification", "slug": "quantification", "status": "active", "bestFor": null, "canonId": "019dd9e1-47ab-72ce-a079-aab1f5299e88", "version": 1, "bodyDocId": null, "description": "Translating a claim into numbers, charts, or tables.", "familyLabel": null }, "subkind": null, "framework": null }, "subkind": "primary", "groupRole": null, "confidence": null, "extraction": { "at": "2026-04-23 22:41:55+00", "model": "claude-code-default", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "019dd951-9f64-72ba-b3fd-d81c2f6df968", "parentComponentId": null }, { "bbox": { "h": 0.058, "w": 0.354, "x": 0.058, "y": 0.125 }, "kind": "title", "text": "AI, applied across industries", "attrs": null, "canon": { "kind": { "name": "Title", "slug": "title", "status": "active", "canonId": "019de52c-f7dd-76d9-b848-b1f12bd85cf4", "version": 1, "description": "Slide title or headline." }, "tool": null, "subkind": { "name": "Headline", "slug": "headline", "status": "active", "canonId": "019de52c-fae1-7463-9a7c-d60668eced0d", "version": 1, "description": null }, "framework": null }, "subkind": "headline", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:49:13.221+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "4e97c1e8-78ef-42c3-a4ae-5597d912399e", "parentComponentId": null } ], "metrics": [ { "metricRaw": "sales cost reduction (solar-panel installer)", "numberRaw": "25%", "numberKind": "percent", "actionTitle": null, "calloutText": "During the COVID-19 pandemic, a major apparel company's e-commerce business grew rapidly—it now makes up more than 50% of their total revenue, up from 15%.", "numberScale": null, "numberValue": 25, "metricFamily": "cost_savings", "numberCurrency": null } ], "tools": [ { "tool": { "name": "Storytelling Effect", "slug": "storytelling-effect", "status": "active", "bestFor": null, "canonId": "019dd956-981b-74f9-9096-5c8df03dab5a", "version": 1, "bodyDocId": null, "description": "Stories are remembered up to 22x better than facts alone", "familyLabel": null, "categoryName": "Block", "categorySlug": "block" }, "agent": "Storyteller", "layer": "block", "agents": [ "Storyteller" ], "matchId": "019dd95a-0f08-73d3-987c-c8442947cc38", "evidence": "First in a sequence of company vignettes used as memory hooks.", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 70, "extraction": { "at": "2026-04-29 13:07:31.336924+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 13, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "Concrete Language", "slug": "concrete-language", "status": "active", "bestFor": null, "canonId": "019dd956-bcd4-7398-9723-6aa72346170b", "version": 1, "bodyDocId": null, "description": "Using specific sensory details instead of abstract terms", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Storyteller", "layer": "slide", "agents": [ "Storyteller" ], "matchId": "019dd95a-0f08-73d3-987c-c0826c15065a", "evidence": "Callout: '50% of revenue, up from 15%'.", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 80, "extraction": { "at": "2026-04-29 13:07:31.336924+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 13, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "Singularity Effect", "slug": "singularity-effect", "status": "active", "bestFor": null, "canonId": "019dd956-dcd3-7287-94d8-5a49496c2ddb", "version": 1, "bodyDocId": null, "description": "People care more about individuals than statistics - use specific examples", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Storyteller", "layer": "slide", "agents": [ "Storyteller" ], "matchId": "019dd95a-0f08-73d3-987c-c73f24089782", "evidence": "Single named retailer humanizes the industry-trend abstraction.", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 70, "extraction": { "at": "2026-04-29 13:07:31.336924+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 13, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "Story Moments", "slug": "story-moments", "status": "active", "bestFor": null, "canonId": "019dd956-ae4e-768d-a18b-108e6cda511e", "version": 1, "bodyDocId": null, "description": "Design key emotional beats: The Shock, The Vision, The Proof, The Choice, The Call", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Storyteller", "layer": "slide", "agents": [ "Storyteller" ], "matchId": "019dd95a-0f08-73d3-987c-be69e7a13427", "evidence": "Apparel COVID e-commerce case as a concrete win moment.", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 75, "extraction": { "at": "2026-04-29 13:07:31.336924+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 13, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "Story Moments", "slug": "story-moments", "status": "active", "bestFor": null, "canonId": "019dd956-ae4e-768d-a18b-108e6cda511e", "version": 1, "bodyDocId": null, "description": "Design key emotional beats: The Shock, The Vision, The Proof, The Choice, The Call", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Storyteller", "layer": "slide", "agents": [ "Storyteller" ], "matchId": "bb51670d-5835-4349-bf77-e57f77fa229a", "evidence": "The slide provides various examples of companies using AI, which are storytelling moments.", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 0.6, "extraction": { "at": "2026-07-16 21:02:30.026549+00", "model": "or:meta-llama/llama-4-scout", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 13, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null } ], "frameworks": [], "arcBeats": [ { "to": 13, "arc": { "name": "The Consultant's Gambit", "slug": "consultants-gambit", "status": "active", "bestFor": "Business cases, project proposals, strategic recommendations", "canonId": "019dd956-5e0a-73c8-b305-81c38c959e9c", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "Situation & Context -> Problem & Complication -> Solution & Approach -> Evidence & Proof -> Impact & Next Steps", "description": null, "familyLabel": null }, "from": 9, "name": "Problem & Complication", "beatId": "019dd95a-0682-776c-8e32-8d747bbd76a7", "matchId": "019dd95a-0542-7728-a78e-666792080e8f", "beatType": { "name": "Problem & Complication", "slug": "consultants-gambit-problem-complication", "status": "active", "canonId": "019dd9b8-064a-777f-a374-e9a8c43dedd4", "version": 1, "description": null }, "evidence": "AI maturity defined; only 7% qualify as Achievers (Fig 3 2x2).", "position": 2, "isPrimaryArc": true, "parentBeatType": { "name": "Complication", "slug": "complication", "status": "active", "canonId": "019dd9b8-0275-7709-b2d6-4f77c3fc7579", "version": 1, "description": "The point in the narrative where the audience should feel discomfort. Required for argumentative arcs." }, "alignedBlockIds": null, "matchConfidence": 88 }, { "to": 13, "arc": { "name": "The Triple Take", "slug": "triple-take", "status": "active", "bestFor": "Data-driven presentations, research findings", "canonId": "019dd956-6221-73ad-bc12-378f8eb1f018", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "The Facts (What) -> The Implications (So What) -> The Action (Now What)", "description": null, "familyLabel": null }, "from": 3, "name": "The Facts (What)", "beatId": "019dd95a-0682-776c-8e32-9ee324fcf070", "matchId": "019dd95a-0542-7728-a78e-68cfbfb51150", "beatType": { "name": "The Facts (What)", "slug": "triple-take-the-facts-what", "status": "active", "canonId": "019dd9b8-092b-754c-8eaa-ede3ffdcb060", "version": 1, "description": null }, "evidence": "AI adoption stats and segmentation of the 2,000-firm sample.", "position": 1, "isPrimaryArc": false, "parentBeatType": { "name": "Setup", "slug": "setup", "status": "active", "canonId": "019dd9b8-020e-7505-af9b-d9b9a4679bcc", "version": 1, "description": "Where the deck grounds the reader before doing anything else. Almost every arc opens here." }, "alignedBlockIds": null, "matchConfidence": 60 } ], "loops": [ { "to": 13, "from": 10, "loop": { "name": "30_2x2_matrix", "slug": "30-2x2-matrix", "status": "active", "bestFor": "Portfolio analysis, prioritization, strategic positioning", "canonId": "019dd956-7225-756a-9cc7-1e6d3f039818", "version": 1, "bodyDocId": "019df22a-2420-77be-bc41-ded96d08cb21", "structure": "Dimension 1 (X-axis) -> Dimension 2 (Y-axis) -> The Four Quadrants -> The Sweet Spot", "description": "Plot options on two critical dimensions to reveal the optimal quadrant", "familyLabel": null }, "matchId": "019dd95a-07fe-70ce-8d3a-5987e0314b42", "evidence": "Fig 3 2x2 with axes AI Foundation/Differentiation defines Achievers/Innovators/Builders/Experimenters.", "position": 3, "objective": "Segment firms via the AI Foundation x Differentiation 2x2", "confidence": 92, "extraction": { "at": "2026-04-29 13:07:29.547081+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null } } ], "locked": true }, { "page": 14, "type": "setup", "title": "The slide uses a high-impact visual of ballet dancers to metaphorically represent the transition from 'practice' to 'performance' in the context of AI maturity.", "function": "transition", "rawType": "transition", "block": null, "metadata": { "slideType": "transition", "slideTypeCanon": { "name": "Transition", "slug": "transition", "status": "active", "canonId": "019de52d-0693-7766-9f05-887f41f8e41e", "version": 1, "description": null }, "function": "transition", "functionCanon": { "name": "Transition", "slug": "transition", "status": "active", "canonId": "019de52d-1365-7149-92aa-66df859e75fd", "version": 1, "description": null }, "density": "sparse", "densityScore": 7, "componentCount": 3, "textChars": 71, "nDataPoints": 0, "notes": "The slide uses a high-impact visual of ballet dancers to metaphorically represent the transition from 'practice' to 'performance' in the context of AI maturity.", "elementsJson": [ "headline_text", "action_title", "photo" ], "confidence": 1, "extraction": { "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "at": "2026-05-02 19:49:09.268+00", "seconds": 5.061, "promptVersion": "v2-canon-conditioned" } }, "links": { "slide": "/slides/019dd923-5ca1-7489-b633-7fa84bbf490b/14", "deck": "/decks/019dd923-5ca1-7489-b633-7fa84bbf490b", "deckAnchor": "/decks/019dd923-5ca1-7489-b633-7fa84bbf490b#slide-14", "deckJson": "/decks/019dd923-5ca1-7489-b633-7fa84bbf490b.json" }, "components": [ { "bbox": { "h": 1, "w": 1, "x": 0, "y": 0 }, "kind": "image", "text": null, "attrs": null, "canon": { "kind": { "name": "Image", "slug": "image", "status": "active", "canonId": "019de52c-f978-701f-a720-51d029d769e7", "version": 1, "description": "Photo, illustration, screenshot or icon." }, "tool": null, "subkind": { "name": "Photo", "slug": "photo", "status": "active", "canonId": "019de52c-fd37-757f-b4a8-ca26d4888875", "version": 1, "description": null }, "framework": null }, "subkind": "photo", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:49:09.268+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "47788d0a-02f3-4199-bc23-32b4a501caf1", "parentComponentId": null }, { "bbox": { "h": 0.166, "w": 0.622, "x": 0.189, "y": 0.418 }, "kind": "title", "text": "AI Achievers advance from practice to performance", "attrs": null, "canon": { "kind": { "name": "Title", "slug": "title", "status": "active", "canonId": "019de52c-f7dd-76d9-b848-b1f12bd85cf4", "version": 1, "description": "Slide title or headline." }, "tool": null, "subkind": { "name": "Action title", "slug": "action-title", "status": "active", "canonId": "019de52c-fb31-734c-a0f5-a3935b73135d", "version": 1, "description": null }, "framework": null }, "subkind": "action-title", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:49:09.268+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "be90f9d3-0e98-439d-908f-352ac0082c75", "parentComponentId": null }, { "bbox": { "h": 0.025, "w": 0.178, "x": 0.058, "y": 0.103 }, "kind": "title", "text": "The art of AI maturity", "attrs": null, "canon": { "kind": { "name": "Title", "slug": "title", "status": "active", "canonId": "019de52c-f7dd-76d9-b848-b1f12bd85cf4", "version": 1, "description": "Slide title or headline." }, "tool": null, "subkind": { "name": "Subtitle", "slug": "subtitle", "status": "active", "canonId": "019de52c-fb09-739d-900c-815b0d9ac526", "version": 1, "description": null }, "framework": null }, "subkind": "subtitle", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:49:09.268+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "6da4b468-68d5-4f76-bcc1-1b5f9211c430", "parentComponentId": null } ], "metrics": [], "tools": [ { "tool": { "name": "Action Titles", "slug": "action-titles", "status": "active", "bestFor": "Any decision-grade deliverable — strategy recommendation, board update, investment memo, M&A review, post-mortem — where the reader is being asked to agree, decide, or act and will skim the title bar at speed.", "canonId": "019dd956-ac70-700b-a608-ba58e78f5dcc", "version": 1, "bodyDocId": "816dad3c-9983-41c1-a86e-978ebd582841", "description": "The McKinsey-bred discipline of writing every slide title as a complete declarative sentence with a verb and an insight, not a topic label. Each title is a sub-claim that ladders up to the deck's governing thought; read in sequence, the titles reconstruct the executive summary.", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Architect", "layer": "slide", "agents": [ "Architect" ], "matchId": "0aa14a4f-52cc-45e8-b497-7a785f330330", "evidence": "The slide has a clear action title: 'AI Achievers advance from practice to performance'.", "pageRefs": null, "priority": "Core", "whenToUse": "Any decision-grade deliverable — strategy recommendation, board update, investment memo, M&A review, post-mortem — where the reader is being asked to agree, decide, or act and will skim the title bar at speed.", "confidence": 0.9, "extraction": { "at": "2026-07-16 21:02:30.091851+00", "model": "or:meta-llama/llama-4-scout", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 14, "whyItWorks": "Solves two failure modes at once. (1) The buried claim: action titles place the conclusion on the page before any analysis is read, so a busy reader doesn't reverse-engineer it from the chart. (2) The spineless deck: because each title is a claim, slides have to ladder up to the governing thought; logical gaps become visible as topic-shaped titles in a sequence that no longer reads as a story.", "antipattern": "Topic labels disguised as titles — Volume by quarter, Key findings, Pricing strategy, Margins have been impacted. No verb, or a passive verb with no agent, or a fact (Revenue grew 12%) without the so-what. Also: titles that overreach the chart's evidence, multi-claim X-grew-but-Y-fell welded titles, and mechanical repetition of the same X-drove-Y template across the deck.", "cardinality": null, "narrativePurpose": "Forces the deck to carry its argument in the title bar so a senior reader can extract the recommendation without opening a single slide; converts a binder of topics into a navigable pyramid where every slide is a node defending the apex." } ], "frameworks": [], "arcBeats": [ { "to": 17, "arc": { "name": "The Consultant's Gambit", "slug": "consultants-gambit", "status": "active", "bestFor": "Business cases, project proposals, strategic recommendations", "canonId": "019dd956-5e0a-73c8-b305-81c38c959e9c", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "Situation & Context -> Problem & Complication -> Solution & Approach -> Evidence & Proof -> Impact & Next Steps", "description": null, "familyLabel": null }, "from": 14, "name": "Evidence & Proof", "beatId": "019dd95a-0682-776c-8e32-901ded58915f", "matchId": "019dd95a-0542-7728-a78e-666792080e8f", "beatType": { "name": "Solution & Approach", "slug": "consultants-gambit-solution-approach", "status": "active", "canonId": "019dd9b8-071c-7161-9184-580fdac7a4f9", "version": 1, "description": null }, "evidence": "Achievers enjoy 50% greater revenue growth, scale pilots more, lead on sustainability.", "position": 3, "isPrimaryArc": true, "parentBeatType": { "name": "Turn", "slug": "turn", "status": "active", "canonId": "019dd9b8-0396-702b-ac2f-9901f8dd8b54", "version": 1, "description": "The pivot — solution proposed, catalyst introduced, decision made. Common (15/20 arcs) but not universal: Triple-take, AIDA, PAS, Voyage-return and Pixar substitute it with a strong reflection or development beat." }, "alignedBlockIds": null, "matchConfidence": 88 }, { "to": 17, "arc": { "name": "The Triple Take", "slug": "triple-take", "status": "active", "bestFor": "Data-driven presentations, research findings", "canonId": "019dd956-6221-73ad-bc12-378f8eb1f018", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "The Facts (What) -> The Implications (So What) -> The Action (Now What)", "description": null, "familyLabel": null }, "from": 14, "name": "The Implications (So What)", "beatId": "019dd95a-0682-776c-8e32-a1d6fecab517", "matchId": "019dd95a-0542-7728-a78e-68cfbfb51150", "beatType": { "name": "The Implications (So What)", "slug": "triple-take-the-implications-so-what", "status": "active", "canonId": "019dd9b8-09c7-75cd-8c7b-ae0e23cca2b8", "version": 1, "description": null }, "evidence": "Achievers outperform peers on revenue and sustainability.", "position": 2, "isPrimaryArc": false, "parentBeatType": { "name": "Reflection", "slug": "reflection", "status": "active", "canonId": "019dd9b8-0510-73fd-8d00-1c7e45f7bc98", "version": 1, "description": "The \"so what\" beat. Used by analytical arcs (Triple-take, Onion) and learning arcs (Voyage-return, Tragedy)." }, "alignedBlockIds": null, "matchConfidence": 60 } ], "loops": [], "locked": true }, { "page": 15, "type": "setup", "title": "The chart uses a matrix of colored squares to indicate performance levels across four categories: Strategy and Sponsorship, Data and AI Core, Talent and Culture", "function": "compare_peers", "rawType": "comparison_table", "block": null, "metadata": { "slideType": "comparison_table", "slideTypeCanon": { "name": "Comparison table", "slug": "comparison_table", "status": "active", "canonId": "019de52d-0a06-73f8-8813-fe022fab1de2", "version": 1, "description": null }, "function": "compare_peers", "functionCanon": { "name": "Compare peers", "slug": "compare_peers", "status": "active", "canonId": "019de52d-1453-72ba-a367-9ba3d34c1630", "version": 1, "description": null }, "density": "overcrowded", "densityScore": 85, "componentCount": 9, "textChars": 927, "nDataPoints": 68, "notes": "The chart uses a matrix of colored squares to indicate performance levels across four categories: Strategy and Sponsorship, Data and AI Core, Talent and Culture, and Responsible AI.", "elementsJson": [ "action_title", "subtitle_text", "paragraph", "heatmap", "footnote" ], "confidence": 1, "extraction": { "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "at": "2026-05-02 19:49:08.583+00", "seconds": 3.944, "promptVersion": "v2-canon-conditioned" } }, "links": { "slide": "/slides/019dd923-5ca1-7489-b633-7fa84bbf490b/15", "deck": "/decks/019dd923-5ca1-7489-b633-7fa84bbf490b", "deckAnchor": "/decks/019dd923-5ca1-7489-b633-7fa84bbf490b#slide-15", "deckJson": "/decks/019dd923-5ca1-7489-b633-7fa84bbf490b.json" }, "components": [ { "bbox": null, "kind": "callout", "text": "Pre-pandemic (2019), AI achievers globally already enjoyed 50% greater revenue growth, on average, versus their peers.", "attrs": null, "canon": { "kind": { "name": "Callout", "slug": "callout", "status": "active", "canonId": "019de52c-f8d3-761a-8953-7d37080de5e2", "version": 1, "description": "Highlighted callout box." }, "tool": { "name": "Visual emphasis", "slug": "visual-emphasis", "status": "active", "bestFor": null, "canonId": "019dd9e1-474b-736b-a8eb-a794dd88241c", "version": 1, "bodyDocId": null, "description": "Drawing the eye to one element above the rest of the slide.", "familyLabel": null }, "subkind": null, "framework": null }, "subkind": null, "groupRole": null, "confidence": null, "extraction": { "at": "2026-04-23 22:42:01+00", "model": "claude-code-default", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "019dd951-9f64-72ba-b3fd-f46495d99c51", "parentComponentId": null }, { "bbox": { "h": 0.65, "w": 0.43, "x": 0.52, "y": 0.13 }, "kind": "chart", "text": "Figure 5: AI Achievers outperform in nearly all capabilities", "attrs": null, "canon": { "kind": { "name": "Chart", "slug": "chart", "status": "active", "canonId": "019de52c-f9a0-76ef-adc6-0b859109d1f8", "version": 1, "description": "Quantitative chart." }, "tool": null, "subkind": { "name": "Heatmap", "slug": "heatmap", "status": "active", "canonId": "019de52d-00cd-71ee-bf36-233b7817c304", "version": 1, "description": null }, "framework": null }, "subkind": "heatmap", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:49:08.583+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "b47f31ba-1f8e-4339-a610-a86c0fe41333", "parentComponentId": null }, { "bbox": { "h": 0.05, "w": 0.43, "x": 0.52, "y": 0.82 }, "kind": "disclaimer", "text": "Note: Each cube represents one of the 17 key capabilities. The cube is highlighted when the AI profile is outperforming against peers.", "attrs": null, "canon": { "kind": { "name": "Disclaimer", "slug": "disclaimer", "status": "active", "canonId": "91173477-d91f-4024-bbaf-d4f93e3f82dc", "version": 1, "description": "Legal/cautionary text that occupies most of the body of its slide." }, "tool": null, "subkind": null, "framework": null }, "subkind": null, "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:49:08.583+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "019a9bc1-aef4-413f-b6e4-9360c66571df", "parentComponentId": null }, { "bbox": null, "kind": "metric", "text": "AI Achievers revenue growth vs peers (pre-pandemic): 50%", "attrs": null, "canon": { "kind": { "name": "Metric", "slug": "metric", "status": "active", "canonId": "019de52c-f923-73bf-8081-d0b1a8c5264d", "version": 1, "description": "Big-number or KPI value." }, "tool": { "name": "Quantification", "slug": "quantification", "status": "active", "bestFor": null, "canonId": "019dd9e1-47ab-72ce-a079-aab1f5299e88", "version": 1, "bodyDocId": null, "description": "Translating a claim into numbers, charts, or tables.", "familyLabel": null }, "subkind": null, "framework": null }, "subkind": "primary", "groupRole": null, "confidence": null, "extraction": { "at": "2026-04-23 22:42:01+00", "model": "claude-code-default", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "019dd951-9f64-72ba-b3fd-fbacf1ea26ca", "parentComponentId": null }, { "bbox": { "h": 0.25, "w": 0.2, "x": 0.28, "y": 0.32 }, "kind": "paragraph", "text": "Mastery of multitasking: When compared with all other groups, AI Achievers demonstrate high performance by combining strengths across strategy, processes and people.", "attrs": null, "canon": { "kind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "5f2affc0-941d-4d07-959d-4bfc1930cea4", "version": 1, "description": "Single prose block in the body of a slide." }, "tool": null, "subkind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "019de52c-fb80-75af-aa5c-a7a4bfac2433", "version": 1, "description": null }, "framework": null }, "subkind": "paragraph", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:49:08.583+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "052f5d0d-4a24-42e2-b29a-4c8e479459bb", "parentComponentId": null }, { "bbox": { "h": 0.15, "w": 0.2, "x": 0.06, "y": 0.32 }, "kind": "paragraph", "text": "Pre-pandemic (2019), AI achievers globally already enjoyed 50% greater revenue growth, on average, versus their peers. And today, they're 3.5 times more likely than Experimenters to see their AI-influenced revenue surpass 30% of their total revenues.", "attrs": null, "canon": { "kind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "5f2affc0-941d-4d07-959d-4bfc1930cea4", "version": 1, "description": "Single prose block in the body of a slide." }, "tool": null, "subkind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "019de52c-fb80-75af-aa5c-a7a4bfac2433", "version": 1, "description": null }, "framework": null }, "subkind": "paragraph", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:49:08.583+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "1617da10-6808-49f4-baf4-4c9864abffd0", "parentComponentId": null }, { "bbox": { "h": 0.02, "w": 0.15, "x": 0.52, "y": 0.79 }, "kind": "source-note", "text": "Source: Accenture Research", "attrs": null, "canon": { "kind": { "name": "Source note", "slug": "source-note", "status": "active", "canonId": "23484952-494b-4a5e-b1ad-550d0d70e948", "version": 1, "description": "Attribution / source / caveat placed at the slide footer. Numbered footnotes use attrs.numbered." }, "tool": null, "subkind": null, "framework": null }, "subkind": null, "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:49:08.583+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "ac408a36-c62c-4774-94a0-96786e0f3100", "parentComponentId": null }, { "bbox": { "h": 0.06, "w": 0.4, "x": 0.06, "y": 0.23 }, "kind": "title", "text": "AI Achievers thrive when it comes to traditional performance metrics.", "attrs": null, "canon": { "kind": { "name": "Title", "slug": "title", "status": "active", "canonId": "019de52c-f7dd-76d9-b848-b1f12bd85cf4", "version": 1, "description": "Slide title or headline." }, "tool": null, "subkind": { "name": "Action title", "slug": "action-title", "status": "active", "canonId": "019de52c-fb31-734c-a0f5-a3935b73135d", "version": 1, "description": null }, "framework": null }, "subkind": "action-title", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:49:08.583+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "35fb9289-fd56-44c6-a9a4-6964236adc98", "parentComponentId": null }, { "bbox": { "h": 0.08, "w": 0.4, "x": 0.06, "y": 0.13 }, "kind": "title", "text": "AI Achievers advance from practice to performance", "attrs": null, "canon": { "kind": { "name": "Title", "slug": "title", "status": "active", "canonId": "019de52c-f7dd-76d9-b848-b1f12bd85cf4", "version": 1, "description": "Slide title or headline." }, "tool": null, "subkind": { "name": "Headline", "slug": "headline", "status": "active", "canonId": "019de52c-fae1-7463-9a7c-d60668eced0d", "version": 1, "description": null }, "framework": null }, "subkind": "headline", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:49:08.583+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "6772c00a-e5c7-4681-8d64-4257d2529183", "parentComponentId": null } ], "metrics": [ { "metricRaw": "AI Achievers revenue growth vs peers (pre-pandemic)", "numberRaw": "50%", "numberKind": "percent", "actionTitle": "AI Achievers advance from practice to performance", "calloutText": "Pre-pandemic (2019), AI achievers globally already enjoyed 50% greater revenue growth, on average, versus their peers.", "numberScale": null, "numberValue": 50, "metricFamily": "growth_rate", "numberCurrency": null } ], "tools": [ { "tool": { "name": "Contrast Pairs", "slug": "contrast-pairs", "status": "active", "bestFor": null, "canonId": "019dd956-9b77-70d3-88b1-f34e26f60860", "version": 1, "bodyDocId": null, "description": "Creating tension through opposites: Before↔After, Problem↔Solution, Pain↔Relief", "familyLabel": null, "categoryName": "Loop", "categorySlug": "loop" }, "agent": "Storyteller", "layer": "loop", "agents": [ "Storyteller" ], "matchId": "019dd95a-0f08-73d3-987c-de5beef91744", "evidence": "Sets up Achievers<->Experimenters contrast that drives the loop.", "pageRefs": null, "priority": "Core", "whenToUse": null, "confidence": 80, "extraction": { "at": "2026-04-29 13:07:31.336924+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 15, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "Data Story Arc", "slug": "data-story-arc", "status": "active", "bestFor": null, "canonId": "019dd956-9c30-728e-b974-d3fb123dcf5a", "version": 1, "bodyDocId": null, "description": "Context → Conflict → Insight → Implication structure for data narratives", "familyLabel": null, "categoryName": "Loop", "categorySlug": "loop" }, "agent": "Storyteller", "layer": "loop", "agents": [ "Storyteller" ], "matchId": "019dd95a-0f08-73d3-987c-e02a57d87b3b", "evidence": "Opens benchmarking arc: context, conflict (gap), insight.", "pageRefs": null, "priority": "Core", "whenToUse": null, "confidence": 70, "extraction": { "at": "2026-04-29 13:07:31.336924+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 15, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "2x2 matrix", "slug": "matrix-2x2", "status": "active", "bestFor": null, "canonId": "019dd9e1-50ab-72d1-8afb-3ab0a38e32a8", "version": 1, "bodyDocId": null, "description": "BCG matrix, importance/urgency, any axes-and-quadrants frame.", "familyLabel": null, "categoryName": null, "categorySlug": null }, "agent": null, "layer": "slide", "agents": null, "matchId": "3a3ab2cd-8202-4133-a522-e8cd6a6a4957", "evidence": "Although not a traditional 2x2 matrix, the slide compares AI achievers with other groups in a tabular format.", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 0.5, "extraction": { "at": "2026-07-16 21:02:30.154103+00", "model": "or:meta-llama/llama-4-scout", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 15, "whyItWorks": null, "antipattern": null, "cardinality": "common", "narrativePurpose": null }, { "tool": { "name": "Action Titles", "slug": "action-titles", "status": "active", "bestFor": "Any decision-grade deliverable — strategy recommendation, board update, investment memo, M&A review, post-mortem — where the reader is being asked to agree, decide, or act and will skim the title bar at speed.", "canonId": "019dd956-ac70-700b-a608-ba58e78f5dcc", "version": 1, "bodyDocId": "816dad3c-9983-41c1-a86e-978ebd582841", "description": "The McKinsey-bred discipline of writing every slide title as a complete declarative sentence with a verb and an insight, not a topic label. Each title is a sub-claim that ladders up to the deck's governing thought; read in sequence, the titles reconstruct the executive summary.", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Architect", "layer": "slide", "agents": [ "Architect" ], "matchId": "019dd95a-0f08-73d3-987c-cdcbb07e9173", "evidence": "'AI Achievers advance from practice to performance' states the verdict.", "pageRefs": null, "priority": "Core", "whenToUse": "Any decision-grade deliverable — strategy recommendation, board update, investment memo, M&A review, post-mortem — where the reader is being asked to agree, decide, or act and will skim the title bar at speed.", "confidence": 85, "extraction": { "at": "2026-04-29 13:07:31.336924+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 15, "whyItWorks": "Solves two failure modes at once. (1) The buried claim: action titles place the conclusion on the page before any analysis is read, so a busy reader doesn't reverse-engineer it from the chart. (2) The spineless deck: because each title is a claim, slides have to ladder up to the governing thought; logical gaps become visible as topic-shaped titles in a sequence that no longer reads as a story.", "antipattern": "Topic labels disguised as titles — Volume by quarter, Key findings, Pricing strategy, Margins have been impacted. No verb, or a passive verb with no agent, or a fact (Revenue grew 12%) without the so-what. Also: titles that overreach the chart's evidence, multi-claim X-grew-but-Y-fell welded titles, and mechanical repetition of the same X-drove-Y template across the deck.", "cardinality": null, "narrativePurpose": "Forces the deck to carry its argument in the title bar so a senior reader can extract the recommendation without opening a single slide; converts a binder of topics into a navigable pyramid where every slide is a node defending the apex." }, { "tool": { "name": "Color Strategy", "slug": "color-strategy", "status": "active", "bestFor": null, "canonId": "019dd956-b202-77cf-8a6e-f445b08c0fd3", "version": 1, "bodyDocId": null, "description": "Using color for emphasis, categories, sentiment, and hierarchy", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Designer", "layer": "slide", "agents": [ "Designer" ], "matchId": "019dd95a-0f08-73d3-987c-d94bba45a13e", "evidence": "Filled vs hollow squares encode out- vs under-performing.", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 75, "extraction": { "at": "2026-04-29 13:07:31.336924+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 15, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "Concrete Language", "slug": "concrete-language", "status": "active", "bestFor": null, "canonId": "019dd956-bcd4-7398-9723-6aa72346170b", "version": 1, "bodyDocId": null, "description": "Using specific sensory details instead of abstract terms", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Storyteller", "layer": "slide", "agents": [ "Storyteller" ], "matchId": "019dd95a-0f08-73d3-987c-d0da7fb84ca7", "evidence": "'50% greater revenue growth' anchors the gap.", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 85, "extraction": { "at": "2026-04-29 13:07:31.336924+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 15, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "Small Multiples", "slug": "small-multiples", "status": "active", "bestFor": null, "canonId": "019dd956-b32d-7586-b368-baa1dd388ed4", "version": 1, "bodyDocId": null, "description": "Repeating similar charts for comparison across categories or time", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Designer", "layer": "slide", "agents": [ "Designer" ], "matchId": "019dd95a-0f08-73d3-987c-d6417e7a8a19", "evidence": "Fig 5 grid of 17 capabilities x 4 archetypes for at-a-glance compare.", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 85, "extraction": { "at": "2026-04-29 13:07:31.336924+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 15, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null } ], "frameworks": [ { "matchId": "019dd95a-1ca5-70bb-bb9f-57dbefdb2e6f", "evidence": "17 capabilities x 4 archetypes grid with filled/hollow performance markers.", "framework": null, "confidence": 80, "extraction": { "at": "2026-04-29 13:07:34.826634+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 15, "frameworkName": "Capability Heatmap" }, { "matchId": "fdb3c76e-c57c-48f3-8dbd-1913fd5752f4", "evidence": "Categorization of AI profiles (Achievers, Builders, Innovators, Experimenters) across capabilities", "framework": null, "confidence": 0.9, "extraction": { "at": "2026-05-02 19:49:08.583+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 15, "frameworkName": "maturity-model" } ], "arcBeats": [ { "to": 17, "arc": { "name": "The Consultant's Gambit", "slug": "consultants-gambit", "status": "active", "bestFor": "Business cases, project proposals, strategic recommendations", "canonId": "019dd956-5e0a-73c8-b305-81c38c959e9c", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "Situation & Context -> Problem & Complication -> Solution & Approach -> Evidence & Proof -> Impact & Next Steps", "description": null, "familyLabel": null }, "from": 14, "name": "Evidence & Proof", "beatId": "019dd95a-0682-776c-8e32-901ded58915f", "matchId": "019dd95a-0542-7728-a78e-666792080e8f", "beatType": { "name": "Solution & Approach", "slug": "consultants-gambit-solution-approach", "status": "active", "canonId": "019dd9b8-071c-7161-9184-580fdac7a4f9", "version": 1, "description": null }, "evidence": "Achievers enjoy 50% greater revenue growth, scale pilots more, lead on sustainability.", "position": 3, "isPrimaryArc": true, "parentBeatType": { "name": "Turn", "slug": "turn", "status": "active", "canonId": "019dd9b8-0396-702b-ac2f-9901f8dd8b54", "version": 1, "description": "The pivot — solution proposed, catalyst introduced, decision made. Common (15/20 arcs) but not universal: Triple-take, AIDA, PAS, Voyage-return and Pixar substitute it with a strong reflection or development beat." }, "alignedBlockIds": null, "matchConfidence": 88 }, { "to": 17, "arc": { "name": "The Triple Take", "slug": "triple-take", "status": "active", "bestFor": "Data-driven presentations, research findings", "canonId": "019dd956-6221-73ad-bc12-378f8eb1f018", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "The Facts (What) -> The Implications (So What) -> The Action (Now What)", "description": null, "familyLabel": null }, "from": 14, "name": "The Implications (So What)", "beatId": "019dd95a-0682-776c-8e32-a1d6fecab517", "matchId": "019dd95a-0542-7728-a78e-68cfbfb51150", "beatType": { "name": "The Implications (So What)", "slug": "triple-take-the-implications-so-what", "status": "active", "canonId": "019dd9b8-09c7-75cd-8c7b-ae0e23cca2b8", "version": 1, "description": null }, "evidence": "Achievers outperform peers on revenue and sustainability.", "position": 2, "isPrimaryArc": false, "parentBeatType": { "name": "Reflection", "slug": "reflection", "status": "active", "canonId": "019dd9b8-0510-73fd-8d00-1c7e45f7bc98", "version": 1, "description": "The \"so what\" beat. Used by analytical arcs (Triple-take, Onion) and learning arcs (Voyage-return, Tragedy)." }, "alignedBlockIds": null, "matchConfidence": 60 } ], "loops": [ { "to": 17, "from": 15, "loop": { "name": "39_benchmark_gap", "slug": "39-benchmark-gap", "status": "active", "bestFor": "Performance improvement, competitive analysis, target setting", "canonId": "019dd956-75a4-7522-8d1a-af94da4703e9", "version": 1, "bodyDocId": "019df22a-2420-77be-bc41-ded96d08cb21", "structure": "Our Performance -> Industry Average -> Best-in-Class -> The Gap = The Opportunity", "description": "Compare performance against best-in-class to quantify the opportunity", "familyLabel": null }, "matchId": "019dd95a-07fe-70ce-8d3a-5d3edf07f6fa", "evidence": "50% greater revenue growth, 5% more likely to scale pilots, capability matrix vs peers.", "position": 4, "objective": "Quantify the performance gap between Achievers and others", "confidence": 85, "extraction": { "at": "2026-04-29 13:07:29.547081+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null } } ], "locked": true }, { "page": 16, "type": "evidence", "title": "The chart is a dot plot comparing 'NA Achievers' and 'NA Experimenters' across various business functions.", "function": "illustrate_case", "rawType": "case_study", "block": null, "metadata": { "slideType": "case_study", "slideTypeCanon": { "name": "Case study", "slug": "case_study", "status": "active", "canonId": "019de52d-0b95-7344-8090-926f3b8e92c8", "version": 1, "description": null }, "function": "illustrate_case", "functionCanon": { "name": "Illustrate case", "slug": "illustrate_case", "status": "active", "canonId": "019de52d-13b4-772c-bb73-1873612a7463", "version": 1, "description": null }, "density": "overcrowded", "densityScore": 77, "componentCount": 8, "textChars": 829, "nDataPoints": 24, "notes": "The chart is a dot plot comparing 'NA Achievers' and 'NA Experimenters' across various business functions.", "elementsJson": [ "headline_text", "action_title", "paragraph", "scatter_plot", "footnote" ], "confidence": 1, "extraction": { "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "at": "2026-05-02 19:49:07.826+00", "seconds": 3.065, "promptVersion": "v2-canon-conditioned" } }, "links": { "slide": "/slides/019dd923-5ca1-7489-b633-7fa84bbf490b/16", "deck": "/decks/019dd923-5ca1-7489-b633-7fa84bbf490b", "deckAnchor": "/decks/019dd923-5ca1-7489-b633-7fa84bbf490b#slide-16", "deckJson": "/decks/019dd923-5ca1-7489-b633-7fa84bbf490b.json" }, "components": [ { "bbox": null, "kind": "callout", "text": "Achievers in North America are 5% more likely to scale AI pilots across the enterprise compared with Experimenters.", "attrs": null, "canon": { "kind": { "name": "Callout", "slug": "callout", "status": "active", "canonId": "019de52c-f8d3-761a-8953-7d37080de5e2", "version": 1, "description": "Highlighted callout box." }, "tool": { "name": "Visual emphasis", "slug": "visual-emphasis", "status": "active", "bestFor": null, "canonId": "019dd9e1-474b-736b-a8eb-a794dd88241c", "version": 1, "bodyDocId": null, "description": "Drawing the eye to one element above the rest of the slide.", "familyLabel": null }, "subkind": null, "framework": null }, "subkind": null, "groupRole": null, "confidence": null, "extraction": { "at": "2026-04-23 22:42:06+00", "model": "claude-code-default", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "019dd951-9f64-72ba-b3fe-1bc6edf270ff", "parentComponentId": null }, { "bbox": { "h": 0.7, "w": 0.55, "x": 0.38, "y": 0.12 }, "kind": "chart", "text": "Figure 6: Achievers excel at turning AI pilots into production", "attrs": null, "canon": { "kind": { "name": "Chart", "slug": "chart", "status": "active", "canonId": "019de52c-f9a0-76ef-adc6-0b859109d1f8", "version": 1, "description": "Quantitative chart." }, "tool": null, "subkind": { "name": "Dot plot", "slug": "dot", "status": "active", "canonId": "019de52d-0235-738b-bd2b-78f8e24d7cb0", "version": 1, "description": null }, "framework": null }, "subkind": "dot", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:49:07.826+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "4a703a20-1800-447d-93fe-fec23b9605f6", "parentComponentId": null }, { "bbox": { "h": 0.08, "w": 0.55, "x": 0.38, "y": 0.77 }, "kind": "disclaimer", "text": "Note: Score 0-100, ranging from 0 = AI use case not started, 50 = AI use in early stage, 100 = having AI programs in place for full productization.", "attrs": null, "canon": { "kind": { "name": "Disclaimer", "slug": "disclaimer", "status": "active", "canonId": "91173477-d91f-4024-bbaf-d4f93e3f82dc", "version": 1, "description": "Legal/cautionary text that occupies most of the body of its slide." }, "tool": null, "subkind": null, "framework": null }, "subkind": null, "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:49:07.826+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "84dbf48e-7e24-4c00-9781-d2f2a9c3a0f1", "parentComponentId": null }, { "bbox": null, "kind": "metric", "text": "Average AI productization score (Achievers vs Experimenters): 60 vs 44", "attrs": null, "canon": { "kind": { "name": "Metric", "slug": "metric", "status": "active", "canonId": "019de52c-f923-73bf-8081-d0b1a8c5264d", "version": 1, "description": "Big-number or KPI value." }, "tool": { "name": "Quantification", "slug": "quantification", "status": "active", "bestFor": null, "canonId": "019dd9e1-47ab-72ce-a079-aab1f5299e88", "version": 1, "bodyDocId": null, "description": "Translating a claim into numbers, charts, or tables.", "familyLabel": null }, "subkind": null, "framework": null }, "subkind": "primary", "groupRole": null, "confidence": null, "extraction": { "at": "2026-04-23 22:42:06+00", "model": "claude-code-default", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "019dd951-9f64-72ba-b3fe-1ea9194017b5", "parentComponentId": null }, { "bbox": { "h": 0.1, "w": 0.3, "x": 0.05, "y": 0.18 }, "kind": "paragraph", "text": "Achievers have largely moved beyond the AI investment “tipping point,” going from experimenting with new AI in isolation to applying AI at scale to solve critical business problems (Figure 6).", "attrs": null, "canon": { "kind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "5f2affc0-941d-4d07-959d-4bfc1930cea4", "version": 1, "description": "Single prose block in the body of a slide." }, "tool": null, "subkind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "019de52c-fb80-75af-aa5c-a7a4bfac2433", "version": 1, "description": null }, "framework": null }, "subkind": "paragraph", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:49:07.826+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "06fcaa26-93ff-4c79-aacf-b55ded64d13f", "parentComponentId": null }, { "bbox": { "h": 0.25, "w": 0.3, "x": 0.05, "y": 0.35 }, "kind": "paragraph", "text": "Take product development as an example: Procter & Gamble (P&G) uses “explainable AI” algorithms to harness its proprietary data and formulation models, and recommend product improvements.", "attrs": null, "canon": { "kind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "5f2affc0-941d-4d07-959d-4bfc1930cea4", "version": 1, "description": "Single prose block in the body of a slide." }, "tool": null, "subkind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "019de52c-fb80-75af-aa5c-a7a4bfac2433", "version": 1, "description": null }, "framework": null }, "subkind": "paragraph", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:49:07.826+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "7e8804d4-f2b3-48f1-af55-675c0c0af491", "parentComponentId": null }, { "bbox": { "h": 0.02, "w": 0.15, "x": 0.38, "y": 0.74 }, "kind": "source-note", "text": "Source: Accenture Research", "attrs": null, "canon": { "kind": { "name": "Source note", "slug": "source-note", "status": "active", "canonId": "23484952-494b-4a5e-b1ad-550d0d70e948", "version": 1, "description": "Attribution / source / caveat placed at the slide footer. Numbered footnotes use attrs.numbered." }, "tool": null, "subkind": null, "framework": null }, "subkind": null, "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:49:07.826+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "a5a5f657-4c9e-45d5-8344-9b159afd1271", "parentComponentId": null }, { "bbox": { "h": 0.03, "w": 0.3, "x": 0.05, "y": 0.12 }, "kind": "title", "text": "Turning pilots into production", "attrs": null, "canon": { "kind": { "name": "Title", "slug": "title", "status": "active", "canonId": "019de52c-f7dd-76d9-b848-b1f12bd85cf4", "version": 1, "description": "Slide title or headline." }, "tool": null, "subkind": { "name": "Headline", "slug": "headline", "status": "active", "canonId": "019de52c-fae1-7463-9a7c-d60668eced0d", "version": 1, "description": null }, "framework": null }, "subkind": "headline", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:49:07.826+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "8e43ece3-e88c-4384-b2d7-18d2e04bfbaa", "parentComponentId": null } ], "metrics": [ { "metricRaw": "Average AI productization score (Achievers vs Experimenters)", "numberRaw": "60 vs 44", "numberKind": "plain", "actionTitle": "Turning pilots into production", "calloutText": "Achievers in North America are 5% more likely to scale AI pilots across the enterprise compared with Experimenters.", "numberScale": null, "numberValue": 60, "metricFamily": "index_score", "numberCurrency": null } ], "tools": [ { "tool": { "name": "Action Titles", "slug": "action-titles", "status": "active", "bestFor": "Any decision-grade deliverable — strategy recommendation, board update, investment memo, M&A review, post-mortem — where the reader is being asked to agree, decide, or act and will skim the title bar at speed.", "canonId": "019dd956-ac70-700b-a608-ba58e78f5dcc", "version": 1, "bodyDocId": "816dad3c-9983-41c1-a86e-978ebd582841", "description": "The McKinsey-bred discipline of writing every slide title as a complete declarative sentence with a verb and an insight, not a topic label. Each title is a sub-claim that ladders up to the deck's governing thought; read in sequence, the titles reconstruct the executive summary.", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Architect", "layer": "slide", "agents": [ "Architect" ], "matchId": "019dd95a-0f08-73d3-987c-e487f368a7d7", "evidence": "Title 'Turning pilots into production' delivers a verb-led message.", "pageRefs": null, "priority": "Core", "whenToUse": "Any decision-grade deliverable — strategy recommendation, board update, investment memo, M&A review, post-mortem — where the reader is being asked to agree, decide, or act and will skim the title bar at speed.", "confidence": 80, "extraction": { "at": "2026-04-29 13:07:31.336924+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 16, "whyItWorks": "Solves two failure modes at once. (1) The buried claim: action titles place the conclusion on the page before any analysis is read, so a busy reader doesn't reverse-engineer it from the chart. (2) The spineless deck: because each title is a claim, slides have to ladder up to the governing thought; logical gaps become visible as topic-shaped titles in a sequence that no longer reads as a story.", "antipattern": "Topic labels disguised as titles — Volume by quarter, Key findings, Pricing strategy, Margins have been impacted. No verb, or a passive verb with no agent, or a fact (Revenue grew 12%) without the so-what. Also: titles that overreach the chart's evidence, multi-claim X-grew-but-Y-fell welded titles, and mechanical repetition of the same X-drove-Y template across the deck.", "cardinality": null, "narrativePurpose": "Forces the deck to carry its argument in the title bar so a senior reader can extract the recommendation without opening a single slide; converts a binder of topics into a navigable pyramid where every slide is a node defending the apex." }, { "tool": { "name": "Concrete Language", "slug": "concrete-language", "status": "active", "bestFor": null, "canonId": "019dd956-bcd4-7398-9723-6aa72346170b", "version": 1, "bodyDocId": null, "description": "Using specific sensory details instead of abstract terms", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Storyteller", "layer": "slide", "agents": [ "Storyteller" ], "matchId": "019dd95a-0f08-73d3-987c-eadf6e1a1063", "evidence": "60 vs 44 scale-rate, 5% more likely to scale.", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 80, "extraction": { "at": "2026-04-29 13:07:31.336924+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 16, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null } ], "frameworks": [], "arcBeats": [ { "to": 17, "arc": { "name": "The Consultant's Gambit", "slug": "consultants-gambit", "status": "active", "bestFor": "Business cases, project proposals, strategic recommendations", "canonId": "019dd956-5e0a-73c8-b305-81c38c959e9c", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "Situation & Context -> Problem & Complication -> Solution & Approach -> Evidence & Proof -> Impact & Next Steps", "description": null, "familyLabel": null }, "from": 14, "name": "Evidence & Proof", "beatId": "019dd95a-0682-776c-8e32-901ded58915f", "matchId": "019dd95a-0542-7728-a78e-666792080e8f", "beatType": { "name": "Solution & Approach", "slug": "consultants-gambit-solution-approach", "status": "active", "canonId": "019dd9b8-071c-7161-9184-580fdac7a4f9", "version": 1, "description": null }, "evidence": "Achievers enjoy 50% greater revenue growth, scale pilots more, lead on sustainability.", "position": 3, "isPrimaryArc": true, "parentBeatType": { "name": "Turn", "slug": "turn", "status": "active", "canonId": "019dd9b8-0396-702b-ac2f-9901f8dd8b54", "version": 1, "description": "The pivot — solution proposed, catalyst introduced, decision made. Common (15/20 arcs) but not universal: Triple-take, AIDA, PAS, Voyage-return and Pixar substitute it with a strong reflection or development beat." }, "alignedBlockIds": null, "matchConfidence": 88 }, { "to": 17, "arc": { "name": "The Triple Take", "slug": "triple-take", "status": "active", "bestFor": "Data-driven presentations, research findings", "canonId": "019dd956-6221-73ad-bc12-378f8eb1f018", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "The Facts (What) -> The Implications (So What) -> The Action (Now What)", "description": null, "familyLabel": null }, "from": 14, "name": "The Implications (So What)", "beatId": "019dd95a-0682-776c-8e32-a1d6fecab517", "matchId": "019dd95a-0542-7728-a78e-68cfbfb51150", "beatType": { "name": "The Implications (So What)", "slug": "triple-take-the-implications-so-what", "status": "active", "canonId": "019dd9b8-09c7-75cd-8c7b-ae0e23cca2b8", "version": 1, "description": null }, "evidence": "Achievers outperform peers on revenue and sustainability.", "position": 2, "isPrimaryArc": false, "parentBeatType": { "name": "Reflection", "slug": "reflection", "status": "active", "canonId": "019dd9b8-0510-73fd-8d00-1c7e45f7bc98", "version": 1, "description": "The \"so what\" beat. Used by analytical arcs (Triple-take, Onion) and learning arcs (Voyage-return, Tragedy)." }, "alignedBlockIds": null, "matchConfidence": 60 } ], "loops": [ { "to": 17, "from": 15, "loop": { "name": "39_benchmark_gap", "slug": "39-benchmark-gap", "status": "active", "bestFor": "Performance improvement, competitive analysis, target setting", "canonId": "019dd956-75a4-7522-8d1a-af94da4703e9", "version": 1, "bodyDocId": "019df22a-2420-77be-bc41-ded96d08cb21", "structure": "Our Performance -> Industry Average -> Best-in-Class -> The Gap = The Opportunity", "description": "Compare performance against best-in-class to quantify the opportunity", "familyLabel": null }, "matchId": "019dd95a-07fe-70ce-8d3a-5d3edf07f6fa", "evidence": "50% greater revenue growth, 5% more likely to scale pilots, capability matrix vs peers.", "position": 4, "objective": "Quantify the performance gap between Achievers and others", "confidence": 85, "extraction": { "at": "2026-04-29 13:07:29.547081+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null } } ], "locked": true }, { "page": 17, "type": "resolution", "title": "The slide uses a three-column layout to present qualitative insights and supporting data points regarding customer experience and sustainability.", "function": "summarize", "rawType": "key_takeaways", "block": null, "metadata": { "slideType": "key_takeaways", "slideTypeCanon": { "name": "Key takeaways", "slug": "key_takeaways", "status": "active", "canonId": "019de52d-06e7-7674-a891-9f7de3b11b6d", "version": 1, "description": null }, "function": "summarize", "functionCanon": { "name": "Summarize", "slug": "summarize", "status": "active", "canonId": "019de52d-1541-704f-b86f-bf7b75056373", "version": 1, "description": null }, "density": "dense", "densityScore": 74, "componentCount": 7, "textChars": 1780, "nDataPoints": 3, "notes": "The slide uses a three-column layout to present qualitative insights and supporting data points regarding customer experience and sustainability.", "elementsJson": [ "headline_text", "paragraph", "footnote" ], "confidence": 1, "extraction": { "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "at": "2026-05-02 19:49:07.806+00", "seconds": 2.992, "promptVersion": "v2-canon-conditioned" } }, "links": { "slide": "/slides/019dd923-5ca1-7489-b633-7fa84bbf490b/17", "deck": "/decks/019dd923-5ca1-7489-b633-7fa84bbf490b", "deckAnchor": "/decks/019dd923-5ca1-7489-b633-7fa84bbf490b#slide-17", "deckJson": "/decks/019dd923-5ca1-7489-b633-7fa84bbf490b.json" }, "components": [ { "bbox": null, "kind": "callout", "text": "Accenture's Sustainable Technology survey of more than 500 multinational companies found that 70% of firms that managed to reduce emissions from their operations relied on AI to achieve those reductions.", "attrs": null, "canon": { "kind": { "name": "Callout", "slug": "callout", "status": "active", "canonId": "019de52c-f8d3-761a-8953-7d37080de5e2", "version": 1, "description": "Highlighted callout box." }, "tool": { "name": "Visual emphasis", "slug": "visual-emphasis", "status": "active", "bestFor": null, "canonId": "019dd9e1-474b-736b-a8eb-a794dd88241c", "version": 1, "bodyDocId": null, "description": "Drawing the eye to one element above the rest of the slide.", "familyLabel": null }, "subkind": null, "framework": null }, "subkind": null, "groupRole": null, "confidence": null, "extraction": { "at": "2026-04-23 22:42:06+00", "model": "claude-code-default", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "019dd951-9f64-72ba-b3fe-3544555eabcf", "parentComponentId": null }, { "bbox": null, "kind": "metric", "text": "Achievers' customer experience lead over Experimenters: 8%", "attrs": null, "canon": { "kind": { "name": "Metric", "slug": "metric", "status": "active", "canonId": "019de52c-f923-73bf-8081-d0b1a8c5264d", "version": 1, "description": "Big-number or KPI value." }, "tool": { "name": "Quantification", "slug": "quantification", "status": "active", "bestFor": null, "canonId": "019dd9e1-47ab-72ce-a079-aab1f5299e88", "version": 1, "bodyDocId": null, "description": "Translating a claim into numbers, charts, or tables.", "familyLabel": null }, "subkind": null, "framework": null }, "subkind": "primary", "groupRole": null, "confidence": null, "extraction": { "at": "2026-04-23 22:42:06+00", "model": "claude-code-default", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "019dd951-9f64-72ba-b3fe-38e2b467db79", "parentComponentId": null }, { "bbox": { "h": 0.5, "w": 0.28, "x": 0.05, "y": 0.2 }, "kind": "paragraph", "text": "Achievers also develop strong relationships with customers—by building trust, reducing churn and boosting the quality and safety of offerings. Our stakeholder performance model showed with high statistical significance that Achievers score 8% higher than Experimenters on customer experience (see Appendix for more on methodology). Additionally, they double down on their commitment to sustainability by, for instance, rigorously measuring and reducing their greenhouse gas emissions, consuming water and other natural resources more economically, and using AI responsibly.", "attrs": null, "canon": { "kind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "5f2affc0-941d-4d07-959d-4bfc1930cea4", "version": 1, "description": "Single prose block in the body of a slide." }, "tool": null, "subkind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "019de52c-fb80-75af-aa5c-a7a4bfac2433", "version": 1, "description": null }, "framework": null }, "subkind": "paragraph", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:49:07.806+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "736d9eda-8b7f-4626-9499-66d379a98f1a", "parentComponentId": null }, { "bbox": { "h": 0.03, "w": 0.2, "x": 0.03, "y": 0.95 }, "kind": "paragraph", "text": "The art of AI maturity - North America", "attrs": null, "canon": { "kind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "5f2affc0-941d-4d07-959d-4bfc1930cea4", "version": 1, "description": "Single prose block in the body of a slide." }, "tool": null, "subkind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "019de52c-fb80-75af-aa5c-a7a4bfac2433", "version": 1, "description": null }, "framework": null }, "subkind": "paragraph", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:49:07.806+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "a1687208-bb55-4d7d-8257-5dc4631e7cdc", "parentComponentId": null }, { "bbox": { "h": 0.7, "w": 0.28, "x": 0.36, "y": 0.2 }, "kind": "paragraph", "text": "Accenture’s Sustainable Technology survey of more than 500 multinational companies found that 70% of firms that managed to reduce emissions from their operations relied on AI to achieve those reductions. Likewise, AI was a key tool for 75% of the surveyed companies that made strides in measuring and disclosing their carbon footprints more transparently. One US-based utility company conducts remote monitoring of its extensive grid infrastructure via satellites, drones and other surveillance tools. With the help of advanced analytics, machine learning and computer vision, the company can quickly identify and prioritize areas for maintenance, improve public safety and better mitigate its scope 1 and scope 2 emissions.", "attrs": null, "canon": { "kind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "5f2affc0-941d-4d07-959d-4bfc1930cea4", "version": 1, "description": "Single prose block in the body of a slide." }, "tool": null, "subkind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "019de52c-fb80-75af-aa5c-a7a4bfac2433", "version": 1, "description": null }, "framework": null }, "subkind": "paragraph", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:49:07.806+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "ecb28bef-073f-49cd-9ac9-178c432cc30c", "parentComponentId": null }, { "bbox": { "h": 0.2, "w": 0.25, "x": 0.67, "y": 0.2 }, "kind": "paragraph", "text": "The stakeholder performance model revealed the value-creation gap between Achievers and other companies is significant when it comes to sustainability.", "attrs": null, "canon": { "kind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "5f2affc0-941d-4d07-959d-4bfc1930cea4", "version": 1, "description": "Single prose block in the body of a slide." }, "tool": null, "subkind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "019de52c-fb80-75af-aa5c-a7a4bfac2433", "version": 1, "description": null }, "framework": null }, "subkind": "paragraph", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:49:07.806+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "f0ade4cc-f2a1-41d3-a275-d26329d8c584", "parentComponentId": null }, { "bbox": { "h": 0.05, "w": 0.4, "x": 0.05, "y": 0.12 }, "kind": "title", "text": "Focusing beyond financial metrics", "attrs": null, "canon": { "kind": { "name": "Title", "slug": "title", "status": "active", "canonId": "019de52c-f7dd-76d9-b848-b1f12bd85cf4", "version": 1, "description": "Slide title or headline." }, "tool": null, "subkind": { "name": "Headline", "slug": "headline", "status": "active", "canonId": "019de52c-fae1-7463-9a7c-d60668eced0d", "version": 1, "description": null }, "framework": null }, "subkind": "headline", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:49:07.806+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "52af798e-3f27-4e39-be94-31e9dedbedaa", "parentComponentId": null } ], "metrics": [ { "metricRaw": "Achievers' customer experience lead over Experimenters", "numberRaw": "8%", "numberKind": "percent", "actionTitle": null, "calloutText": "Accenture's Sustainable Technology survey of more than 500 multinational companies found that 70% of firms that managed to reduce emissions from their operations relied on AI to achieve those reductions.", "numberScale": null, "numberValue": 8, "metricFamily": "other", "numberCurrency": null } ], "tools": [ { "tool": { "name": "Action Titles", "slug": "action-titles", "status": "active", "bestFor": "Any decision-grade deliverable — strategy recommendation, board update, investment memo, M&A review, post-mortem — where the reader is being asked to agree, decide, or act and will skim the title bar at speed.", "canonId": "019dd956-ac70-700b-a608-ba58e78f5dcc", "version": 1, "bodyDocId": "816dad3c-9983-41c1-a86e-978ebd582841", "description": "The McKinsey-bred discipline of writing every slide title as a complete declarative sentence with a verb and an insight, not a topic label. Each title is a sub-claim that ladders up to the deck's governing thought; read in sequence, the titles reconstruct the executive summary.", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Architect", "layer": "slide", "agents": [ "Architect" ], "matchId": "019dd95a-0f08-73d3-987c-ed8f03f70aa3", "evidence": "'Focusing beyond financial metrics' signals the next dimension.", "pageRefs": null, "priority": "Core", "whenToUse": "Any decision-grade deliverable — strategy recommendation, board update, investment memo, M&A review, post-mortem — where the reader is being asked to agree, decide, or act and will skim the title bar at speed.", "confidence": 75, "extraction": { "at": "2026-04-29 13:07:31.336924+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 17, "whyItWorks": "Solves two failure modes at once. (1) The buried claim: action titles place the conclusion on the page before any analysis is read, so a busy reader doesn't reverse-engineer it from the chart. (2) The spineless deck: because each title is a claim, slides have to ladder up to the governing thought; logical gaps become visible as topic-shaped titles in a sequence that no longer reads as a story.", "antipattern": "Topic labels disguised as titles — Volume by quarter, Key findings, Pricing strategy, Margins have been impacted. No verb, or a passive verb with no agent, or a fact (Revenue grew 12%) without the so-what. Also: titles that overreach the chart's evidence, multi-claim X-grew-but-Y-fell welded titles, and mechanical repetition of the same X-drove-Y template across the deck.", "cardinality": null, "narrativePurpose": "Forces the deck to carry its argument in the title bar so a senior reader can extract the recommendation without opening a single slide; converts a binder of topics into a navigable pyramid where every slide is a node defending the apex." }, { "tool": { "name": "Authority Bias", "slug": "authority-bias", "status": "active", "bestFor": null, "canonId": "019dd956-c38d-70b9-a284-b2b479763356", "version": 1, "bodyDocId": null, "description": "Expert opinions are weighted more heavily - cite credible sources", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Storyteller", "layer": "slide", "agents": [ "Architect", "Storyteller" ], "matchId": "019dd95a-0f08-73d3-987c-f7dfed8ecbef", "evidence": "Cites Accenture's Sustainable Technology survey of 500+ multinationals.", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 65, "extraction": { "at": "2026-04-29 13:07:31.336924+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 17, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "Concrete Language", "slug": "concrete-language", "status": "active", "bestFor": null, "canonId": "019dd956-bcd4-7398-9723-6aa72346170b", "version": 1, "bodyDocId": null, "description": "Using specific sensory details instead of abstract terms", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Storyteller", "layer": "slide", "agents": [ "Storyteller" ], "matchId": "019dd95a-0f08-73d3-987c-f263775fabfe", "evidence": "70% reduced emissions via AI; 8% stat in body.", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 80, "extraction": { "at": "2026-04-29 13:07:31.336924+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 17, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null } ], "frameworks": [], "arcBeats": [ { "to": 17, "arc": { "name": "The Consultant's Gambit", "slug": "consultants-gambit", "status": "active", "bestFor": "Business cases, project proposals, strategic recommendations", "canonId": "019dd956-5e0a-73c8-b305-81c38c959e9c", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "Situation & Context -> Problem & Complication -> Solution & Approach -> Evidence & Proof -> Impact & Next Steps", "description": null, "familyLabel": null }, "from": 14, "name": "Evidence & Proof", "beatId": "019dd95a-0682-776c-8e32-901ded58915f", "matchId": "019dd95a-0542-7728-a78e-666792080e8f", "beatType": { "name": "Solution & Approach", "slug": "consultants-gambit-solution-approach", "status": "active", "canonId": "019dd9b8-071c-7161-9184-580fdac7a4f9", "version": 1, "description": null }, "evidence": "Achievers enjoy 50% greater revenue growth, scale pilots more, lead on sustainability.", "position": 3, "isPrimaryArc": true, "parentBeatType": { "name": "Turn", "slug": "turn", "status": "active", "canonId": "019dd9b8-0396-702b-ac2f-9901f8dd8b54", "version": 1, "description": "The pivot — solution proposed, catalyst introduced, decision made. Common (15/20 arcs) but not universal: Triple-take, AIDA, PAS, Voyage-return and Pixar substitute it with a strong reflection or development beat." }, "alignedBlockIds": null, "matchConfidence": 88 }, { "to": 17, "arc": { "name": "The Triple Take", "slug": "triple-take", "status": "active", "bestFor": "Data-driven presentations, research findings", "canonId": "019dd956-6221-73ad-bc12-378f8eb1f018", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "The Facts (What) -> The Implications (So What) -> The Action (Now What)", "description": null, "familyLabel": null }, "from": 14, "name": "The Implications (So What)", "beatId": "019dd95a-0682-776c-8e32-a1d6fecab517", "matchId": "019dd95a-0542-7728-a78e-68cfbfb51150", "beatType": { "name": "The Implications (So What)", "slug": "triple-take-the-implications-so-what", "status": "active", "canonId": "019dd9b8-09c7-75cd-8c7b-ae0e23cca2b8", "version": 1, "description": null }, "evidence": "Achievers outperform peers on revenue and sustainability.", "position": 2, "isPrimaryArc": false, "parentBeatType": { "name": "Reflection", "slug": "reflection", "status": "active", "canonId": "019dd9b8-0510-73fd-8d00-1c7e45f7bc98", "version": 1, "description": "The \"so what\" beat. Used by analytical arcs (Triple-take, Onion) and learning arcs (Voyage-return, Tragedy)." }, "alignedBlockIds": null, "matchConfidence": 60 } ], "loops": [ { "to": 17, "from": 15, "loop": { "name": "39_benchmark_gap", "slug": "39-benchmark-gap", "status": "active", "bestFor": "Performance improvement, competitive analysis, target setting", "canonId": "019dd956-75a4-7522-8d1a-af94da4703e9", "version": 1, "bodyDocId": "019df22a-2420-77be-bc41-ded96d08cb21", "structure": "Our Performance -> Industry Average -> Best-in-Class -> The Gap = The Opportunity", "description": "Compare performance against best-in-class to quantify the opportunity", "familyLabel": null }, "matchId": "019dd95a-07fe-70ce-8d3a-5d3edf07f6fa", "evidence": "50% greater revenue growth, 5% more likely to scale pilots, capability matrix vs peers.", "position": 4, "objective": "Quantify the performance gap between Achievers and others", "confidence": 85, "extraction": { "at": "2026-04-29 13:07:29.547081+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null } } ], "locked": true }, { "page": 18, "type": "setup", "title": "The slide uses a visual metaphor of a DJ mixing music to represent 'mastering the craft' of AI.", "function": "transition", "rawType": "section_divider", "block": null, "metadata": { "slideType": "section_divider", "slideTypeCanon": { "name": "Section divider", "slug": "section_divider", "status": "active", "canonId": "019de52d-066a-7402-9554-6ae504999041", "version": 1, "description": null }, "function": "transition", "functionCanon": { "name": "Transition", "slug": "transition", "status": "active", "canonId": "019de52d-1365-7149-92aa-66df859e75fd", "version": 1, "description": null }, "density": "sparse", "densityScore": 12, "componentCount": 4, "textChars": 92, "nDataPoints": 0, "notes": "The slide uses a visual metaphor of a DJ mixing music to represent 'mastering the craft' of AI.", "elementsJson": [ "headline_text", "subtitle_text", "photo" ], "confidence": 1, "extraction": { "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "at": "2026-05-02 19:49:09.539+00", "seconds": 4.713, "promptVersion": "v2-canon-conditioned" } }, "links": { "slide": "/slides/019dd923-5ca1-7489-b633-7fa84bbf490b/18", "deck": "/decks/019dd923-5ca1-7489-b633-7fa84bbf490b", "deckAnchor": "/decks/019dd923-5ca1-7489-b633-7fa84bbf490b#slide-18", "deckJson": "/decks/019dd923-5ca1-7489-b633-7fa84bbf490b.json" }, "components": [ { "bbox": { "h": 1, "w": 1, "x": 0, "y": 0 }, "kind": "image", "text": "DJ mixing music", "attrs": null, "canon": { "kind": { "name": "Image", "slug": "image", "status": "active", "canonId": "019de52c-f978-701f-a720-51d029d769e7", "version": 1, "description": "Photo, illustration, screenshot or icon." }, "tool": null, "subkind": { "name": "Photo", "slug": "photo", "status": "active", "canonId": "019de52c-fd37-757f-b4a8-ca26d4888875", "version": 1, "description": null }, "framework": null }, "subkind": "photo", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:49:09.539+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "b8b852b8-0377-47b1-bf46-6911ae2ba12a", "parentComponentId": null }, { "bbox": { "h": 0.2, "w": 0.5, "x": 0.25, "y": 0.4 }, "kind": "title", "text": "How AI Achievers master their craft", "attrs": null, "canon": { "kind": { "name": "Title", "slug": "title", "status": "active", "canonId": "019de52c-f7dd-76d9-b848-b1f12bd85cf4", "version": 1, "description": "Slide title or headline." }, "tool": null, "subkind": { "name": "Headline", "slug": "headline", "status": "active", "canonId": "019de52c-fae1-7463-9a7c-d60668eced0d", "version": 1, "description": null }, "framework": null }, "subkind": "headline", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:49:09.539+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "e8b54c49-baba-4642-9c38-e7fe304088c6", "parentComponentId": null }, { "bbox": { "h": 0.05, "w": 0.2, "x": 0.4, "y": 0.6 }, "kind": "title", "text": "Five success factors", "attrs": null, "canon": { "kind": { "name": "Title", "slug": "title", "status": "active", "canonId": "019de52c-f7dd-76d9-b848-b1f12bd85cf4", "version": 1, "description": "Slide title or headline." }, "tool": null, "subkind": { "name": "Subtitle", "slug": "subtitle", "status": "active", "canonId": "019de52c-fb09-739d-900c-815b0d9ac526", "version": 1, "description": null }, "framework": null }, "subkind": "subtitle", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:49:09.539+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "914e9a4a-8d6c-4f3f-83e6-70ef822fd5c3", "parentComponentId": null }, { "bbox": { "h": 0.05, "w": 0.2, "x": 0.05, "y": 0.1 }, "kind": "title", "text": "The art of AI maturity", "attrs": null, "canon": { "kind": { "name": "Title", "slug": "title", "status": "active", "canonId": "019de52c-f7dd-76d9-b848-b1f12bd85cf4", "version": 1, "description": "Slide title or headline." }, "tool": null, "subkind": { "name": "Subtitle", "slug": "subtitle", "status": "active", "canonId": "019de52c-fb09-739d-900c-815b0d9ac526", "version": 1, "description": null }, "framework": null }, "subkind": "subtitle", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:49:09.539+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "fc4bf94a-1b27-4f95-9fb0-0d2c05e2e0f3", "parentComponentId": null } ], "metrics": [], "tools": [ { "tool": { "name": "Section divider", "slug": "section-divider", "status": "active", "bestFor": null, "canonId": "019dd9e1-4c66-707d-8d1f-6e14547134c7", "version": 1, "bodyDocId": null, "description": "A transitional slide marking the start of a new section.", "familyLabel": null, "categoryName": null, "categorySlug": null }, "agent": null, "layer": "slide", "agents": null, "matchId": "48c11967-1810-4ee7-aada-0c9a94accf68", "evidence": "The slide is clearly a section divider with a title and subtitle.", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 0.9, "extraction": { "at": "2026-07-16 21:02:30.282899+00", "model": "or:meta-llama/llama-4-scout", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 18, "whyItWorks": null, "antipattern": null, "cardinality": "common", "narrativePurpose": null } ], "frameworks": [], "arcBeats": [ { "to": 28, "arc": { "name": "The Consultant's Gambit", "slug": "consultants-gambit", "status": "active", "bestFor": "Business cases, project proposals, strategic recommendations", "canonId": "019dd956-5e0a-73c8-b305-81c38c959e9c", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "Situation & Context -> Problem & Complication -> Solution & Approach -> Evidence & Proof -> Impact & Next Steps", "description": null, "familyLabel": null }, "from": 18, "name": "Solution & Approach", "beatId": "019dd95a-0682-776c-8e32-9637b6b2b41d", "matchId": "019dd95a-0542-7728-a78e-666792080e8f", "beatType": { "name": "Evidence & Proof", "slug": "consultants-gambit-evidence-proof", "status": "active", "canonId": "019dd9b8-07b1-7688-8e1e-7637fec3802a", "version": 1, "description": null }, "evidence": "Five success factors: leadership, talent, AI core, responsible AI, investment.", "position": 4, "isPrimaryArc": true, "parentBeatType": { "name": "Evidence", "slug": "evidence", "status": "active", "canonId": "019dd9b8-03f9-772a-b84a-4f07b415b77a", "version": 1, "description": "A dedicated proof beat exists in only ~4 arcs (Gambit, Sequoia, AIDA, Monroes). Other arcs embed evidence inline within development." }, "alignedBlockIds": null, "matchConfidence": 88 }, { "to": 32, "arc": { "name": "The Triple Take", "slug": "triple-take", "status": "active", "bestFor": "Data-driven presentations, research findings", "canonId": "019dd956-6221-73ad-bc12-378f8eb1f018", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "The Facts (What) -> The Implications (So What) -> The Action (Now What)", "description": null, "familyLabel": null }, "from": 18, "name": "The Action (Now What)", "beatId": "019dd95a-0682-776c-8e32-a6c160fdc8c9", "matchId": "019dd95a-0542-7728-a78e-68cfbfb51150", "beatType": { "name": "The Action (Now What)", "slug": "triple-take-the-action-now-what", "status": "active", "canonId": "019dd9b8-0a5e-735a-bf53-3a1ba629b7aa", "version": 1, "description": null }, "evidence": "Five success factors plus C-suite self-assessment.", "position": 3, "isPrimaryArc": false, "parentBeatType": { "name": "Resolution", "slug": "resolution", "status": "active", "canonId": "019dd9b8-045d-703b-8dd7-e92aba3ba91b", "version": 1, "description": "How the deck ends. Required in 19/20 arcs. The exception (Sparkline) ends with new bliss which is functionally a resolution." }, "alignedBlockIds": null, "matchConfidence": 60 } ], "loops": [], "locked": true }, { "page": 19, "type": "setup", "function": "transition", "rawType": "transition", "block": null, "metadata": { "slideType": "transition", "slideTypeCanon": { "name": "Transition", "slug": "transition", "status": "active", "canonId": "019de52d-0693-7766-9f05-887f41f8e41e", "version": 1, "description": null }, "function": "transition", "functionCanon": { "name": "Transition", "slug": "transition", "status": "active", "canonId": "019de52d-1365-7149-92aa-66df859e75fd", "version": 1, "description": null }, "density": "balanced", "densityScore": 32, "componentCount": 4, "textChars": 565, "nDataPoints": 0, "notes": null, "elementsJson": [ "headline_text", "paragraph", "photo" ], "confidence": 1, "extraction": { "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "at": "2026-05-02 19:49:09.698+00", "seconds": 4.742, "promptVersion": "v2-canon-conditioned" } }, "links": { "slide": "/slides/019dd923-5ca1-7489-b633-7fa84bbf490b/19", "deck": "/decks/019dd923-5ca1-7489-b633-7fa84bbf490b", "deckAnchor": "/decks/019dd923-5ca1-7489-b633-7fa84bbf490b#slide-19", "deckJson": "/decks/019dd923-5ca1-7489-b633-7fa84bbf490b.json" }, "components": [ { "bbox": null, "kind": "callout", "text": "high performance today will ultimately become business-as-usual tomorrow.", "attrs": null, "canon": { "kind": { "name": "Callout", "slug": "callout", "status": "active", "canonId": "019de52c-f8d3-761a-8953-7d37080de5e2", "version": 1, "description": "Highlighted callout box." }, "tool": { "name": "Visual emphasis", "slug": "visual-emphasis", "status": "active", "bestFor": null, "canonId": "019dd9e1-474b-736b-a8eb-a794dd88241c", "version": 1, "bodyDocId": null, "description": "Drawing the eye to one element above the rest of the slide.", "familyLabel": null }, "subkind": null, "framework": null }, "subkind": null, "groupRole": null, "confidence": null, "extraction": { "at": "2026-04-23 22:42:19+00", "model": "claude-code-default", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "019dd951-9f64-72ba-b3fe-65b001b27399", "parentComponentId": null }, { "bbox": { "h": 0.869, "w": 0.605, "x": 0.355, "y": 0.037 }, "kind": "image", "text": null, "attrs": null, "canon": { "kind": { "name": "Image", "slug": "image", "status": "active", "canonId": "019de52c-f978-701f-a720-51d029d769e7", "version": 1, "description": "Photo, illustration, screenshot or icon." }, "tool": null, "subkind": { "name": "Photo", "slug": "photo", "status": "active", "canonId": "019de52c-fd37-757f-b4a8-ca26d4888875", "version": 1, "description": null }, "framework": null }, "subkind": "photo", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:49:09.698+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "c43961d7-16f1-41d4-93f6-9d3ccb96573b", "parentComponentId": null }, { "bbox": { "h": 0.328, "w": 0.256, "x": 0.058, "y": 0.268 }, "kind": "paragraph", "text": "Today's AI Achievers have set the standard and are poised to remain leaders. They have demonstrated that excellence in areas like vision and culture are just as critical as algorithmic integrity. But the potential for AI-mature organizations will evolve along with the technology itself—in other words, high performance today will ultimately become business-as-usual tomorrow. So, here are five key success factors for companies aspiring to be AI Achievers.", "attrs": null, "canon": { "kind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "5f2affc0-941d-4d07-959d-4bfc1930cea4", "version": 1, "description": "Single prose block in the body of a slide." }, "tool": null, "subkind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "019de52c-fb80-75af-aa5c-a7a4bfac2433", "version": 1, "description": null }, "framework": null }, "subkind": "paragraph", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:49:09.698+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "42bfda70-83d9-41f6-94a3-5b75243715ac", "parentComponentId": null }, { "bbox": { "h": 0.084, "w": 0.245, "x": 0.058, "y": 0.148 }, "kind": "title", "text": "How AI Achievers master their craft", "attrs": null, "canon": { "kind": { "name": "Title", "slug": "title", "status": "active", "canonId": "019de52c-f7dd-76d9-b848-b1f12bd85cf4", "version": 1, "description": "Slide title or headline." }, "tool": null, "subkind": { "name": "Headline", "slug": "headline", "status": "active", "canonId": "019de52c-fae1-7463-9a7c-d60668eced0d", "version": 1, "description": null }, "framework": null }, "subkind": "headline", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:49:09.698+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "27c93a28-177b-407e-9667-d38a370da735", "parentComponentId": null } ], "metrics": [], "tools": [], "frameworks": [], "arcBeats": [ { "to": 28, "arc": { "name": "The Consultant's Gambit", "slug": "consultants-gambit", "status": "active", "bestFor": "Business cases, project proposals, strategic recommendations", "canonId": "019dd956-5e0a-73c8-b305-81c38c959e9c", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "Situation & Context -> Problem & Complication -> Solution & Approach -> Evidence & Proof -> Impact & Next Steps", "description": null, "familyLabel": null }, "from": 18, "name": "Solution & Approach", "beatId": "019dd95a-0682-776c-8e32-9637b6b2b41d", "matchId": "019dd95a-0542-7728-a78e-666792080e8f", "beatType": { "name": "Evidence & Proof", "slug": "consultants-gambit-evidence-proof", "status": "active", "canonId": "019dd9b8-07b1-7688-8e1e-7637fec3802a", "version": 1, "description": null }, "evidence": "Five success factors: leadership, talent, AI core, responsible AI, investment.", "position": 4, "isPrimaryArc": true, "parentBeatType": { "name": "Evidence", "slug": "evidence", "status": "active", "canonId": "019dd9b8-03f9-772a-b84a-4f07b415b77a", "version": 1, "description": "A dedicated proof beat exists in only ~4 arcs (Gambit, Sequoia, AIDA, Monroes). Other arcs embed evidence inline within development." }, "alignedBlockIds": null, "matchConfidence": 88 }, { "to": 32, "arc": { "name": "The Triple Take", "slug": "triple-take", "status": "active", "bestFor": "Data-driven presentations, research findings", "canonId": "019dd956-6221-73ad-bc12-378f8eb1f018", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "The Facts (What) -> The Implications (So What) -> The Action (Now What)", "description": null, "familyLabel": null }, "from": 18, "name": "The Action (Now What)", "beatId": "019dd95a-0682-776c-8e32-a6c160fdc8c9", "matchId": "019dd95a-0542-7728-a78e-68cfbfb51150", "beatType": { "name": "The Action (Now What)", "slug": "triple-take-the-action-now-what", "status": "active", "canonId": "019dd9b8-0a5e-735a-bf53-3a1ba629b7aa", "version": 1, "description": null }, "evidence": "Five success factors plus C-suite self-assessment.", "position": 3, "isPrimaryArc": false, "parentBeatType": { "name": "Resolution", "slug": "resolution", "status": "active", "canonId": "019dd9b8-045d-703b-8dd7-e92aba3ba91b", "version": 1, "description": "How the deck ends. Required in 19/20 arcs. The exception (Sparkline) ends with new bliss which is functionally a resolution." }, "alignedBlockIds": null, "matchConfidence": 60 } ], "loops": [], "locked": true }, { "page": 20, "type": "tension", "title": "Success Factor 01 header indicates this is part of a series of findings.", "function": "cite_precedent", "rawType": "ceo_quote", "block": null, "metadata": { "slideType": "ceo_quote", "slideTypeCanon": { "name": "CEO quote", "slug": "ceo_quote", "status": "active", "canonId": "019de52d-09b6-71c8-93a5-f90a9772a8fa", "version": 1, "description": null }, "function": "cite_precedent", "functionCanon": { "name": "Cite precedent", "slug": "cite_precedent", "status": "active", "canonId": "019de52d-142b-714b-86d4-58aad7b568ec", "version": 1, "description": null }, "density": "overcrowded", "densityScore": 91, "componentCount": 11, "textChars": 1807, "nDataPoints": 3, "notes": "Success Factor 01 header indicates this is part of a series of findings.", "elementsJson": [ "action_title", "subtitle_text", "paragraph", "quote_block" ], "confidence": 1, "extraction": { "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "at": "2026-05-02 19:49:08.499+00", "seconds": 3.481, "promptVersion": "v2-canon-conditioned" } }, "links": { "slide": "/slides/019dd923-5ca1-7489-b633-7fa84bbf490b/20", "deck": "/decks/019dd923-5ca1-7489-b633-7fa84bbf490b", "deckAnchor": "/decks/019dd923-5ca1-7489-b633-7fa84bbf490b#slide-20", "deckJson": "/decks/019dd923-5ca1-7489-b633-7fa84bbf490b.json" }, "components": [ { "bbox": null, "kind": "callout", "text": "85% of Achievers in North America have such sponsorship, compared to 53% of Builders and 57% of Experimenters.", "attrs": null, "canon": { "kind": { "name": "Callout", "slug": "callout", "status": "active", "canonId": "019de52c-f8d3-761a-8953-7d37080de5e2", "version": 1, "description": "Highlighted callout box." }, "tool": { "name": "Visual emphasis", "slug": "visual-emphasis", "status": "active", "bestFor": null, "canonId": "019dd9e1-474b-736b-a8eb-a794dd88241c", "version": 1, "bodyDocId": null, "description": "Drawing the eye to one element above the rest of the slide.", "familyLabel": null }, "subkind": null, "framework": null }, "subkind": null, "groupRole": null, "confidence": null, "extraction": { "at": "2026-04-23 22:42:27+00", "model": "claude-code-default", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "019dd951-9f64-72ba-b3fe-9e4d42a3bd18", "parentComponentId": null }, { "bbox": null, "kind": "metric", "text": "Achievers with formal senior AI sponsorship in North America: 85%", "attrs": null, "canon": { "kind": { "name": "Metric", "slug": "metric", "status": "active", "canonId": "019de52c-f923-73bf-8081-d0b1a8c5264d", "version": 1, "description": "Big-number or KPI value." }, "tool": { "name": "Quantification", "slug": "quantification", "status": "active", "bestFor": null, "canonId": "019dd9e1-47ab-72ce-a079-aab1f5299e88", "version": 1, "bodyDocId": null, "description": "Translating a claim into numbers, charts, or tables.", "familyLabel": null }, "subkind": null, "framework": null }, "subkind": "primary", "groupRole": null, "confidence": null, "extraction": { "at": "2026-04-23 22:42:27+00", "model": "claude-code-default", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "019dd951-9f64-72ba-b3fe-a79e7577c445", "parentComponentId": null }, { "bbox": { "h": 0.033, "w": 0.386, "x": 0.557, "y": 0.683 }, "kind": "paragraph", "text": "Stephen Squeri, CEO, American Express.", "attrs": null, "canon": { "kind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "5f2affc0-941d-4d07-959d-4bfc1930cea4", "version": 1, "description": "Single prose block in the body of a slide." }, "tool": null, "subkind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "019de52c-fb80-75af-aa5c-a7a4bfac2433", "version": 1, "description": null }, "framework": null }, "subkind": "paragraph", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:49:08.499+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "0b63d858-a28b-482d-99af-a978c4ae1b62", "parentComponentId": null }, { "bbox": { "h": 0.047, "w": 0.257, "x": 0.343, "y": 0.633 }, "kind": "paragraph", "text": "In fact, in North America, 23% of Achievers embed innovation in their organizational strategies, while just 34% of Experimenters do.", "attrs": null, "canon": { "kind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "5f2affc0-941d-4d07-959d-4bfc1930cea4", "version": 1, "description": "Single prose block in the body of a slide." }, "tool": null, "subkind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "019de52c-fb80-75af-aa5c-a7a4bfac2433", "version": 1, "description": null }, "framework": null }, "subkind": "paragraph", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:49:08.499+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "207cd9be-2e17-4d43-9dc2-5072eafe9c21", "parentComponentId": null }, { "bbox": { "h": 0.153, "w": 0.257, "x": 0.343, "y": 0.373 }, "kind": "paragraph", "text": "Our research also suggests that the best AI strategies tend to be bold, even when they have modest beginnings. Bold AI strategies, in turn, help spur innovation. And for the CEOs of Achievers, creating a culture of innovation is itself a deliberate, strategic move—one that is used as a vehicle for experimentation and learning across the organization.", "attrs": null, "canon": { "kind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "5f2affc0-941d-4d07-959d-4bfc1930cea4", "version": 1, "description": "Single prose block in the body of a slide." }, "tool": null, "subkind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "019de52c-fb80-75af-aa5c-a7a4bfac2433", "version": 1, "description": null }, "framework": null }, "subkind": "paragraph", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:49:08.499+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "28f60e63-8dd6-492c-b864-f6eb4bd79b00", "parentComponentId": null }, { "bbox": { "h": 0.117, "w": 0.257, "x": 0.057, "y": 0.553 }, "kind": "paragraph", "text": "Achievers are more likely to have formal senior sponsorship for their AI strategies: we found that 85% of Achievers in North America have such sponsorship, compared to 53% of Builders and 57% of Experimenters.", "attrs": null, "canon": { "kind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "5f2affc0-941d-4d07-959d-4bfc1930cea4", "version": 1, "description": "Single prose block in the body of a slide." }, "tool": null, "subkind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "019de52c-fb80-75af-aa5c-a7a4bfac2433", "version": 1, "description": null }, "framework": null }, "subkind": "paragraph", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:49:08.499+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "4c7f0f80-1803-4664-96da-3d74d89c2652", "parentComponentId": null }, { "bbox": { "h": 0.117, "w": 0.257, "x": 0.057, "y": 0.373 }, "kind": "paragraph", "text": "Companies can create strong AI strategies, but unless those strategies receive enthusiastic support from the CEO and the rest of the C-suite, they're likely to flounder, competing with other initiatives for attention and resources.", "attrs": null, "canon": { "kind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "5f2affc0-941d-4d07-959d-4bfc1930cea4", "version": 1, "description": "Single prose block in the body of a slide." }, "tool": null, "subkind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "019de52c-fb80-75af-aa5c-a7a4bfac2433", "version": 1, "description": null }, "framework": null }, "subkind": "paragraph", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:49:08.499+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "f51c2d46-b889-4f92-906e-b5c4b60d7a6c", "parentComponentId": null }, { "bbox": { "h": 0.453, "w": 0.386, "x": 0.557, "y": 0.253 }, "kind": "quote", "text": "Data is nice—information is power. We've been on this journey, utilizing AI [artificial intelligence] and utilizing machine learning to help make credit decisions, to help make fraud decisions, to anticipate for our card members what offers to give them.", "attrs": null, "canon": { "kind": { "name": "Quote", "slug": "quote", "status": "active", "canonId": "019de52c-f8fb-751e-8bc6-d58e2d59562a", "version": 1, "description": "Pull quote or testimonial." }, "tool": null, "subkind": { "name": "Pull quote", "slug": "pull-quote", "status": "active", "canonId": "019de52c-fbf9-76fe-97e1-a0b7540445c9", "version": 1, "description": null }, "framework": null }, "subkind": "pull-quote", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:49:08.499+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "1e2f0466-4a39-4f16-9f5f-0fb3b1087b9d", "parentComponentId": null }, { "bbox": null, "kind": "quote", "text": "\"Data is nice—information is power. We've been on this journey, utilizing AI [artificial intelligence] and utilizing machine learning to help make credit decisions, to help make fraud decisions, to anticipate for our card members what offers to give them.\" — Stephen Squeri, CEO, American Express.", "attrs": null, "canon": { "kind": { "name": "Quote", "slug": "quote", "status": "active", "canonId": "019de52c-f8fb-751e-8bc6-d58e2d59562a", "version": 1, "description": "Pull quote or testimonial." }, "tool": { "name": "Authority citation", "slug": "authority-citation", "status": "active", "bestFor": null, "canonId": "019dd9e1-49ae-7557-89ad-3fca70469b45", "version": 1, "bodyDocId": null, "description": "Quoting an authority figure, study, or precedent to lend weight.", "familyLabel": null }, "subkind": null, "framework": null }, "subkind": null, "groupRole": null, "confidence": null, "extraction": { "at": "2026-04-23 22:42:27+00", "model": "claude-code-default", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "019dd951-9f64-72ba-b3fe-a1b773934650", "parentComponentId": null }, { "bbox": { "h": 0.117, "w": 0.425, "x": 0.057, "y": 0.173 }, "kind": "title", "text": "Champion AI as a strategic priority for the entire organization, with full sponsorship from leadership", "attrs": null, "canon": { "kind": { "name": "Title", "slug": "title", "status": "active", "canonId": "019de52c-f7dd-76d9-b848-b1f12bd85cf4", "version": 1, "description": "Slide title or headline." }, "tool": null, "subkind": { "name": "Headline", "slug": "headline", "status": "active", "canonId": "019de52c-fae1-7463-9a7c-d60668eced0d", "version": 1, "description": null }, "framework": null }, "subkind": "headline", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:49:08.499+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "1b3fe8d4-b8d4-4fe4-b8b4-88d60243b580", "parentComponentId": null }, { "bbox": { "h": 0.033, "w": 0.199, "x": 0.057, "y": 0.103 }, "kind": "title", "text": "Success Factor 01", "attrs": null, "canon": { "kind": { "name": "Title", "slug": "title", "status": "active", "canonId": "019de52c-f7dd-76d9-b848-b1f12bd85cf4", "version": 1, "description": "Slide title or headline." }, "tool": null, "subkind": { "name": "Subtitle", "slug": "subtitle", "status": "active", "canonId": "019de52c-fb09-739d-900c-815b0d9ac526", "version": 1, "description": null }, "framework": null }, "subkind": "subtitle", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:49:08.499+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "a8b655b6-e585-4aa2-931f-459f3fa91132", "parentComponentId": null } ], "metrics": [ { "metricRaw": "Achievers with formal senior AI sponsorship in North America", "numberRaw": "85%", "numberKind": "percent", "actionTitle": "Champion AI as a strategic priority for the entire organization, with full sponsorship from leadership", "calloutText": "85% of Achievers in North America have such sponsorship, compared to 53% of Builders and 57% of Experimenters.", "numberScale": null, "numberValue": 85, "metricFamily": "other", "numberCurrency": null } ], "tools": [ { "tool": { "name": "MECE Principle", "slug": "mece-principle", "status": "active", "bestFor": null, "canonId": "019dd956-7c60-71a8-8758-c79d914489c9", "version": 1, "bodyDocId": null, "description": "Mutually Exclusive, Collectively Exhaustive - ensuring complete, non-overlapping structure", "familyLabel": null, "categoryName": "Block", "categorySlug": "block" }, "agent": "Architect", "layer": "block", "agents": [ "Architect" ], "matchId": "019dd95a-0f08-73d3-987d-0df2f98702da", "evidence": "Five labelled, non-overlapping success factors structure the section.", "pageRefs": null, "priority": "Core", "whenToUse": null, "confidence": 80, "extraction": { "at": "2026-04-29 13:07:31.336924+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 20, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "Parallel Structure", "slug": "parallel-structure", "status": "active", "bestFor": null, "canonId": "019dd956-9f34-762a-93b7-1d8e84bbd153", "version": 1, "bodyDocId": null, "description": "Using similar grammatical structure for related ideas", "familyLabel": null, "categoryName": "Loop", "categorySlug": "loop" }, "agent": "Architect", "layer": "loop", "agents": [ "Architect" ], "matchId": "019dd95a-0f08-73d3-987d-0956cc8dd458", "evidence": "Opens 'Success Factor 01-05' template repeated through p28.", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 85, "extraction": { "at": "2026-04-29 13:07:31.336924+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 20, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "Action Titles", "slug": "action-titles", "status": "active", "bestFor": "Any decision-grade deliverable — strategy recommendation, board update, investment memo, M&A review, post-mortem — where the reader is being asked to agree, decide, or act and will skim the title bar at speed.", "canonId": "019dd956-ac70-700b-a608-ba58e78f5dcc", "version": 1, "bodyDocId": "816dad3c-9983-41c1-a86e-978ebd582841", "description": "The McKinsey-bred discipline of writing every slide title as a complete declarative sentence with a verb and an insight, not a topic label. Each title is a sub-claim that ladders up to the deck's governing thought; read in sequence, the titles reconstruct the executive summary.", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Architect", "layer": "slide", "agents": [ "Architect" ], "matchId": "019dd95a-0f08-73d3-987c-f85f60a1558c", "evidence": "Action title 'Champion AI as a strategic priority...' states the rec.", "pageRefs": null, "priority": "Core", "whenToUse": "Any decision-grade deliverable — strategy recommendation, board update, investment memo, M&A review, post-mortem — where the reader is being asked to agree, decide, or act and will skim the title bar at speed.", "confidence": 90, "extraction": { "at": "2026-04-29 13:07:31.336924+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 20, "whyItWorks": "Solves two failure modes at once. (1) The buried claim: action titles place the conclusion on the page before any analysis is read, so a busy reader doesn't reverse-engineer it from the chart. (2) The spineless deck: because each title is a claim, slides have to ladder up to the governing thought; logical gaps become visible as topic-shaped titles in a sequence that no longer reads as a story.", "antipattern": "Topic labels disguised as titles — Volume by quarter, Key findings, Pricing strategy, Margins have been impacted. No verb, or a passive verb with no agent, or a fact (Revenue grew 12%) without the so-what. Also: titles that overreach the chart's evidence, multi-claim X-grew-but-Y-fell welded titles, and mechanical repetition of the same X-drove-Y template across the deck.", "cardinality": null, "narrativePurpose": "Forces the deck to carry its argument in the title bar so a senior reader can extract the recommendation without opening a single slide; converts a binder of topics into a navigable pyramid where every slide is a node defending the apex." }, { "tool": { "name": "Authority Bias", "slug": "authority-bias", "status": "active", "bestFor": null, "canonId": "019dd956-c38d-70b9-a284-b2b479763356", "version": 1, "bodyDocId": null, "description": "Expert opinions are weighted more heavily - cite credible sources", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Storyteller", "layer": "slide", "agents": [ "Architect", "Storyteller" ], "matchId": "019dd95a-0f08-73d3-987d-0077d5a6a5ab", "evidence": "Named Fortune-500 CEO as the validating voice.", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 85, "extraction": { "at": "2026-04-29 13:07:31.336924+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 20, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "CEO quote contradiction", "slug": "ceo-quote-contradiction", "status": "active", "bestFor": "When management credibility is the lever", "canonId": "019dd9e1-52e9-717f-8454-93e627563ed6", "version": 1, "bodyDocId": "019dd9a1-8296-720d-8f51-da76937f9415", "description": "You reproduce management's own words — verbatim, with source and date — and\nthen place them next to the outcome that contradicts them. The CEO built\nthe rope; you put it around their own neck.", "familyLabel": null, "categoryName": null, "categorySlug": null }, "agent": null, "layer": "slide", "agents": null, "matchId": "057c10c5-ce51-4cfc-a0e9-9317678ff211", "evidence": "The slide includes a CEO quote, which could potentially be used to contradict a previous statement.", "pageRefs": null, "priority": null, "whenToUse": "When management credibility is the lever", "confidence": 0.6, "extraction": { "at": "2026-07-16 21:02:30.378817+00", "model": "or:meta-llama/llama-4-scout", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 20, "whyItWorks": "- **Maximum credibility**: no adjective you could write is as damning as the\n target's own prior statement.\n- **No rebuttal path**: management can't argue they didn't say it.\n- **It forces accountability onto a person**, not an institution — even if\n you aren't explicitly naming a villain elsewhere.\n- **Reporters amplify it**. A CEO-quote-contradiction slide is quotable,\n which means it lands in WSJ/FT/Bloomberg coverage.", "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "Concrete Language", "slug": "concrete-language", "status": "active", "bestFor": null, "canonId": "019dd956-bcd4-7398-9723-6aa72346170b", "version": 1, "bodyDocId": null, "description": "Using specific sensory details instead of abstract terms", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Storyteller", "layer": "slide", "agents": [ "Storyteller" ], "matchId": "019dd95a-0f08-73d3-987d-065a82c5d6af", "evidence": "85% of NA Achievers vs 53% Builders, 57% Experimenters.", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 85, "extraction": { "at": "2026-04-29 13:07:31.336924+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 20, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "Credibility Transfer", "slug": "credibility-transfer", "status": "active", "bestFor": null, "canonId": "019dd956-bd34-759a-8e3b-2f14b571a2a1", "version": 1, "bodyDocId": null, "description": "Borrowing authority from trusted sources or vivid details", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Storyteller", "layer": "slide", "agents": [ "Storyteller" ], "matchId": "019dd95a-0f08-73d3-987c-ff515049c8b6", "evidence": "Pull quote from Stephen Squeri, CEO of American Express.", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 90, "extraction": { "at": "2026-04-29 13:07:31.336924+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 20, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null } ], "frameworks": [], "arcBeats": [ { "to": 28, "arc": { "name": "The Consultant's Gambit", "slug": "consultants-gambit", "status": "active", "bestFor": "Business cases, project proposals, strategic recommendations", "canonId": "019dd956-5e0a-73c8-b305-81c38c959e9c", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "Situation & Context -> Problem & Complication -> Solution & Approach -> Evidence & Proof -> Impact & Next Steps", "description": null, "familyLabel": null }, "from": 18, "name": "Solution & Approach", "beatId": "019dd95a-0682-776c-8e32-9637b6b2b41d", "matchId": "019dd95a-0542-7728-a78e-666792080e8f", "beatType": { "name": "Evidence & Proof", "slug": "consultants-gambit-evidence-proof", "status": "active", "canonId": "019dd9b8-07b1-7688-8e1e-7637fec3802a", "version": 1, "description": null }, "evidence": "Five success factors: leadership, talent, AI core, responsible AI, investment.", "position": 4, "isPrimaryArc": true, "parentBeatType": { "name": "Evidence", "slug": "evidence", "status": "active", "canonId": "019dd9b8-03f9-772a-b84a-4f07b415b77a", "version": 1, "description": "A dedicated proof beat exists in only ~4 arcs (Gambit, Sequoia, AIDA, Monroes). Other arcs embed evidence inline within development." }, "alignedBlockIds": null, "matchConfidence": 88 }, { "to": 32, "arc": { "name": "The Triple Take", "slug": "triple-take", "status": "active", "bestFor": "Data-driven presentations, research findings", "canonId": "019dd956-6221-73ad-bc12-378f8eb1f018", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "The Facts (What) -> The Implications (So What) -> The Action (Now What)", "description": null, "familyLabel": null }, "from": 18, "name": "The Action (Now What)", "beatId": "019dd95a-0682-776c-8e32-a6c160fdc8c9", "matchId": "019dd95a-0542-7728-a78e-68cfbfb51150", "beatType": { "name": "The Action (Now What)", "slug": "triple-take-the-action-now-what", "status": "active", "canonId": "019dd9b8-0a5e-735a-bf53-3a1ba629b7aa", "version": 1, "description": null }, "evidence": "Five success factors plus C-suite self-assessment.", "position": 3, "isPrimaryArc": false, "parentBeatType": { "name": "Resolution", "slug": "resolution", "status": "active", "canonId": "019dd9b8-045d-703b-8dd7-e92aba3ba91b", "version": 1, "description": "How the deck ends. Required in 19/20 arcs. The exception (Sparkline) ends with new bliss which is functionally a resolution." }, "alignedBlockIds": null, "matchConfidence": 60 } ], "loops": [ { "to": 28, "from": 20, "loop": { "name": "40_mece_breakdown", "slug": "40-mece-breakdown", "status": "active", "bestFor": "Problem structuring, ensuring completeness, strategic analysis", "canonId": "019dd956-763c-765e-8b68-6ee3ae1ef184", "version": 1, "bodyDocId": "019df22a-2420-77be-bc41-ded96d08cb21", "structure": "The Whole -> Category A (distinct) -> Category B (distinct) -> Category C (distinct) -> Complete Coverage", "description": "Divide a complex topic into mutually exclusive, collectively exhaustive categories", "familyLabel": null }, "matchId": "019dd95a-07fe-70ce-8d3a-633fdd7803ae", "evidence": "Five labelled 'Success Factor 0X' sections each pairing recommendation + case study.", "position": 5, "objective": "Lay out five MECE success factors with evidence and cases", "confidence": 88, "extraction": { "at": "2026-04-29 13:07:29.547081+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null } } ], "locked": true }, { "page": 21, "type": "evidence", "title": "The slide uses a narrative approach to illustrate the benefits of AI maturity in North American companies.", "function": "illustrate_case", "rawType": "case_study", "block": null, "metadata": { "slideType": "case_study", "slideTypeCanon": { "name": "Case study", "slug": "case_study", "status": "active", "canonId": "019de52d-0b95-7344-8090-926f3b8e92c8", "version": 1, "description": null }, "function": "illustrate_case", "functionCanon": { "name": "Illustrate case", "slug": "illustrate_case", "status": "active", "canonId": "019de52d-13b4-772c-bb73-1873612a7463", "version": 1, "description": null }, "density": "dense", "densityScore": 72, "componentCount": 7, "textChars": 1289, "nDataPoints": 3, "notes": "The slide uses a narrative approach to illustrate the benefits of AI maturity in North American companies.", "elementsJson": [ "photo", "paragraph", "footnote" ], "confidence": 0.9, "extraction": { "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "at": "2026-05-02 19:49:11.689+00", "seconds": 6.501, "promptVersion": "v2-canon-conditioned" } }, "links": { "slide": "/slides/019dd923-5ca1-7489-b633-7fa84bbf490b/21", "deck": "/decks/019dd923-5ca1-7489-b633-7fa84bbf490b", "deckAnchor": "/decks/019dd923-5ca1-7489-b633-7fa84bbf490b#slide-21", "deckJson": "/decks/019dd923-5ca1-7489-b633-7fa84bbf490b.json" }, "components": [ { "bbox": null, "kind": "callout", "text": "We found that 4% of Achievers in North America are already using platforms that allow workers to easily pose questions and share ideas with colleagues across the company—compared to 3% of Experimenters.", "attrs": null, "canon": { "kind": { "name": "Callout", "slug": "callout", "status": "active", "canonId": "019de52c-f8d3-761a-8953-7d37080de5e2", "version": 1, "description": "Highlighted callout box." }, "tool": { "name": "Visual emphasis", "slug": "visual-emphasis", "status": "active", "bestFor": null, "canonId": "019dd9e1-474b-736b-a8eb-a794dd88241c", "version": 1, "bodyDocId": null, "description": "Drawing the eye to one element above the rest of the slide.", "familyLabel": null }, "subkind": null, "framework": null }, "subkind": null, "groupRole": null, "confidence": null, "extraction": { "at": "2026-04-23 22:42:31+00", "model": "claude-code-default", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "019dd951-9f64-72ba-b3fe-bc3955bddf77", "parentComponentId": null }, { "bbox": { "h": 0.87, "w": 0.45, "x": 0.03, "y": 0.05 }, "kind": "image", "text": null, "attrs": null, "canon": { "kind": { "name": "Image", "slug": "image", "status": "active", "canonId": "019de52c-f978-701f-a720-51d029d769e7", "version": 1, "description": "Photo, illustration, screenshot or icon." }, "tool": null, "subkind": { "name": "Photo", "slug": "photo", "status": "active", "canonId": "019de52c-fd37-757f-b4a8-ca26d4888875", "version": 1, "description": null }, "framework": null }, "subkind": "photo", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:49:11.689+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "48e077d4-b6b4-4590-bfdc-90e64ddb8119", "parentComponentId": null }, { "bbox": null, "kind": "metric", "text": "annualized margin uplift (global fashion retailer): US$70M", "attrs": null, "canon": { "kind": { "name": "Metric", "slug": "metric", "status": "active", "canonId": "019de52c-f923-73bf-8081-d0b1a8c5264d", "version": 1, "description": "Big-number or KPI value." }, "tool": { "name": "Quantification", "slug": "quantification", "status": "active", "bestFor": null, "canonId": "019dd9e1-47ab-72ce-a079-aab1f5299e88", "version": 1, "bodyDocId": null, "description": "Translating a claim into numbers, charts, or tables.", "familyLabel": null }, "subkind": null, "framework": null }, "subkind": "primary", "groupRole": null, "confidence": null, "extraction": { "at": "2026-04-23 22:42:31+00", "model": "claude-code-default", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "019dd951-9f64-72ba-b3fe-c07109414d4e", "parentComponentId": null }, { "bbox": { "h": 0.55, "w": 0.22, "x": 0.75, "y": 0.22 }, "kind": "paragraph", "text": "For Achievers, the willingness to embrace new tools and technologies often pays off. One global fashion retailer headquartered in the US aimed to address key challenges, including managing an increasingly costly and complex retail supply chain. They adopted an inventory solution that combines AI and simulation-driven optimization to cut losses, increase profits and improve the customer journey in stores. Today, the brand is projected to reap an annualized margin uplift of US$70M and expanded product availability.", "attrs": null, "canon": { "kind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "5f2affc0-941d-4d07-959d-4bfc1930cea4", "version": 1, "description": "Single prose block in the body of a slide." }, "tool": null, "subkind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "019de52c-fb80-75af-aa5c-a7a4bfac2433", "version": 1, "description": null }, "framework": null }, "subkind": "paragraph", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:49:11.689+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "0974a7c1-ac02-4e25-bbfa-b4103c14c15b", "parentComponentId": null }, { "bbox": { "h": 0.03, "w": 0.2, "x": 0.03, "y": 0.94 }, "kind": "paragraph", "text": "The art of AI maturity - North America", "attrs": null, "canon": { "kind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "5f2affc0-941d-4d07-959d-4bfc1930cea4", "version": 1, "description": "Single prose block in the body of a slide." }, "tool": null, "subkind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "019de52c-fb80-75af-aa5c-a7a4bfac2433", "version": 1, "description": null }, "framework": null }, "subkind": "paragraph", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:49:11.689+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "30ae3918-16b3-4631-93c2-3d3fe086503b", "parentComponentId": null }, { "bbox": { "h": 0.03, "w": 0.02, "x": 0.96, "y": 0.94 }, "kind": "paragraph", "text": "21", "attrs": null, "canon": { "kind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "5f2affc0-941d-4d07-959d-4bfc1930cea4", "version": 1, "description": "Single prose block in the body of a slide." }, "tool": null, "subkind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "019de52c-fb80-75af-aa5c-a7a4bfac2433", "version": 1, "description": null }, "framework": null }, "subkind": "paragraph", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:49:11.689+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "3e25c927-48e3-46dc-9d4e-f26a682f198b", "parentComponentId": null }, { "bbox": { "h": 0.55, "w": 0.22, "x": 0.51, "y": 0.22 }, "kind": "paragraph", "text": "To encourage such end-to-end innovation, Achievers implement systems and structures that help employees showcase their innovation experiments and seek constructive feedback from leadership. We found that 4% of Achievers in North America are already using platforms that allow workers to easily pose questions and share ideas with colleagues across the company—compared to 3% of Experimenters. That number will only grow as these companies expand their pools of AI talent.", "attrs": null, "canon": { "kind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "5f2affc0-941d-4d07-959d-4bfc1930cea4", "version": 1, "description": "Single prose block in the body of a slide." }, "tool": null, "subkind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "019de52c-fb80-75af-aa5c-a7a4bfac2433", "version": 1, "description": null }, "framework": null }, "subkind": "paragraph", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:49:11.689+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "4dafa2b4-4b05-4160-b603-1615e87a6845", "parentComponentId": null } ], "metrics": [ { "metricRaw": "annualized margin uplift (global fashion retailer)", "numberRaw": "US$70M", "numberKind": "money", "actionTitle": "For Achievers, the willingness to embrace new tools and technologies often pays off.", "calloutText": "We found that 4% of Achievers in North America are already using platforms that allow workers to easily pose questions and share ideas with colleagues across the company—compared to 3% of Experimenters.", "numberScale": "m", "numberValue": 70, "metricFamily": "margin_return", "numberCurrency": "$" } ], "tools": [ { "tool": { "name": "Concrete Language", "slug": "concrete-language", "status": "active", "bestFor": null, "canonId": "019dd956-bcd4-7398-9723-6aa72346170b", "version": 1, "bodyDocId": null, "description": "Using specific sensory details instead of abstract terms", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Storyteller", "layer": "slide", "agents": [ "Storyteller" ], "matchId": "019dd95a-0f08-73d3-987d-1063827989f7", "evidence": "Callout cites US$70M and 4% vs 3% comparison.", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 75, "extraction": { "at": "2026-04-29 13:07:31.336924+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 21, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "Story Moments", "slug": "story-moments", "status": "active", "bestFor": null, "canonId": "019dd956-ae4e-768d-a18b-108e6cda511e", "version": 1, "bodyDocId": null, "description": "Design key emotional beats: The Shock, The Vision, The Proof, The Choice, The Call", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Storyteller", "layer": "slide", "agents": [ "Storyteller" ], "matchId": "019dd95a-0f08-73d3-987d-14b2367452f5", "evidence": "Vignette of a NA Achiever embracing collaboration tools.", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 70, "extraction": { "at": "2026-04-29 13:07:31.336924+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 21, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null } ], "frameworks": [], "arcBeats": [ { "to": 28, "arc": { "name": "The Consultant's Gambit", "slug": "consultants-gambit", "status": "active", "bestFor": "Business cases, project proposals, strategic recommendations", "canonId": "019dd956-5e0a-73c8-b305-81c38c959e9c", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "Situation & Context -> Problem & Complication -> Solution & Approach -> Evidence & Proof -> Impact & Next Steps", "description": null, "familyLabel": null }, "from": 18, "name": "Solution & Approach", "beatId": "019dd95a-0682-776c-8e32-9637b6b2b41d", "matchId": "019dd95a-0542-7728-a78e-666792080e8f", "beatType": { "name": "Evidence & Proof", "slug": "consultants-gambit-evidence-proof", "status": "active", "canonId": "019dd9b8-07b1-7688-8e1e-7637fec3802a", "version": 1, "description": null }, "evidence": "Five success factors: leadership, talent, AI core, responsible AI, investment.", "position": 4, "isPrimaryArc": true, "parentBeatType": { "name": "Evidence", "slug": "evidence", "status": "active", "canonId": "019dd9b8-03f9-772a-b84a-4f07b415b77a", "version": 1, "description": "A dedicated proof beat exists in only ~4 arcs (Gambit, Sequoia, AIDA, Monroes). Other arcs embed evidence inline within development." }, "alignedBlockIds": null, "matchConfidence": 88 }, { "to": 32, "arc": { "name": "The Triple Take", "slug": "triple-take", "status": "active", "bestFor": "Data-driven presentations, research findings", "canonId": "019dd956-6221-73ad-bc12-378f8eb1f018", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "The Facts (What) -> The Implications (So What) -> The Action (Now What)", "description": null, "familyLabel": null }, "from": 18, "name": "The Action (Now What)", "beatId": "019dd95a-0682-776c-8e32-a6c160fdc8c9", "matchId": "019dd95a-0542-7728-a78e-68cfbfb51150", "beatType": { "name": "The Action (Now What)", "slug": "triple-take-the-action-now-what", "status": "active", "canonId": "019dd9b8-0a5e-735a-bf53-3a1ba629b7aa", "version": 1, "description": null }, "evidence": "Five success factors plus C-suite self-assessment.", "position": 3, "isPrimaryArc": false, "parentBeatType": { "name": "Resolution", "slug": "resolution", "status": "active", "canonId": "019dd9b8-045d-703b-8dd7-e92aba3ba91b", "version": 1, "description": "How the deck ends. Required in 19/20 arcs. The exception (Sparkline) ends with new bliss which is functionally a resolution." }, "alignedBlockIds": null, "matchConfidence": 60 } ], "loops": [ { "to": 28, "from": 20, "loop": { "name": "40_mece_breakdown", "slug": "40-mece-breakdown", "status": "active", "bestFor": "Problem structuring, ensuring completeness, strategic analysis", "canonId": "019dd956-763c-765e-8b68-6ee3ae1ef184", "version": 1, "bodyDocId": "019df22a-2420-77be-bc41-ded96d08cb21", "structure": "The Whole -> Category A (distinct) -> Category B (distinct) -> Category C (distinct) -> Complete Coverage", "description": "Divide a complex topic into mutually exclusive, collectively exhaustive categories", "familyLabel": null }, "matchId": "019dd95a-07fe-70ce-8d3a-633fdd7803ae", "evidence": "Five labelled 'Success Factor 0X' sections each pairing recommendation + case study.", "position": 5, "objective": "Lay out five MECE success factors with evidence and cases", "confidence": 88, "extraction": { "at": "2026-04-29 13:07:29.547081+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null } } ], "locked": true }, { "page": 22, "type": "resolution", "title": "Part of a series on 'The art of AI maturity'.", "function": "summarize", "rawType": "key_takeaways", "block": null, "metadata": { "slideType": "key_takeaways", "slideTypeCanon": { "name": "Key takeaways", "slug": "key_takeaways", "status": "active", "canonId": "019de52d-06e7-7674-a891-9f7de3b11b6d", "version": 1, "description": null }, "function": "summarize", "functionCanon": { "name": "Summarize", "slug": "summarize", "status": "active", "canonId": "019de52d-1541-704f-b86f-bf7b75056373", "version": 1, "description": null }, "density": "overcrowded", "densityScore": 79, "componentCount": 8, "textChars": 1260, "nDataPoints": 3, "notes": "Part of a series on 'The art of AI maturity'.", "elementsJson": [ "headline_text", "action_title", "subtitle_text", "paragraph", "photo" ], "confidence": 0.95, "extraction": { "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "at": "2026-05-02 19:49:08.896+00", "seconds": 3.445, "promptVersion": "v2-canon-conditioned" } }, "links": { "slide": "/slides/019dd923-5ca1-7489-b633-7fa84bbf490b/22", "deck": "/decks/019dd923-5ca1-7489-b633-7fa84bbf490b", "deckAnchor": "/decks/019dd923-5ca1-7489-b633-7fa84bbf490b#slide-22", "deckJson": "/decks/019dd923-5ca1-7489-b633-7fa84bbf490b.json" }, "components": [ { "bbox": null, "kind": "callout", "text": "We found, for example, that 56% of Achievers in North America have mandatory AI trainings for most employees, from product development engineers to C-suite executives.", "attrs": null, "canon": { "kind": { "name": "Callout", "slug": "callout", "status": "active", "canonId": "019de52c-f8d3-761a-8953-7d37080de5e2", "version": 1, "description": "Highlighted callout box." }, "tool": { "name": "Visual emphasis", "slug": "visual-emphasis", "status": "active", "bestFor": null, "canonId": "019dd9e1-474b-736b-a8eb-a794dd88241c", "version": 1, "bodyDocId": null, "description": "Drawing the eye to one element above the rest of the slide.", "familyLabel": null }, "subkind": null, "framework": null }, "subkind": null, "groupRole": null, "confidence": null, "extraction": { "at": "2026-04-23 22:42:26+00", "model": "claude-code-default", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "019dd951-9f64-72ba-b3fe-7f4fedb828c7", "parentComponentId": null }, { "bbox": { "h": 0.85, "w": 0.44, "x": 0.52, "y": 0.06 }, "kind": "image", "text": null, "attrs": null, "canon": { "kind": { "name": "Image", "slug": "image", "status": "active", "canonId": "019de52c-f978-701f-a720-51d029d769e7", "version": 1, "description": "Photo, illustration, screenshot or icon." }, "tool": null, "subkind": { "name": "Photo", "slug": "photo", "status": "active", "canonId": "019de52c-fd37-757f-b4a8-ca26d4888875", "version": 1, "description": null }, "framework": null }, "subkind": "photo", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:49:08.896+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "1ae1f70b-7fde-4b59-a9ff-5c58ed79144a", "parentComponentId": null }, { "bbox": null, "kind": "metric", "text": "Achievers with consistently high AI skills competencies: 35%", "attrs": null, "canon": { "kind": { "name": "Metric", "slug": "metric", "status": "active", "canonId": "019de52c-f923-73bf-8081-d0b1a8c5264d", "version": 1, "description": "Big-number or KPI value." }, "tool": { "name": "Quantification", "slug": "quantification", "status": "active", "bestFor": null, "canonId": "019dd9e1-47ab-72ce-a079-aab1f5299e88", "version": 1, "bodyDocId": null, "description": "Translating a claim into numbers, charts, or tables.", "familyLabel": null }, "subkind": null, "framework": null }, "subkind": "primary", "groupRole": null, "confidence": null, "extraction": { "at": "2026-04-23 22:42:26+00", "model": "claude-code-default", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "019dd951-9f64-72ba-b3fe-83a4e3d48642", "parentComponentId": null }, { "bbox": { "h": 0.15, "w": 0.2, "x": 0.06, "y": 0.3 }, "kind": "paragraph", "text": "With a clear AI strategy and strong CEO sponsorship, organizations are more likely to invest heavily in creating data and AI fluency across their workforces. While AI proficiency must start at the top, it can't end there.", "attrs": null, "canon": { "kind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "5f2affc0-941d-4d07-959d-4bfc1930cea4", "version": 1, "description": "Single prose block in the body of a slide." }, "tool": null, "subkind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "019de52c-fb80-75af-aa5c-a7a4bfac2433", "version": 1, "description": null }, "framework": null }, "subkind": "paragraph", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:49:08.896+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "87d284d2-7fd0-405f-ad39-a2b5afba3836", "parentComponentId": null }, { "bbox": { "h": 0.25, "w": 0.4, "x": 0.06, "y": 0.48 }, "kind": "paragraph", "text": "We found, for example, that 56% of Achievers in North America have mandatory AI trainings for most employees, from product development engineers to C-suite executives. Because Achievers prioritize efforts to build AI literacy in their workforces, it's no surprise that their employees are also more proficient in AI-related skills. This makes it much easier to scale human and AI collaboration and ensure that AI permeates the organization.", "attrs": null, "canon": { "kind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "5f2affc0-941d-4d07-959d-4bfc1930cea4", "version": 1, "description": "Single prose block in the body of a slide." }, "tool": null, "subkind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "019de52c-fb80-75af-aa5c-a7a4bfac2433", "version": 1, "description": null }, "framework": null }, "subkind": "paragraph", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:49:08.896+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "b1d72901-c4be-431e-925b-01beb07eb7d2", "parentComponentId": null }, { "bbox": { "h": 0.2, "w": 0.2, "x": 0.28, "y": 0.3 }, "kind": "paragraph", "text": "Today, more than one-third (35%) of Achievers have employees with consistently high AI skills competencies, while Innovators (33%) and Experimenters (27%) have fewer such employees, on average. Furthermore, Achievers have employees with higher competencies in almost all data- and AI-related skills.", "attrs": null, "canon": { "kind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "5f2affc0-941d-4d07-959d-4bfc1930cea4", "version": 1, "description": "Single prose block in the body of a slide." }, "tool": null, "subkind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "019de52c-fb80-75af-aa5c-a7a4bfac2433", "version": 1, "description": null }, "framework": null }, "subkind": "paragraph", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:49:08.896+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "b2ddbada-7966-4cd9-bab9-584f0b2dd3a0", "parentComponentId": null }, { "bbox": { "h": 0.1, "w": 0.4, "x": 0.06, "y": 0.16 }, "kind": "title", "text": "Invest heavily in talent to get more from AI investments", "attrs": null, "canon": { "kind": { "name": "Title", "slug": "title", "status": "active", "canonId": "019de52c-f7dd-76d9-b848-b1f12bd85cf4", "version": 1, "description": "Slide title or headline." }, "tool": null, "subkind": { "name": "Headline", "slug": "headline", "status": "active", "canonId": "019de52c-fae1-7463-9a7c-d60668eced0d", "version": 1, "description": null }, "framework": null }, "subkind": "headline", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:49:08.896+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "fa5fc626-9da5-4468-ba2b-f4df5b57b662", "parentComponentId": null }, { "bbox": { "h": 0.03, "w": 0.2, "x": 0.06, "y": 0.1 }, "kind": "title", "text": "Success Factor 02", "attrs": null, "canon": { "kind": { "name": "Title", "slug": "title", "status": "active", "canonId": "019de52c-f7dd-76d9-b848-b1f12bd85cf4", "version": 1, "description": "Slide title or headline." }, "tool": null, "subkind": { "name": "Subtitle", "slug": "subtitle", "status": "active", "canonId": "019de52c-fb09-739d-900c-815b0d9ac526", "version": 1, "description": null }, "framework": null }, "subkind": "subtitle", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:49:08.896+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "ad6216c8-3a04-4254-8e4d-450aeb8a1e45", "parentComponentId": null } ], "metrics": [ { "metricRaw": "Achievers with consistently high AI skills competencies", "numberRaw": "35%", "numberKind": "percent", "actionTitle": "Invest heavily in talent to get more from AI investments", "calloutText": "We found, for example, that 56% of Achievers in North America have mandatory AI trainings for most employees, from product development engineers to C-suite executives.", "numberScale": null, "numberValue": 35, "metricFamily": "other", "numberCurrency": null } ], "tools": [ { "tool": { "name": "Action Titles", "slug": "action-titles", "status": "active", "bestFor": "Any decision-grade deliverable — strategy recommendation, board update, investment memo, M&A review, post-mortem — where the reader is being asked to agree, decide, or act and will skim the title bar at speed.", "canonId": "019dd956-ac70-700b-a608-ba58e78f5dcc", "version": 1, "bodyDocId": "816dad3c-9983-41c1-a86e-978ebd582841", "description": "The McKinsey-bred discipline of writing every slide title as a complete declarative sentence with a verb and an insight, not a topic label. Each title is a sub-claim that ladders up to the deck's governing thought; read in sequence, the titles reconstruct the executive summary.", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Architect", "layer": "slide", "agents": [ "Architect" ], "matchId": "019dd95a-0f08-73d3-987d-19c9f532e24c", "evidence": "Action title 'Invest heavily in talent...' is the recommendation.", "pageRefs": null, "priority": "Core", "whenToUse": "Any decision-grade deliverable — strategy recommendation, board update, investment memo, M&A review, post-mortem — where the reader is being asked to agree, decide, or act and will skim the title bar at speed.", "confidence": 90, "extraction": { "at": "2026-04-29 13:07:31.336924+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 22, "whyItWorks": "Solves two failure modes at once. (1) The buried claim: action titles place the conclusion on the page before any analysis is read, so a busy reader doesn't reverse-engineer it from the chart. (2) The spineless deck: because each title is a claim, slides have to ladder up to the governing thought; logical gaps become visible as topic-shaped titles in a sequence that no longer reads as a story.", "antipattern": "Topic labels disguised as titles — Volume by quarter, Key findings, Pricing strategy, Margins have been impacted. No verb, or a passive verb with no agent, or a fact (Revenue grew 12%) without the so-what. Also: titles that overreach the chart's evidence, multi-claim X-grew-but-Y-fell welded titles, and mechanical repetition of the same X-drove-Y template across the deck.", "cardinality": null, "narrativePurpose": "Forces the deck to carry its argument in the title bar so a senior reader can extract the recommendation without opening a single slide; converts a binder of topics into a navigable pyramid where every slide is a node defending the apex." }, { "tool": { "name": "Concrete Language", "slug": "concrete-language", "status": "active", "bestFor": null, "canonId": "019dd956-bcd4-7398-9723-6aa72346170b", "version": 1, "bodyDocId": null, "description": "Using specific sensory details instead of abstract terms", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Storyteller", "layer": "slide", "agents": [ "Storyteller" ], "matchId": "019dd95a-0f08-73d3-987d-1c19f31c9904", "evidence": "56% with mandatory training; 35% NA stat.", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 85, "extraction": { "at": "2026-04-29 13:07:31.336924+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 22, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null } ], "frameworks": [], "arcBeats": [ { "to": 28, "arc": { "name": "The Consultant's Gambit", "slug": "consultants-gambit", "status": "active", "bestFor": "Business cases, project proposals, strategic recommendations", "canonId": "019dd956-5e0a-73c8-b305-81c38c959e9c", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "Situation & Context -> Problem & Complication -> Solution & Approach -> Evidence & Proof -> Impact & Next Steps", "description": null, "familyLabel": null }, "from": 18, "name": "Solution & Approach", "beatId": "019dd95a-0682-776c-8e32-9637b6b2b41d", "matchId": "019dd95a-0542-7728-a78e-666792080e8f", "beatType": { "name": "Evidence & Proof", "slug": "consultants-gambit-evidence-proof", "status": "active", "canonId": "019dd9b8-07b1-7688-8e1e-7637fec3802a", "version": 1, "description": null }, "evidence": "Five success factors: leadership, talent, AI core, responsible AI, investment.", "position": 4, "isPrimaryArc": true, "parentBeatType": { "name": "Evidence", "slug": "evidence", "status": "active", "canonId": "019dd9b8-03f9-772a-b84a-4f07b415b77a", "version": 1, "description": "A dedicated proof beat exists in only ~4 arcs (Gambit, Sequoia, AIDA, Monroes). Other arcs embed evidence inline within development." }, "alignedBlockIds": null, "matchConfidence": 88 }, { "to": 32, "arc": { "name": "The Triple Take", "slug": "triple-take", "status": "active", "bestFor": "Data-driven presentations, research findings", "canonId": "019dd956-6221-73ad-bc12-378f8eb1f018", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "The Facts (What) -> The Implications (So What) -> The Action (Now What)", "description": null, "familyLabel": null }, "from": 18, "name": "The Action (Now What)", "beatId": "019dd95a-0682-776c-8e32-a6c160fdc8c9", "matchId": "019dd95a-0542-7728-a78e-68cfbfb51150", "beatType": { "name": "The Action (Now What)", "slug": "triple-take-the-action-now-what", "status": "active", "canonId": "019dd9b8-0a5e-735a-bf53-3a1ba629b7aa", "version": 1, "description": null }, "evidence": "Five success factors plus C-suite self-assessment.", "position": 3, "isPrimaryArc": false, "parentBeatType": { "name": "Resolution", "slug": "resolution", "status": "active", "canonId": "019dd9b8-045d-703b-8dd7-e92aba3ba91b", "version": 1, "description": "How the deck ends. Required in 19/20 arcs. The exception (Sparkline) ends with new bliss which is functionally a resolution." }, "alignedBlockIds": null, "matchConfidence": 60 } ], "loops": [ { "to": 28, "from": 20, "loop": { "name": "40_mece_breakdown", "slug": "40-mece-breakdown", "status": "active", "bestFor": "Problem structuring, ensuring completeness, strategic analysis", "canonId": "019dd956-763c-765e-8b68-6ee3ae1ef184", "version": 1, "bodyDocId": "019df22a-2420-77be-bc41-ded96d08cb21", "structure": "The Whole -> Category A (distinct) -> Category B (distinct) -> Category C (distinct) -> Complete Coverage", "description": "Divide a complex topic into mutually exclusive, collectively exhaustive categories", "familyLabel": null }, "matchId": "019dd95a-07fe-70ce-8d3a-633fdd7803ae", "evidence": "Five labelled 'Success Factor 0X' sections each pairing recommendation + case study.", "position": 5, "objective": "Lay out five MECE success factors with evidence and cases", "confidence": 88, "extraction": { "at": "2026-04-29 13:07:29.547081+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null } } ], "locked": true }, { "page": 23, "type": "evidence", "title": "The slide uses a mix of narrative case studies and a quantitative callout to support the thesis on AI talent maturity.", "function": "illustrate_case", "rawType": "client_example", "block": null, "metadata": { "slideType": "client_example", "slideTypeCanon": { "name": "Client example", "slug": "client_example", "status": "active", "canonId": "019de52d-0c87-77cb-9867-613ae22e95ac", "version": 1, "description": null }, "function": "illustrate_case", "functionCanon": { "name": "Illustrate case", "slug": "illustrate_case", "status": "active", "canonId": "019de52d-13b4-772c-bb73-1873612a7463", "version": 1, "description": null }, "density": "overcrowded", "densityScore": 75, "componentCount": 7, "textChars": 1786, "nDataPoints": 3, "notes": "The slide uses a mix of narrative case studies and a quantitative callout to support the thesis on AI talent maturity.", "elementsJson": [ "paragraph", "big_number", "callout_box" ], "confidence": 0.95, "extraction": { "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "at": "2026-05-02 19:49:09.089+00", "seconds": 3.617, "promptVersion": "v2-canon-conditioned" } }, "links": { "slide": "/slides/019dd923-5ca1-7489-b633-7fa84bbf490b/23", "deck": "/decks/019dd923-5ca1-7489-b633-7fa84bbf490b", "deckAnchor": "/decks/019dd923-5ca1-7489-b633-7fa84bbf490b#slide-23", "deckJson": "/decks/019dd923-5ca1-7489-b633-7fa84bbf490b.json" }, "components": [ { "bbox": null, "kind": "callout", "text": "35% of Achievers in North America have employees with consistently high AI skills competencies, while Innovators (33%) and Experimenters (27%) have fewer such employees, on average.", "attrs": null, "canon": { "kind": { "name": "Callout", "slug": "callout", "status": "active", "canonId": "019de52c-f8d3-761a-8953-7d37080de5e2", "version": 1, "description": "Highlighted callout box." }, "tool": { "name": "Visual emphasis", "slug": "visual-emphasis", "status": "active", "bestFor": null, "canonId": "019dd9e1-474b-736b-a8eb-a794dd88241c", "version": 1, "bodyDocId": null, "description": "Drawing the eye to one element above the rest of the slide.", "familyLabel": null }, "subkind": null, "framework": null }, "subkind": null, "groupRole": null, "confidence": null, "extraction": { "at": "2026-04-23 22:42:31+00", "model": "claude-code-default", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "019dd951-9f64-72ba-b3fe-dca0f13e62eb", "parentComponentId": null }, { "bbox": { "h": 0.15, "w": 0.15, "x": 0.6, "y": 0.25 }, "kind": "metric", "text": "35%", "attrs": null, "canon": { "kind": { "name": "Metric", "slug": "metric", "status": "active", "canonId": "019de52c-f923-73bf-8081-d0b1a8c5264d", "version": 1, "description": "Big-number or KPI value." }, "tool": null, "subkind": { "name": "Big number", "slug": "big-number", "status": "active", "canonId": "019de52c-fc70-70c8-b965-0584548a9204", "version": 1, "description": null }, "framework": null }, "subkind": "big-number", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:49:09.089+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "1ad52d25-9c36-4e29-a531-f4bac27e4c60", "parentComponentId": null }, { "bbox": null, "kind": "metric", "text": "Share of companies with consistently high AI skills competencies: 35%", "attrs": null, "canon": { "kind": { "name": "Metric", "slug": "metric", "status": "active", "canonId": "019de52c-f923-73bf-8081-d0b1a8c5264d", "version": 1, "description": "Big-number or KPI value." }, "tool": { "name": "Quantification", "slug": "quantification", "status": "active", "bestFor": null, "canonId": "019dd9e1-47ab-72ce-a079-aab1f5299e88", "version": 1, "bodyDocId": null, "description": "Translating a claim into numbers, charts, or tables.", "familyLabel": null }, "subkind": null, "framework": null }, "subkind": "primary", "groupRole": null, "confidence": null, "extraction": { "at": "2026-04-23 22:42:31+00", "model": "claude-code-default", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "019dd951-9f64-72ba-b3fe-e336fc7d1a08", "parentComponentId": null }, { "bbox": { "h": 0.35, "w": 0.25, "x": 0.05, "y": 0.55 }, "kind": "paragraph", "text": "In 2018, US utility Exelon established an “analytics academy.” This training center upskilled employees like Jeffrey Swiatek, who, at the age of 41, transitioned from his longtime role as a maintenance worker to become a quantitative engineer (a higher-paying position). Swiatek has since used his training to write predictive software that saved Exelon an estimated $1 million over eight years on equipment maintenance.", "attrs": null, "canon": { "kind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "5f2affc0-941d-4d07-959d-4bfc1930cea4", "version": 1, "description": "Single prose block in the body of a slide." }, "tool": null, "subkind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "019de52c-fb80-75af-aa5c-a7a4bfac2433", "version": 1, "description": null }, "framework": null }, "subkind": "paragraph", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:49:09.089+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "442d0a65-f2b1-47b9-b596-a59fc967c1d3", "parentComponentId": null }, { "bbox": { "h": 0.35, "w": 0.25, "x": 0.32, "y": 0.18 }, "kind": "paragraph", "text": "Another example: A global retailer in North America used data and AI to create a more inclusive workplace in which people could thrive in a culture of belonging. Moving away from often siloed, conventional approaches to bias detection (such as black box models or statistical machine learning), it used flexible analytics and I&D frameworks to determine the degree and significance of bias within the organization and develop a roadmap to achieve its representative staffing goals.", "attrs": null, "canon": { "kind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "5f2affc0-941d-4d07-959d-4bfc1930cea4", "version": 1, "description": "Single prose block in the body of a slide." }, "tool": null, "subkind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "019de52c-fb80-75af-aa5c-a7a4bfac2433", "version": 1, "description": null }, "framework": null }, "subkind": "paragraph", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:49:09.089+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "5f58b0e1-6ca7-4e9b-b4c6-5bc4b3d26e8e", "parentComponentId": null }, { "bbox": { "h": 0.2, "w": 0.25, "x": 0.6, "y": 0.45 }, "kind": "paragraph", "text": "of Achievers in North America have employees with consistently high AI skills competencies, while Innovators (33%) and Experimenters (27%) have fewer such employees, on average.", "attrs": null, "canon": { "kind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "5f2affc0-941d-4d07-959d-4bfc1930cea4", "version": 1, "description": "Single prose block in the body of a slide." }, "tool": null, "subkind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "019de52c-fb80-75af-aa5c-a7a4bfac2433", "version": 1, "description": null }, "framework": null }, "subkind": "paragraph", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:49:09.089+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "95126404-e1c1-482b-b6a0-2dcee4da6ceb", "parentComponentId": null }, { "bbox": { "h": 0.35, "w": 0.25, "x": 0.05, "y": 0.18 }, "kind": "paragraph", "text": "Achievers also develop proactive AI talent strategies to stay at the forefront of industry trends. In addition to hiring, this could mean partnering with or acquiring specialist companies to fill critical roles (such as data or behavioral scientists, social scientists and ethicists). It also means having a plan to get these diverse, multidisciplinary workers to collaborate, create and sustain maximum value from the company's data-science capabilities.", "attrs": null, "canon": { "kind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "5f2affc0-941d-4d07-959d-4bfc1930cea4", "version": 1, "description": "Single prose block in the body of a slide." }, "tool": null, "subkind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "019de52c-fb80-75af-aa5c-a7a4bfac2433", "version": 1, "description": null }, "framework": null }, "subkind": "paragraph", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:49:09.089+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "faa5bc3a-99d0-4c7a-906c-fa772d6c1d32", "parentComponentId": null } ], "metrics": [ { "metricRaw": "Share of companies with consistently high AI skills competencies", "numberRaw": "35%", "numberKind": "percent", "actionTitle": "35% of Achievers in North America have employees with consistently high AI skills competencies, while Innovators (33%) and Experimenters (27%) have fewer such employees, on average.", "calloutText": "35% of Achievers in North America have employees with consistently high AI skills competencies, while Innovators (33%) and Experimenters (27%) have fewer such employees, on average.", "numberScale": null, "numberValue": 35, "metricFamily": "survey_sentiment", "numberCurrency": null } ], "tools": [ { "tool": { "name": "Concrete Language", "slug": "concrete-language", "status": "active", "bestFor": null, "canonId": "019dd956-bcd4-7398-9723-6aa72346170b", "version": 1, "bodyDocId": null, "description": "Using specific sensory details instead of abstract terms", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Storyteller", "layer": "slide", "agents": [ "Storyteller" ], "matchId": "019dd95a-0f08-73d3-987d-23198726ca9e", "evidence": "35% Achievers vs 33% Innovators vs 27% Experimenters.", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 80, "extraction": { "at": "2026-04-29 13:07:31.336924+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 23, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "Story Moments", "slug": "story-moments", "status": "active", "bestFor": null, "canonId": "019dd956-ae4e-768d-a18b-108e6cda511e", "version": 1, "bodyDocId": null, "description": "Design key emotional beats: The Shock, The Vision, The Proof, The Choice, The Call", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Storyteller", "layer": "slide", "agents": [ "Storyteller" ], "matchId": "019dd95a-0f08-73d3-987d-2734dc9b4e2a", "evidence": "Case illustration of AI talent depth across firm.", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 65, "extraction": { "at": "2026-04-29 13:07:31.336924+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 23, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null } ], "frameworks": [], "arcBeats": [ { "to": 28, "arc": { "name": "The Consultant's Gambit", "slug": "consultants-gambit", "status": "active", "bestFor": "Business cases, project proposals, strategic recommendations", "canonId": "019dd956-5e0a-73c8-b305-81c38c959e9c", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "Situation & Context -> Problem & Complication -> Solution & Approach -> Evidence & Proof -> Impact & Next Steps", "description": null, "familyLabel": null }, "from": 18, "name": "Solution & Approach", "beatId": "019dd95a-0682-776c-8e32-9637b6b2b41d", "matchId": "019dd95a-0542-7728-a78e-666792080e8f", "beatType": { "name": "Evidence & Proof", "slug": "consultants-gambit-evidence-proof", "status": "active", "canonId": "019dd9b8-07b1-7688-8e1e-7637fec3802a", "version": 1, "description": null }, "evidence": "Five success factors: leadership, talent, AI core, responsible AI, investment.", "position": 4, "isPrimaryArc": true, "parentBeatType": { "name": "Evidence", "slug": "evidence", "status": "active", "canonId": "019dd9b8-03f9-772a-b84a-4f07b415b77a", "version": 1, "description": "A dedicated proof beat exists in only ~4 arcs (Gambit, Sequoia, AIDA, Monroes). Other arcs embed evidence inline within development." }, "alignedBlockIds": null, "matchConfidence": 88 }, { "to": 32, "arc": { "name": "The Triple Take", "slug": "triple-take", "status": "active", "bestFor": "Data-driven presentations, research findings", "canonId": "019dd956-6221-73ad-bc12-378f8eb1f018", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "The Facts (What) -> The Implications (So What) -> The Action (Now What)", "description": null, "familyLabel": null }, "from": 18, "name": "The Action (Now What)", "beatId": "019dd95a-0682-776c-8e32-a6c160fdc8c9", "matchId": "019dd95a-0542-7728-a78e-68cfbfb51150", "beatType": { "name": "The Action (Now What)", "slug": "triple-take-the-action-now-what", "status": "active", "canonId": "019dd9b8-0a5e-735a-bf53-3a1ba629b7aa", "version": 1, "description": null }, "evidence": "Five success factors plus C-suite self-assessment.", "position": 3, "isPrimaryArc": false, "parentBeatType": { "name": "Resolution", "slug": "resolution", "status": "active", "canonId": "019dd9b8-045d-703b-8dd7-e92aba3ba91b", "version": 1, "description": "How the deck ends. Required in 19/20 arcs. The exception (Sparkline) ends with new bliss which is functionally a resolution." }, "alignedBlockIds": null, "matchConfidence": 60 } ], "loops": [ { "to": 28, "from": 20, "loop": { "name": "40_mece_breakdown", "slug": "40-mece-breakdown", "status": "active", "bestFor": "Problem structuring, ensuring completeness, strategic analysis", "canonId": "019dd956-763c-765e-8b68-6ee3ae1ef184", "version": 1, "bodyDocId": "019df22a-2420-77be-bc41-ded96d08cb21", "structure": "The Whole -> Category A (distinct) -> Category B (distinct) -> Category C (distinct) -> Complete Coverage", "description": "Divide a complex topic into mutually exclusive, collectively exhaustive categories", "familyLabel": null }, "matchId": "019dd95a-07fe-70ce-8d3a-633fdd7803ae", "evidence": "Five labelled 'Success Factor 0X' sections each pairing recommendation + case study.", "position": 5, "objective": "Lay out five MECE success factors with evidence and cases", "confidence": 88, "extraction": { "at": "2026-04-29 13:07:29.547081+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null } } ], "locked": true }, { "page": 24, "type": "resolution", "title": "Part of a series on 'Success Factors' for AI maturity.", "function": "summarize", "rawType": "key_takeaways", "block": null, "metadata": { "slideType": "key_takeaways", "slideTypeCanon": { "name": "Key takeaways", "slug": "key_takeaways", "status": "active", "canonId": "019de52d-06e7-7674-a891-9f7de3b11b6d", "version": 1, "description": null }, "function": "summarize", "functionCanon": { "name": "Summarize", "slug": "summarize", "status": "active", "canonId": "019de52d-1541-704f-b86f-bf7b75056373", "version": 1, "description": null }, "density": "overcrowded", "densityScore": 83, "componentCount": 9, "textChars": 1193, "nDataPoints": 2, "notes": "Part of a series on 'Success Factors' for AI maturity.", "elementsJson": [ "headline_text", "action_title", "subtitle_text", "paragraph", "photo", "footnote" ], "confidence": 0.95, "extraction": { "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "at": "2026-05-02 19:49:08.819+00", "seconds": 3.018, "promptVersion": "v2-canon-conditioned" } }, "links": { "slide": "/slides/019dd923-5ca1-7489-b633-7fa84bbf490b/24", "deck": "/decks/019dd923-5ca1-7489-b633-7fa84bbf490b", "deckAnchor": "/decks/019dd923-5ca1-7489-b633-7fa84bbf490b#slide-24", "deckJson": "/decks/019dd923-5ca1-7489-b633-7fa84bbf490b.json" }, "components": [ { "bbox": null, "kind": "callout", "text": "Achievers in North America are 72% more likely, on average, than Experimenters to either develop custom-built machine learning applications or work with a partner that offers solutions-as-a-service.", "attrs": null, "canon": { "kind": { "name": "Callout", "slug": "callout", "status": "active", "canonId": "019de52c-f8d3-761a-8953-7d37080de5e2", "version": 1, "description": "Highlighted callout box." }, "tool": { "name": "Visual emphasis", "slug": "visual-emphasis", "status": "active", "bestFor": null, "canonId": "019dd9e1-474b-736b-a8eb-a794dd88241c", "version": 1, "bodyDocId": null, "description": "Drawing the eye to one element above the rest of the slide.", "familyLabel": null }, "subkind": null, "framework": null }, "subkind": null, "groupRole": null, "confidence": null, "extraction": { "at": "2026-04-23 22:42:37+00", "model": "claude-code-default", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "019dd951-9f64-72ba-b3fe-f56ba8fcc151", "parentComponentId": null }, { "bbox": { "h": 0.85, "w": 0.4, "x": 0.55, "y": 0.05 }, "kind": "image", "text": null, "attrs": null, "canon": { "kind": { "name": "Image", "slug": "image", "status": "active", "canonId": "019de52c-f978-701f-a720-51d029d769e7", "version": 1, "description": "Photo, illustration, screenshot or icon." }, "tool": null, "subkind": { "name": "Photo", "slug": "photo", "status": "active", "canonId": "019de52c-fd37-757f-b4a8-ca26d4888875", "version": 1, "description": null }, "framework": null }, "subkind": "photo", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:49:08.819+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "959e9a77-f597-4a4a-af1d-c3a8ddb89576", "parentComponentId": null }, { "bbox": null, "kind": "metric", "text": "North American Achievers who re-worked strategy and cloud plans: 80%", "attrs": null, "canon": { "kind": { "name": "Metric", "slug": "metric", "status": "active", "canonId": "019de52c-f923-73bf-8081-d0b1a8c5264d", "version": 1, "description": "Big-number or KPI value." }, "tool": { "name": "Quantification", "slug": "quantification", "status": "active", "bestFor": null, "canonId": "019dd9e1-47ab-72ce-a079-aab1f5299e88", "version": 1, "bodyDocId": null, "description": "Translating a claim into numbers, charts, or tables.", "familyLabel": null }, "subkind": null, "framework": null }, "subkind": "primary", "groupRole": null, "confidence": null, "extraction": { "at": "2026-04-23 22:42:37+00", "model": "claude-code-default", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "019dd951-9f64-72ba-b3fe-fba1ba8744b8", "parentComponentId": null }, { "bbox": { "h": 0.15, "w": 0.22, "x": 0.28, "y": 0.6 }, "kind": "paragraph", "text": "To extract value from their data quickly and effectively, Achievers in North America are 72% more likely, on average, than Experimenters to either develop custom-built machine learning applications or work with a partner.", "attrs": null, "canon": { "kind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "5f2affc0-941d-4d07-959d-4bfc1930cea4", "version": 1, "description": "Single prose block in the body of a slide." }, "tool": null, "subkind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "019de52c-fb80-75af-aa5c-a7a4bfac2433", "version": 1, "description": null }, "framework": null }, "subkind": "paragraph", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:49:08.819+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "3ae6c6e1-d4c8-4b5f-a7e8-e0d09af02a91", "parentComponentId": null }, { "bbox": { "h": 0.2, "w": 0.22, "x": 0.28, "y": 0.3 }, "kind": "paragraph", "text": "To build AI cores, Achievers harness the power of internal and external data... 80% of North America-based organizations (vs. 75% globally) have already re-worked their strategy and cloud plans to achieve AI success.", "attrs": null, "canon": { "kind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "5f2affc0-941d-4d07-959d-4bfc1930cea4", "version": 1, "description": "Single prose block in the body of a slide." }, "tool": null, "subkind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "019de52c-fb80-75af-aa5c-a7a4bfac2433", "version": 1, "description": null }, "framework": null }, "subkind": "paragraph", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:49:08.819+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "44355adc-3037-4b37-9fec-a464e14b4ec0", "parentComponentId": null }, { "bbox": { "h": 0.2, "w": 0.22, "x": 0.05, "y": 0.3 }, "kind": "paragraph", "text": "Another priority for Achievers involves building an AI core: an operational data and AI platform that taps into company talent, technology and data ecosystems, allowing firms to balance experimentation and execution.", "attrs": null, "canon": { "kind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "5f2affc0-941d-4d07-959d-4bfc1930cea4", "version": 1, "description": "Single prose block in the body of a slide." }, "tool": null, "subkind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "019de52c-fb80-75af-aa5c-a7a4bfac2433", "version": 1, "description": null }, "framework": null }, "subkind": "paragraph", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:49:08.819+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "58adb911-ddd7-415a-aaa0-b465ca7073bd", "parentComponentId": null }, { "bbox": { "h": 0.2, "w": 0.22, "x": 0.05, "y": 0.55 }, "kind": "paragraph", "text": "An AI core also works across the cloud continuum (e.g. from migration to innovation), provides end-to-end data capabilities (foundation, management and governance), manages the machine learning lifecycle.", "attrs": null, "canon": { "kind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "5f2affc0-941d-4d07-959d-4bfc1930cea4", "version": 1, "description": "Single prose block in the body of a slide." }, "tool": null, "subkind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "019de52c-fb80-75af-aa5c-a7a4bfac2433", "version": 1, "description": null }, "framework": null }, "subkind": "paragraph", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:49:08.819+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "68150538-c803-484a-98fb-60cda6114bfc", "parentComponentId": null }, { "bbox": { "h": 0.1, "w": 0.4, "x": 0.05, "y": 0.15 }, "kind": "title", "text": "Industrialize AI tools and teams to create an AI core", "attrs": null, "canon": { "kind": { "name": "Title", "slug": "title", "status": "active", "canonId": "019de52c-f7dd-76d9-b848-b1f12bd85cf4", "version": 1, "description": "Slide title or headline." }, "tool": null, "subkind": { "name": "Headline", "slug": "headline", "status": "active", "canonId": "019de52c-fae1-7463-9a7c-d60668eced0d", "version": 1, "description": null }, "framework": null }, "subkind": "headline", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:49:08.819+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "baaa2907-7aa6-4bad-93c2-03f43eef9d15", "parentComponentId": null }, { "bbox": { "h": 0.03, "w": 0.2, "x": 0.05, "y": 0.1 }, "kind": "title", "text": "Success Factor 03", "attrs": null, "canon": { "kind": { "name": "Title", "slug": "title", "status": "active", "canonId": "019de52c-f7dd-76d9-b848-b1f12bd85cf4", "version": 1, "description": "Slide title or headline." }, "tool": null, "subkind": { "name": "Subtitle", "slug": "subtitle", "status": "active", "canonId": "019de52c-fb09-739d-900c-815b0d9ac526", "version": 1, "description": null }, "framework": null }, "subkind": "subtitle", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:49:08.819+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "d21a4d01-203b-47e0-9255-ee2a374a8611", "parentComponentId": null } ], "metrics": [ { "metricRaw": "North American Achievers who re-worked strategy and cloud plans", "numberRaw": "80%", "numberKind": "percent", "actionTitle": "Industrialize AI tools and teams to create an AI core", "calloutText": "Achievers in North America are 72% more likely, on average, than Experimenters to either develop custom-built machine learning applications or work with a partner that offers solutions-as-a-service.", "numberScale": null, "numberValue": 80, "metricFamily": "other", "numberCurrency": null } ], "tools": [ { "tool": { "name": "Action Titles", "slug": "action-titles", "status": "active", "bestFor": "Any decision-grade deliverable — strategy recommendation, board update, investment memo, M&A review, post-mortem — where the reader is being asked to agree, decide, or act and will skim the title bar at speed.", "canonId": "019dd956-ac70-700b-a608-ba58e78f5dcc", "version": 1, "bodyDocId": "816dad3c-9983-41c1-a86e-978ebd582841", "description": "The McKinsey-bred discipline of writing every slide title as a complete declarative sentence with a verb and an insight, not a topic label. Each title is a sub-claim that ladders up to the deck's governing thought; read in sequence, the titles reconstruct the executive summary.", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Architect", "layer": "slide", "agents": [ "Architect" ], "matchId": "019dd95a-0f08-73d3-987d-2913f03ac63f", "evidence": "Action title 'Industrialize AI tools and teams to create an AI core'.", "pageRefs": null, "priority": "Core", "whenToUse": "Any decision-grade deliverable — strategy recommendation, board update, investment memo, M&A review, post-mortem — where the reader is being asked to agree, decide, or act and will skim the title bar at speed.", "confidence": 90, "extraction": { "at": "2026-04-29 13:07:31.336924+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 24, "whyItWorks": "Solves two failure modes at once. (1) The buried claim: action titles place the conclusion on the page before any analysis is read, so a busy reader doesn't reverse-engineer it from the chart. (2) The spineless deck: because each title is a claim, slides have to ladder up to the governing thought; logical gaps become visible as topic-shaped titles in a sequence that no longer reads as a story.", "antipattern": "Topic labels disguised as titles — Volume by quarter, Key findings, Pricing strategy, Margins have been impacted. No verb, or a passive verb with no agent, or a fact (Revenue grew 12%) without the so-what. Also: titles that overreach the chart's evidence, multi-claim X-grew-but-Y-fell welded titles, and mechanical repetition of the same X-drove-Y template across the deck.", "cardinality": null, "narrativePurpose": "Forces the deck to carry its argument in the title bar so a senior reader can extract the recommendation without opening a single slide; converts a binder of topics into a navigable pyramid where every slide is a node defending the apex." }, { "tool": { "name": "Audience Definition", "slug": "audience-definition", "status": "active", "bestFor": null, "canonId": "019dd956-7f2a-775d-aeee-ff099bcb7756", "version": 1, "bodyDocId": null, "description": "Six key questions: Who are they? What do they know? What do they believe? What do they care about? What do they fear? What decisions can they make?", "familyLabel": null, "categoryName": "Block", "categorySlug": "block" }, "agent": "Storyteller", "layer": "slide", "agents": [ "Storyteller" ], "matchId": "c8aa27d3-563e-4128-bbdf-320c0d876da6", "evidence": "To extract value from their data quickly and effectively, Achievers in North America are 72% more likely, on average, than Experimenters to either develop custom-built machine learning applications...", "pageRefs": null, "priority": "Core", "whenToUse": null, "confidence": 0.7, "extraction": { "at": "2026-07-16 21:02:24.203124+00", "model": "or:meta-llama/llama-4-scout", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 24, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "Concrete Language", "slug": "concrete-language", "status": "active", "bestFor": null, "canonId": "019dd956-bcd4-7398-9723-6aa72346170b", "version": 1, "bodyDocId": null, "description": "Using specific sensory details instead of abstract terms", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Storyteller", "layer": "slide", "agents": [ "Storyteller" ], "matchId": "019dd95a-0f08-73d3-987d-2c17b3c3b92a", "evidence": "80% callout; 72% more likely vs Experimenters.", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 85, "extraction": { "at": "2026-04-29 13:07:31.336924+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 24, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "Data Story Arc", "slug": "data-story-arc", "status": "active", "bestFor": null, "canonId": "019dd956-9c30-728e-b974-d3fb123dcf5a", "version": 1, "bodyDocId": null, "description": "Context → Conflict → Insight → Implication structure for data narratives", "familyLabel": null, "categoryName": "Loop", "categorySlug": "loop" }, "agent": "Storyteller", "layer": "slide", "agents": [ "Storyteller" ], "matchId": "26b43720-735e-4a65-be0d-419b059f8028", "evidence": "To build AI cores, Achievers harness the power of internal and external data... 80% of North America-based organizations (vs. 75% globally) have already re-worked their strategy and cloud plans to ac", "pageRefs": null, "priority": "Core", "whenToUse": null, "confidence": 0.6, "extraction": { "at": "2026-07-16 21:02:24.243176+00", "model": "or:meta-llama/llama-4-scout", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 24, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null } ], "frameworks": [], "arcBeats": [ { "to": 28, "arc": { "name": "The Consultant's Gambit", "slug": "consultants-gambit", "status": "active", "bestFor": "Business cases, project proposals, strategic recommendations", "canonId": "019dd956-5e0a-73c8-b305-81c38c959e9c", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "Situation & Context -> Problem & Complication -> Solution & Approach -> Evidence & Proof -> Impact & Next Steps", "description": null, "familyLabel": null }, "from": 18, "name": "Solution & Approach", "beatId": "019dd95a-0682-776c-8e32-9637b6b2b41d", "matchId": "019dd95a-0542-7728-a78e-666792080e8f", "beatType": { "name": "Evidence & Proof", "slug": "consultants-gambit-evidence-proof", "status": "active", "canonId": "019dd9b8-07b1-7688-8e1e-7637fec3802a", "version": 1, "description": null }, "evidence": "Five success factors: leadership, talent, AI core, responsible AI, investment.", "position": 4, "isPrimaryArc": true, "parentBeatType": { "name": "Evidence", "slug": "evidence", "status": "active", "canonId": "019dd9b8-03f9-772a-b84a-4f07b415b77a", "version": 1, "description": "A dedicated proof beat exists in only ~4 arcs (Gambit, Sequoia, AIDA, Monroes). Other arcs embed evidence inline within development." }, "alignedBlockIds": null, "matchConfidence": 88 }, { "to": 32, "arc": { "name": "The Triple Take", "slug": "triple-take", "status": "active", "bestFor": "Data-driven presentations, research findings", "canonId": "019dd956-6221-73ad-bc12-378f8eb1f018", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "The Facts (What) -> The Implications (So What) -> The Action (Now What)", "description": null, "familyLabel": null }, "from": 18, "name": "The Action (Now What)", "beatId": "019dd95a-0682-776c-8e32-a6c160fdc8c9", "matchId": "019dd95a-0542-7728-a78e-68cfbfb51150", "beatType": { "name": "The Action (Now What)", "slug": "triple-take-the-action-now-what", "status": "active", "canonId": "019dd9b8-0a5e-735a-bf53-3a1ba629b7aa", "version": 1, "description": null }, "evidence": "Five success factors plus C-suite self-assessment.", "position": 3, "isPrimaryArc": false, "parentBeatType": { "name": "Resolution", "slug": "resolution", "status": "active", "canonId": "019dd9b8-045d-703b-8dd7-e92aba3ba91b", "version": 1, "description": "How the deck ends. Required in 19/20 arcs. The exception (Sparkline) ends with new bliss which is functionally a resolution." }, "alignedBlockIds": null, "matchConfidence": 60 } ], "loops": [ { "to": 28, "from": 20, "loop": { "name": "40_mece_breakdown", "slug": "40-mece-breakdown", "status": "active", "bestFor": "Problem structuring, ensuring completeness, strategic analysis", "canonId": "019dd956-763c-765e-8b68-6ee3ae1ef184", "version": 1, "bodyDocId": "019df22a-2420-77be-bc41-ded96d08cb21", "structure": "The Whole -> Category A (distinct) -> Category B (distinct) -> Category C (distinct) -> Complete Coverage", "description": "Divide a complex topic into mutually exclusive, collectively exhaustive categories", "familyLabel": null }, "matchId": "019dd95a-07fe-70ce-8d3a-633fdd7803ae", "evidence": "Five labelled 'Success Factor 0X' sections each pairing recommendation + case study.", "position": 5, "objective": "Lay out five MECE success factors with evidence and cases", "confidence": 88, "extraction": { "at": "2026-04-29 13:07:29.547081+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null } } ], "locked": true }, { "page": 25, "type": "evidence", "title": "The slide uses a split layout with a large photo on the left and text-based case studies on the right.", "function": "illustrate_case", "rawType": "case_study", "block": null, "metadata": { "slideType": "case_study", "slideTypeCanon": { "name": "Case study", "slug": "case_study", "status": "active", "canonId": "019de52d-0b95-7344-8090-926f3b8e92c8", "version": 1, "description": null }, "function": "illustrate_case", "functionCanon": { "name": "Illustrate case", "slug": "illustrate_case", "status": "active", "canonId": "019de52d-13b4-772c-bb73-1873612a7463", "version": 1, "description": null }, "density": "dense", "densityScore": 74, "componentCount": 7, "textChars": 1638, "nDataPoints": 3, "notes": "The slide uses a split layout with a large photo on the left and text-based case studies on the right.", "elementsJson": [ "paragraph", "photo" ], "confidence": 1, "extraction": { "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "at": "2026-05-02 19:49:09.175+00", "seconds": 3.348, "promptVersion": "v2-canon-conditioned" } }, "links": { "slide": "/slides/019dd923-5ca1-7489-b633-7fa84bbf490b/25", "deck": "/decks/019dd923-5ca1-7489-b633-7fa84bbf490b", "deckAnchor": "/decks/019dd923-5ca1-7489-b633-7fa84bbf490b#slide-25", "deckJson": "/decks/019dd923-5ca1-7489-b633-7fa84bbf490b.json" }, "components": [ { "bbox": null, "kind": "callout", "text": "By industrializing its AI tools and teams, the company targeted efficiency gains of 5% in its first year alone, with longer-term cost savings of more than $100 million annually.", "attrs": null, "canon": { "kind": { "name": "Callout", "slug": "callout", "status": "active", "canonId": "019de52c-f8d3-761a-8953-7d37080de5e2", "version": 1, "description": "Highlighted callout box." }, "tool": { "name": "Visual emphasis", "slug": "visual-emphasis", "status": "active", "bestFor": null, "canonId": "019dd9e1-474b-736b-a8eb-a794dd88241c", "version": 1, "bodyDocId": null, "description": "Drawing the eye to one element above the rest of the slide.", "familyLabel": null }, "subkind": null, "framework": null }, "subkind": null, "groupRole": null, "confidence": null, "extraction": { "at": "2026-04-23 22:42:41+00", "model": "claude-code-default", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "019dd951-9f64-72ba-b3ff-18034e48cd08", "parentComponentId": null }, { "bbox": { "h": 0.87, "w": 0.45, "x": 0.03, "y": 0.05 }, "kind": "image", "text": null, "attrs": null, "canon": { "kind": { "name": "Image", "slug": "image", "status": "active", "canonId": "019de52c-f978-701f-a720-51d029d769e7", "version": 1, "description": "Photo, illustration, screenshot or icon." }, "tool": null, "subkind": { "name": "Photo", "slug": "photo", "status": "active", "canonId": "019de52c-fd37-757f-b4a8-ca26d4888875", "version": 1, "description": null }, "framework": null }, "subkind": "photo", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:49:09.175+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "02fddca4-0097-4c2b-b280-8256c100d3ee", "parentComponentId": null }, { "bbox": null, "kind": "metric", "text": "long-term cost savings: $100 million annually", "attrs": null, "canon": { "kind": { "name": "Metric", "slug": "metric", "status": "active", "canonId": "019de52c-f923-73bf-8081-d0b1a8c5264d", "version": 1, "description": "Big-number or KPI value." }, "tool": { "name": "Quantification", "slug": "quantification", "status": "active", "bestFor": null, "canonId": "019dd9e1-47ab-72ce-a079-aab1f5299e88", "version": 1, "bodyDocId": null, "description": "Translating a claim into numbers, charts, or tables.", "familyLabel": null }, "subkind": null, "framework": null }, "subkind": "primary", "groupRole": null, "confidence": null, "extraction": { "at": "2026-04-23 22:42:41+00", "model": "claude-code-default", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "019dd951-9f64-72ba-b3ff-1fa63954daf0", "parentComponentId": null }, { "bbox": { "h": 0.15, "w": 0.21, "x": 0.51, "y": 0.1 }, "kind": "paragraph", "text": "Achievers are also more likely than Innovators to use AI for innovation, tapping into readily available developer networks that can swiftly productionize and scale successful pilots.", "attrs": null, "canon": { "kind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "5f2affc0-941d-4d07-959d-4bfc1930cea4", "version": 1, "description": "Single prose block in the body of a slide." }, "tool": null, "subkind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "019de52c-fb80-75af-aa5c-a7a4bfac2433", "version": 1, "description": null }, "framework": null }, "subkind": "paragraph", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:49:09.175+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "08647fb3-e91e-43dc-8af4-0788f5f9cc0e", "parentComponentId": null }, { "bbox": { "h": 0.2, "w": 0.21, "x": 0.74, "y": 0.1 }, "kind": "paragraph", "text": "As part of its wider data and AI transformation, A US-based food company plans to pilot a data and analytics factory scale platform. Once formalized, this effort will help support alerts, transparency and collaboration; increase agility and responsiveness; and ultimately drive revenue uplift.", "attrs": null, "canon": { "kind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "5f2affc0-941d-4d07-959d-4bfc1930cea4", "version": 1, "description": "Single prose block in the body of a slide." }, "tool": null, "subkind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "019de52c-fb80-75af-aa5c-a7a4bfac2433", "version": 1, "description": null }, "framework": null }, "subkind": "paragraph", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:49:09.175+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "0ef6970f-8304-490e-869d-cea4f282e854", "parentComponentId": null }, { "bbox": { "h": 0.28, "w": 0.21, "x": 0.74, "y": 0.34 }, "kind": "paragraph", "text": "To strengthen their AI cores, Achievers often collaborate with external experts to stay on top of breakthroughs in science and engineering. In 2020, for example, American Express partnered with the Indian Institute of Technology Madras to create a data analytics, risk and technology laboratory at the prestigious university. Such innovation ecosystems help Achievers develop AI apps tailored specifically to their needs and to help keep up with consumer demands.", "attrs": null, "canon": { "kind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "5f2affc0-941d-4d07-959d-4bfc1930cea4", "version": 1, "description": "Single prose block in the body of a slide." }, "tool": null, "subkind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "019de52c-fb80-75af-aa5c-a7a4bfac2433", "version": 1, "description": null }, "framework": null }, "subkind": "paragraph", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:49:09.175+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "18dd579b-f043-4b5c-9c5a-58f7a9342480", "parentComponentId": null }, { "bbox": { "h": 0.35, "w": 0.21, "x": 0.51, "y": 0.27 }, "kind": "paragraph", "text": "A major insurer used to rely on its employees to manually administer claims—a tedious process that cost more than $500 million annually. The company explored native cloud-storage systems and AI with the goal to store, analyze and track images and other unstructured data to support claims processing. By industrializing its AI tools and teams, the company targeted efficiency gains of 5% in its first year alone, with longer-term cost savings of more than $100 million annually.", "attrs": null, "canon": { "kind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "5f2affc0-941d-4d07-959d-4bfc1930cea4", "version": 1, "description": "Single prose block in the body of a slide." }, "tool": null, "subkind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "019de52c-fb80-75af-aa5c-a7a4bfac2433", "version": 1, "description": null }, "framework": null }, "subkind": "paragraph", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:49:09.175+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "232f3bf2-d411-4a0d-a4b9-079b02d39394", "parentComponentId": null } ], "metrics": [ { "metricRaw": "long-term cost savings", "numberRaw": "$100 million annually", "numberKind": "money", "actionTitle": "Achievers are also more likely than Innovators to use AI for innovation, tapping into readily available developer networks that can swiftly productionize and scale successful pilots.", "calloutText": "By industrializing its AI tools and teams, the company targeted efficiency gains of 5% in its first year alone, with longer-term cost savings of more than $100 million annually.", "numberScale": "m", "numberValue": 100, "metricFamily": "cost_savings", "numberCurrency": "$" } ], "tools": [ { "tool": { "name": "Concrete Language", "slug": "concrete-language", "status": "active", "bestFor": null, "canonId": "019dd956-bcd4-7398-9723-6aa72346170b", "version": 1, "bodyDocId": null, "description": "Using specific sensory details instead of abstract terms", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Storyteller", "layer": "slide", "agents": [ "Storyteller" ], "matchId": "019dd95a-0f08-73d3-987d-30d7e81c1df1", "evidence": "5% Y1 efficiency, $100M annual savings target.", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 85, "extraction": { "at": "2026-04-29 13:07:31.336924+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 25, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "Story Moments", "slug": "story-moments", "status": "active", "bestFor": null, "canonId": "019dd956-ae4e-768d-a18b-108e6cda511e", "version": 1, "bodyDocId": null, "description": "Design key emotional beats: The Shock, The Vision, The Proof, The Choice, The Call", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Storyteller", "layer": "slide", "agents": [ "Storyteller" ], "matchId": "019dd95a-0f08-73d3-987d-36c1894bde7b", "evidence": "Industrialization case quantified with savings figure.", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 70, "extraction": { "at": "2026-04-29 13:07:31.336924+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 25, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null } ], "frameworks": [], "arcBeats": [ { "to": 28, "arc": { "name": "The Consultant's Gambit", "slug": "consultants-gambit", "status": "active", "bestFor": "Business cases, project proposals, strategic recommendations", "canonId": "019dd956-5e0a-73c8-b305-81c38c959e9c", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "Situation & Context -> Problem & Complication -> Solution & Approach -> Evidence & Proof -> Impact & Next Steps", "description": null, "familyLabel": null }, "from": 18, "name": "Solution & Approach", "beatId": "019dd95a-0682-776c-8e32-9637b6b2b41d", "matchId": "019dd95a-0542-7728-a78e-666792080e8f", "beatType": { "name": "Evidence & Proof", "slug": "consultants-gambit-evidence-proof", "status": "active", "canonId": "019dd9b8-07b1-7688-8e1e-7637fec3802a", "version": 1, "description": null }, "evidence": "Five success factors: leadership, talent, AI core, responsible AI, investment.", "position": 4, "isPrimaryArc": true, "parentBeatType": { "name": "Evidence", "slug": "evidence", "status": "active", "canonId": "019dd9b8-03f9-772a-b84a-4f07b415b77a", "version": 1, "description": "A dedicated proof beat exists in only ~4 arcs (Gambit, Sequoia, AIDA, Monroes). Other arcs embed evidence inline within development." }, "alignedBlockIds": null, "matchConfidence": 88 }, { "to": 32, "arc": { "name": "The Triple Take", "slug": "triple-take", "status": "active", "bestFor": "Data-driven presentations, research findings", "canonId": "019dd956-6221-73ad-bc12-378f8eb1f018", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "The Facts (What) -> The Implications (So What) -> The Action (Now What)", "description": null, "familyLabel": null }, "from": 18, "name": "The Action (Now What)", "beatId": "019dd95a-0682-776c-8e32-a6c160fdc8c9", "matchId": "019dd95a-0542-7728-a78e-68cfbfb51150", "beatType": { "name": "The Action (Now What)", "slug": "triple-take-the-action-now-what", "status": "active", "canonId": "019dd9b8-0a5e-735a-bf53-3a1ba629b7aa", "version": 1, "description": null }, "evidence": "Five success factors plus C-suite self-assessment.", "position": 3, "isPrimaryArc": false, "parentBeatType": { "name": "Resolution", "slug": "resolution", "status": "active", "canonId": "019dd9b8-045d-703b-8dd7-e92aba3ba91b", "version": 1, "description": "How the deck ends. Required in 19/20 arcs. The exception (Sparkline) ends with new bliss which is functionally a resolution." }, "alignedBlockIds": null, "matchConfidence": 60 } ], "loops": [ { "to": 28, "from": 20, "loop": { "name": "40_mece_breakdown", "slug": "40-mece-breakdown", "status": "active", "bestFor": "Problem structuring, ensuring completeness, strategic analysis", "canonId": "019dd956-763c-765e-8b68-6ee3ae1ef184", "version": 1, "bodyDocId": "019df22a-2420-77be-bc41-ded96d08cb21", "structure": "The Whole -> Category A (distinct) -> Category B (distinct) -> Category C (distinct) -> Complete Coverage", "description": "Divide a complex topic into mutually exclusive, collectively exhaustive categories", "familyLabel": null }, "matchId": "019dd95a-07fe-70ce-8d3a-633fdd7803ae", "evidence": "Five labelled 'Success Factor 0X' sections each pairing recommendation + case study.", "position": 5, "objective": "Lay out five MECE success factors with evidence and cases", "confidence": 88, "extraction": { "at": "2026-04-29 13:07:29.547081+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null } } ], "locked": true }, { "page": 26, "type": "setup", "title": "Success Factor 04 from 'The art of AI maturity - North America' report.", "function": "summarize", "rawType": "key_messages", "block": null, "metadata": { "slideType": "key_messages", "slideTypeCanon": { "name": "Key messages", "slug": "key_messages", "status": "active", "canonId": "019de52d-0712-703f-89f5-bda6688faf3f", "version": 1, "description": null }, "function": "summarize", "functionCanon": { "name": "Summarize", "slug": "summarize", "status": "active", "canonId": "019de52d-1541-704f-b86f-bf7b75056373", "version": 1, "description": null }, "density": "overcrowded", "densityScore": 78, "componentCount": 8, "textChars": 1174, "nDataPoints": 2, "notes": "Success Factor 04 from 'The art of AI maturity - North America' report.", "elementsJson": [ "headline_text", "subtitle_text", "action_title", "paragraph", "photo" ], "confidence": 1, "extraction": { "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "at": "2026-05-02 21:24:35.65+00", "seconds": 3.229, "promptVersion": "v2-canon-conditioned" } }, "links": { "slide": "/slides/019dd923-5ca1-7489-b633-7fa84bbf490b/26", "deck": "/decks/019dd923-5ca1-7489-b633-7fa84bbf490b", "deckAnchor": "/decks/019dd923-5ca1-7489-b633-7fa84bbf490b#slide-26", "deckJson": "/decks/019dd923-5ca1-7489-b633-7fa84bbf490b.json" }, "components": [ { "bbox": null, "kind": "callout", "text": "Nearly all (97%) respondents believed that regulation will impact them to some extent, and 77% indicated that compliance is a company-wide priority.", "attrs": null, "canon": { "kind": { "name": "Callout", "slug": "callout", "status": "active", "canonId": "019de52c-f8d3-761a-8953-7d37080de5e2", "version": 1, "description": "Highlighted callout box." }, "tool": { "name": "Visual emphasis", "slug": "visual-emphasis", "status": "active", "bestFor": null, "canonId": "019dd9e1-474b-736b-a8eb-a794dd88241c", "version": 1, "bodyDocId": null, "description": "Drawing the eye to one element above the rest of the slide.", "familyLabel": null }, "subkind": null, "framework": null }, "subkind": null, "groupRole": null, "confidence": null, "extraction": { "at": "2026-04-23 22:42:41+00", "model": "claude-code-default", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "019dd951-9f64-72ba-b3ff-362953fdd1e7", "parentComponentId": null }, { "bbox": { "h": 1, "w": 0.486, "x": 0.514, "y": 0 }, "kind": "image", "text": null, "attrs": null, "canon": { "kind": { "name": "Image", "slug": "image", "status": "active", "canonId": "019de52c-f978-701f-a720-51d029d769e7", "version": 1, "description": "Photo, illustration, screenshot or icon." }, "tool": null, "subkind": { "name": "Photo", "slug": "photo", "status": "active", "canonId": "019de52c-fd37-757f-b4a8-ca26d4888875", "version": 1, "description": null }, "framework": null }, "subkind": "photo", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 21:24:35.65+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "686593e0-1b71-4ffc-a833-05034056544b", "parentComponentId": null }, { "bbox": null, "kind": "metric", "text": "C-suite respondents who believe AI regulation will impact them: 97%", "attrs": null, "canon": { "kind": { "name": "Metric", "slug": "metric", "status": "active", "canonId": "019de52c-f923-73bf-8081-d0b1a8c5264d", "version": 1, "description": "Big-number or KPI value." }, "tool": { "name": "Quantification", "slug": "quantification", "status": "active", "bestFor": null, "canonId": "019dd9e1-47ab-72ce-a079-aab1f5299e88", "version": 1, "bodyDocId": null, "description": "Translating a claim into numbers, charts, or tables.", "familyLabel": null }, "subkind": null, "framework": null }, "subkind": "primary", "groupRole": null, "confidence": null, "extraction": { "at": "2026-04-23 22:42:41+00", "model": "claude-code-default", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "019dd951-9f64-72ba-b3ff-3b264394d25b", "parentComponentId": null }, { "bbox": { "h": 0.215, "w": 0.44, "x": 0.058, "y": 0.479 }, "kind": "paragraph", "text": "In a separate Accenture study of 850 C-suite executives, we sought to gauge attitudes toward AI regulation and assess organizations’ readiness to comply. Nearly all (97%) respondents believed that regulation will impact them to some extent, and 77% indicated that compliance is a company-wide priority. Interestingly, many organizations view AI regulation as a boon rather than a barrier to success.", "attrs": null, "canon": { "kind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "5f2affc0-941d-4d07-959d-4bfc1930cea4", "version": 1, "description": "Single prose block in the body of a slide." }, "tool": null, "subkind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "019de52c-fb80-75af-aa5c-a7a4bfac2433", "version": 1, "description": null }, "framework": null }, "subkind": "paragraph", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 21:24:35.65+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "0febafc8-45df-4573-ba31-5460c12d2406", "parentComponentId": null }, { "bbox": { "h": 0.165, "w": 0.215, "x": 0.058, "y": 0.271 }, "kind": "paragraph", "text": "As companies deploy AI for a growing range of tasks, adhering to laws, regulations and ethical norms is critical. The potential for regulatory changes in many countries makes the challenge to build a sound data and AI foundation even more daunting.", "attrs": null, "canon": { "kind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "5f2affc0-941d-4d07-959d-4bfc1930cea4", "version": 1, "description": "Single prose block in the body of a slide." }, "tool": null, "subkind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "019de52c-fb80-75af-aa5c-a7a4bfac2433", "version": 1, "description": null }, "framework": null }, "subkind": "paragraph", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 21:24:35.65+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "b22be767-cb45-4601-83df-af4102c16bd1", "parentComponentId": null }, { "bbox": { "h": 0.165, "w": 0.212, "x": 0.286, "y": 0.423 }, "kind": "paragraph", "text": "The ability to demonstrate high-quality, trustworthy AI systems that are “regulation ready” will give first movers a significant advantage in the short and long term, enabling them to attract new customers, retain existing ones and build investor confidence.", "attrs": null, "canon": { "kind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "5f2affc0-941d-4d07-959d-4bfc1930cea4", "version": 1, "description": "Single prose block in the body of a slide." }, "tool": null, "subkind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "019de52c-fb80-75af-aa5c-a7a4bfac2433", "version": 1, "description": null }, "framework": null }, "subkind": "paragraph", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 21:24:35.65+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "fa14fc83-fd68-4b22-8832-67f0f56cf851", "parentComponentId": null }, { "bbox": { "h": 0.045, "w": 0.44, "x": 0.058, "y": 0.175 }, "kind": "title", "text": "Design AI responsibly, from the start", "attrs": null, "canon": { "kind": { "name": "Title", "slug": "title", "status": "active", "canonId": "019de52c-f7dd-76d9-b848-b1f12bd85cf4", "version": 1, "description": "Slide title or headline." }, "tool": null, "subkind": { "name": "Headline", "slug": "headline", "status": "active", "canonId": "019de52c-fae1-7463-9a7c-d60668eced0d", "version": 1, "description": null }, "framework": null }, "subkind": "headline", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 21:24:35.65+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "db34fae3-450f-405b-8e32-87ec7e227892", "parentComponentId": null }, { "bbox": { "h": 0.033, "w": 0.205, "x": 0.058, "y": 0.102 }, "kind": "title", "text": "Success Factor 04", "attrs": null, "canon": { "kind": { "name": "Title", "slug": "title", "status": "active", "canonId": "019de52c-f7dd-76d9-b848-b1f12bd85cf4", "version": 1, "description": "Slide title or headline." }, "tool": null, "subkind": { "name": "Subtitle", "slug": "subtitle", "status": "active", "canonId": "019de52c-fb09-739d-900c-815b0d9ac526", "version": 1, "description": null }, "framework": null }, "subkind": "subtitle", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 21:24:35.65+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "3897425a-d192-47a8-a8bb-278d408b4fb7", "parentComponentId": null } ], "metrics": [ { "metricRaw": "C-suite respondents who believe AI regulation will impact them", "numberRaw": "97%", "numberKind": "percent", "actionTitle": "Design AI responsibly, from the start", "calloutText": "Nearly all (97%) respondents believed that regulation will impact them to some extent, and 77% indicated that compliance is a company-wide priority.", "numberScale": null, "numberValue": 97, "metricFamily": "survey_sentiment", "numberCurrency": null } ], "tools": [ { "tool": { "name": "Action Titles", "slug": "action-titles", "status": "active", "bestFor": "Any decision-grade deliverable — strategy recommendation, board update, investment memo, M&A review, post-mortem — where the reader is being asked to agree, decide, or act and will skim the title bar at speed.", "canonId": "019dd956-ac70-700b-a608-ba58e78f5dcc", "version": 1, "bodyDocId": "816dad3c-9983-41c1-a86e-978ebd582841", "description": "The McKinsey-bred discipline of writing every slide title as a complete declarative sentence with a verb and an insight, not a topic label. Each title is a sub-claim that ladders up to the deck's governing thought; read in sequence, the titles reconstruct the executive summary.", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Architect", "layer": "slide", "agents": [ "Architect" ], "matchId": "019dd95a-0f08-73d3-987d-3bc14e2deefe", "evidence": "Action title 'Design AI responsibly, from the start'.", "pageRefs": null, "priority": "Core", "whenToUse": "Any decision-grade deliverable — strategy recommendation, board update, investment memo, M&A review, post-mortem — where the reader is being asked to agree, decide, or act and will skim the title bar at speed.", "confidence": 90, "extraction": { "at": "2026-04-29 13:07:31.336924+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 26, "whyItWorks": "Solves two failure modes at once. (1) The buried claim: action titles place the conclusion on the page before any analysis is read, so a busy reader doesn't reverse-engineer it from the chart. (2) The spineless deck: because each title is a claim, slides have to ladder up to the governing thought; logical gaps become visible as topic-shaped titles in a sequence that no longer reads as a story.", "antipattern": "Topic labels disguised as titles — Volume by quarter, Key findings, Pricing strategy, Margins have been impacted. No verb, or a passive verb with no agent, or a fact (Revenue grew 12%) without the so-what. Also: titles that overreach the chart's evidence, multi-claim X-grew-but-Y-fell welded titles, and mechanical repetition of the same X-drove-Y template across the deck.", "cardinality": null, "narrativePurpose": "Forces the deck to carry its argument in the title bar so a senior reader can extract the recommendation without opening a single slide; converts a binder of topics into a navigable pyramid where every slide is a node defending the apex." }, { "tool": { "name": "Concrete Language", "slug": "concrete-language", "status": "active", "bestFor": null, "canonId": "019dd956-bcd4-7398-9723-6aa72346170b", "version": 1, "bodyDocId": null, "description": "Using specific sensory details instead of abstract terms", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Storyteller", "layer": "slide", "agents": [ "Storyteller" ], "matchId": "019dd95a-0f08-73d3-987d-3e9a29f85584", "evidence": "97% expect regulatory impact; 77% say company-wide priority.", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 85, "extraction": { "at": "2026-04-29 13:07:31.336924+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 26, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null } ], "frameworks": [], "arcBeats": [ { "to": 28, "arc": { "name": "The Consultant's Gambit", "slug": "consultants-gambit", "status": "active", "bestFor": "Business cases, project proposals, strategic recommendations", "canonId": "019dd956-5e0a-73c8-b305-81c38c959e9c", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "Situation & Context -> Problem & Complication -> Solution & Approach -> Evidence & Proof -> Impact & Next Steps", "description": null, "familyLabel": null }, "from": 18, "name": "Solution & Approach", "beatId": "019dd95a-0682-776c-8e32-9637b6b2b41d", "matchId": "019dd95a-0542-7728-a78e-666792080e8f", "beatType": { "name": "Evidence & Proof", "slug": "consultants-gambit-evidence-proof", "status": "active", "canonId": "019dd9b8-07b1-7688-8e1e-7637fec3802a", "version": 1, "description": null }, "evidence": "Five success factors: leadership, talent, AI core, responsible AI, investment.", "position": 4, "isPrimaryArc": true, "parentBeatType": { "name": "Evidence", "slug": "evidence", "status": "active", "canonId": "019dd9b8-03f9-772a-b84a-4f07b415b77a", "version": 1, "description": "A dedicated proof beat exists in only ~4 arcs (Gambit, Sequoia, AIDA, Monroes). Other arcs embed evidence inline within development." }, "alignedBlockIds": null, "matchConfidence": 88 }, { "to": 32, "arc": { "name": "The Triple Take", "slug": "triple-take", "status": "active", "bestFor": "Data-driven presentations, research findings", "canonId": "019dd956-6221-73ad-bc12-378f8eb1f018", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "The Facts (What) -> The Implications (So What) -> The Action (Now What)", "description": null, "familyLabel": null }, "from": 18, "name": "The Action (Now What)", "beatId": "019dd95a-0682-776c-8e32-a6c160fdc8c9", "matchId": "019dd95a-0542-7728-a78e-68cfbfb51150", "beatType": { "name": "The Action (Now What)", "slug": "triple-take-the-action-now-what", "status": "active", "canonId": "019dd9b8-0a5e-735a-bf53-3a1ba629b7aa", "version": 1, "description": null }, "evidence": "Five success factors plus C-suite self-assessment.", "position": 3, "isPrimaryArc": false, "parentBeatType": { "name": "Resolution", "slug": "resolution", "status": "active", "canonId": "019dd9b8-045d-703b-8dd7-e92aba3ba91b", "version": 1, "description": "How the deck ends. Required in 19/20 arcs. The exception (Sparkline) ends with new bliss which is functionally a resolution." }, "alignedBlockIds": null, "matchConfidence": 60 } ], "loops": [ { "to": 28, "from": 20, "loop": { "name": "40_mece_breakdown", "slug": "40-mece-breakdown", "status": "active", "bestFor": "Problem structuring, ensuring completeness, strategic analysis", "canonId": "019dd956-763c-765e-8b68-6ee3ae1ef184", "version": 1, "bodyDocId": "019df22a-2420-77be-bc41-ded96d08cb21", "structure": "The Whole -> Category A (distinct) -> Category B (distinct) -> Category C (distinct) -> Complete Coverage", "description": "Divide a complex topic into mutually exclusive, collectively exhaustive categories", "familyLabel": null }, "matchId": "019dd95a-07fe-70ce-8d3a-633fdd7803ae", "evidence": "Five labelled 'Success Factor 0X' sections each pairing recommendation + case study.", "position": 5, "objective": "Lay out five MECE success factors with evidence and cases", "confidence": 88, "extraction": { "at": "2026-04-29 13:07:29.547081+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null } } ], "locked": true }, { "page": 27, "type": "evidence", "title": "The slide uses a callout box to highlight key survey statistics while providing a narrative case study on the left.", "function": "illustrate_case", "rawType": "case_study", "block": null, "metadata": { "slideType": "case_study", "slideTypeCanon": { "name": "Case study", "slug": "case_study", "status": "active", "canonId": "019de52d-0b95-7344-8090-926f3b8e92c8", "version": 1, "description": null }, "function": "illustrate_case", "functionCanon": { "name": "Illustrate case", "slug": "illustrate_case", "status": "active", "canonId": "019de52d-13b4-772c-bb73-1873612a7463", "version": 1, "description": null }, "density": "balanced", "densityScore": 41, "componentCount": 4, "textChars": 687, "nDataPoints": 4, "notes": "The slide uses a callout box to highlight key survey statistics while providing a narrative case study on the left.", "elementsJson": [ "paragraph", "callout_box", "headline_text" ], "confidence": 1, "extraction": { "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "at": "2026-05-02 19:49:08.396+00", "seconds": 2.304, "promptVersion": "v2-canon-conditioned" } }, "links": { "slide": "/slides/019dd923-5ca1-7489-b633-7fa84bbf490b/27", "deck": "/decks/019dd923-5ca1-7489-b633-7fa84bbf490b", "deckAnchor": "/decks/019dd923-5ca1-7489-b633-7fa84bbf490b#slide-27", "deckJson": "/decks/019dd923-5ca1-7489-b633-7fa84bbf490b.json" }, "components": [ { "bbox": { "h": 0.6, "w": 0.35, "x": 0.55, "y": 0.15 }, "kind": "callout", "text": "Even though only 3% of the North American companies surveyed had already implemented responsible AI practices, nearly half (45%) aspire to scale such frameworks by the end of 2024.", "attrs": null, "canon": { "kind": { "name": "Callout", "slug": "callout", "status": "active", "canonId": "019de52c-f8d3-761a-8953-7d37080de5e2", "version": 1, "description": "Highlighted callout box." }, "tool": null, "subkind": { "name": "Primary callout", "slug": "primary", "status": "active", "canonId": "019de52c-fbd1-70eb-a9ce-8997f8674c1d", "version": 1, "description": null }, "framework": null }, "subkind": "primary", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:49:08.396+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "adb0b41b-de05-46f0-b759-762cc9bf3cd0", "parentComponentId": null }, { "bbox": null, "kind": "metric", "text": "North American companies aspiring to scale responsible AI frameworks by end of 2024: 45%", "attrs": null, "canon": { "kind": { "name": "Metric", "slug": "metric", "status": "active", "canonId": "019de52c-f923-73bf-8081-d0b1a8c5264d", "version": 1, "description": "Big-number or KPI value." }, "tool": { "name": "Quantification", "slug": "quantification", "status": "active", "bestFor": null, "canonId": "019dd9e1-47ab-72ce-a079-aab1f5299e88", "version": 1, "bodyDocId": null, "description": "Translating a claim into numbers, charts, or tables.", "familyLabel": null }, "subkind": null, "framework": null }, "subkind": "primary", "groupRole": null, "confidence": null, "extraction": { "at": "2026-04-23 22:42:52+00", "model": "claude-code-default", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "019dd951-9f64-72ba-b3ff-5bf9815b6771", "parentComponentId": null }, { "bbox": { "h": 0.25, "w": 0.25, "x": 0.06, "y": 0.19 }, "kind": "paragraph", "text": "Achievers are consciously applying responsible AI with greater urgency than their peers. Achievers in North America are 47% more likely than Builders and 4 times more likely than Innovators, on average, to be \"responsible by design.\"", "attrs": null, "canon": { "kind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "5f2affc0-941d-4d07-959d-4bfc1930cea4", "version": 1, "description": "Single prose block in the body of a slide." }, "tool": null, "subkind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "019de52c-fb80-75af-aa5c-a7a4bfac2433", "version": 1, "description": null }, "framework": null }, "subkind": "paragraph", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:49:08.396+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "7dd4d8c8-edb2-41cc-8880-3ee3f09e6bb5", "parentComponentId": null }, { "bbox": { "h": 0.25, "w": 0.25, "x": 0.35, "y": 0.19 }, "kind": "paragraph", "text": "A global investment and wealth management firm understands that AI's potential for generating growth opportunities will reach greater heights when data is collected and used responsibly.", "attrs": null, "canon": { "kind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "5f2affc0-941d-4d07-959d-4bfc1930cea4", "version": 1, "description": "Single prose block in the body of a slide." }, "tool": null, "subkind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "019de52c-fb80-75af-aa5c-a7a4bfac2433", "version": 1, "description": null }, "framework": null }, "subkind": "paragraph", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:49:08.396+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "cde0a04e-a2cf-4c51-83ce-de7ea08e80d4", "parentComponentId": null } ], "metrics": [ { "metricRaw": "North American companies aspiring to scale responsible AI frameworks by end of 2024", "numberRaw": "45%", "numberKind": "percent", "actionTitle": "Even though only 3% of the North American companies surveyed had already implemented responsible AI practices, nearly half (45%) aspire to scale such frameworks by the end of 2024.", "calloutText": "Even though only 3% of the North American companies surveyed had already implemented responsible AI practices, nearly half (45%) aspire to scale such frameworks by the end of 2024.", "numberScale": null, "numberValue": 45, "metricFamily": "other", "numberCurrency": null } ], "tools": [ { "tool": { "name": "Tension Management", "slug": "tension-management", "status": "active", "bestFor": null, "canonId": "019dd956-9bd5-70ed-a5d2-1ce45853c248", "version": 1, "bodyDocId": null, "description": "Planning emotional peaks and valleys throughout the narrative", "familyLabel": null, "categoryName": "Loop", "categorySlug": "loop" }, "agent": "Storyteller", "layer": "loop", "agents": [ "Storyteller" ], "matchId": "019dd95a-0f08-73d3-987d-440ac1dc5edc", "evidence": "Contrasts current 3% with aspirational 45% to manufacture urgency.", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 60, "extraction": { "at": "2026-04-29 13:07:31.336924+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 27, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "Concrete Language", "slug": "concrete-language", "status": "active", "bestFor": null, "canonId": "019dd956-bcd4-7398-9723-6aa72346170b", "version": 1, "bodyDocId": null, "description": "Using specific sensory details instead of abstract terms", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Storyteller", "layer": "slide", "agents": [ "Storyteller" ], "matchId": "019dd95a-0f08-73d3-987d-42b6f470d066", "evidence": "Only 3% have responsible AI today vs 45% targeting it by 2024.", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 85, "extraction": { "at": "2026-04-29 13:07:31.336924+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 27, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null } ], "frameworks": [], "arcBeats": [ { "to": 28, "arc": { "name": "The Consultant's Gambit", "slug": "consultants-gambit", "status": "active", "bestFor": "Business cases, project proposals, strategic recommendations", "canonId": "019dd956-5e0a-73c8-b305-81c38c959e9c", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "Situation & Context -> Problem & Complication -> Solution & Approach -> Evidence & Proof -> Impact & Next Steps", "description": null, "familyLabel": null }, "from": 18, "name": "Solution & Approach", "beatId": "019dd95a-0682-776c-8e32-9637b6b2b41d", "matchId": "019dd95a-0542-7728-a78e-666792080e8f", "beatType": { "name": "Evidence & Proof", "slug": "consultants-gambit-evidence-proof", "status": "active", "canonId": "019dd9b8-07b1-7688-8e1e-7637fec3802a", "version": 1, "description": null }, "evidence": "Five success factors: leadership, talent, AI core, responsible AI, investment.", "position": 4, "isPrimaryArc": true, "parentBeatType": { "name": "Evidence", "slug": "evidence", "status": "active", "canonId": "019dd9b8-03f9-772a-b84a-4f07b415b77a", "version": 1, "description": "A dedicated proof beat exists in only ~4 arcs (Gambit, Sequoia, AIDA, Monroes). Other arcs embed evidence inline within development." }, "alignedBlockIds": null, "matchConfidence": 88 }, { "to": 32, "arc": { "name": "The Triple Take", "slug": "triple-take", "status": "active", "bestFor": "Data-driven presentations, research findings", "canonId": "019dd956-6221-73ad-bc12-378f8eb1f018", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "The Facts (What) -> The Implications (So What) -> The Action (Now What)", "description": null, "familyLabel": null }, "from": 18, "name": "The Action (Now What)", "beatId": "019dd95a-0682-776c-8e32-a6c160fdc8c9", "matchId": "019dd95a-0542-7728-a78e-68cfbfb51150", "beatType": { "name": "The Action (Now What)", "slug": "triple-take-the-action-now-what", "status": "active", "canonId": "019dd9b8-0a5e-735a-bf53-3a1ba629b7aa", "version": 1, "description": null }, "evidence": "Five success factors plus C-suite self-assessment.", "position": 3, "isPrimaryArc": false, "parentBeatType": { "name": "Resolution", "slug": "resolution", "status": "active", "canonId": "019dd9b8-045d-703b-8dd7-e92aba3ba91b", "version": 1, "description": "How the deck ends. Required in 19/20 arcs. The exception (Sparkline) ends with new bliss which is functionally a resolution." }, "alignedBlockIds": null, "matchConfidence": 60 } ], "loops": [ { "to": 28, "from": 20, "loop": { "name": "40_mece_breakdown", "slug": "40-mece-breakdown", "status": "active", "bestFor": "Problem structuring, ensuring completeness, strategic analysis", "canonId": "019dd956-763c-765e-8b68-6ee3ae1ef184", "version": 1, "bodyDocId": "019df22a-2420-77be-bc41-ded96d08cb21", "structure": "The Whole -> Category A (distinct) -> Category B (distinct) -> Category C (distinct) -> Complete Coverage", "description": "Divide a complex topic into mutually exclusive, collectively exhaustive categories", "familyLabel": null }, "matchId": "019dd95a-07fe-70ce-8d3a-633fdd7803ae", "evidence": "Five labelled 'Success Factor 0X' sections each pairing recommendation + case study.", "position": 5, "objective": "Lay out five MECE success factors with evidence and cases", "confidence": 88, "extraction": { "at": "2026-04-29 13:07:29.547081+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null } } ], "locked": true }, { "page": 28, "type": "resolution", "title": "Success Factor 05", "function": "summarize", "rawType": "key_takeaways", "block": null, "metadata": { "slideType": "key_takeaways", "slideTypeCanon": { "name": "Key takeaways", "slug": "key_takeaways", "status": "active", "canonId": "019de52d-06e7-7674-a891-9f7de3b11b6d", "version": 1, "description": null }, "function": "summarize", "functionCanon": { "name": "Summarize", "slug": "summarize", "status": "active", "canonId": "019de52d-1541-704f-b86f-bf7b75056373", "version": 1, "description": null }, "density": "overcrowded", "densityScore": 80, "componentCount": 8, "textChars": 1382, "nDataPoints": 3, "notes": "Success Factor 05", "elementsJson": [ "headline_text", "subtitle_text", "callout_box", "paragraph", "big_number" ], "confidence": 1, "extraction": { "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "at": "2026-05-02 19:49:09.642+00", "seconds": 3.461, "promptVersion": "v2-canon-conditioned" } }, "links": { "slide": "/slides/019dd923-5ca1-7489-b633-7fa84bbf490b/28", "deck": "/decks/019dd923-5ca1-7489-b633-7fa84bbf490b", "deckAnchor": "/decks/019dd923-5ca1-7489-b633-7fa84bbf490b#slide-28", "deckJson": "/decks/019dd923-5ca1-7489-b633-7fa84bbf490b.json" }, "components": [ { "bbox": null, "kind": "callout", "text": "In 2018, Achievers in North America devoted 11% of their total technology budgets to AI. In 2021, that rose to 25%. By 2024, they plan to devote 31%.", "attrs": null, "canon": { "kind": { "name": "Callout", "slug": "callout", "status": "active", "canonId": "019de52c-f8d3-761a-8953-7d37080de5e2", "version": 1, "description": "Highlighted callout box." }, "tool": { "name": "Visual emphasis", "slug": "visual-emphasis", "status": "active", "bestFor": null, "canonId": "019dd9e1-474b-736b-a8eb-a794dd88241c", "version": 1, "bodyDocId": null, "description": "Drawing the eye to one element above the rest of the slide.", "familyLabel": null }, "subkind": null, "framework": null }, "subkind": null, "groupRole": null, "confidence": null, "extraction": { "at": "2026-04-23 22:43:04+00", "model": "claude-code-default", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "019dd951-9f64-72ba-b3ff-c260131f5b90", "parentComponentId": null }, { "bbox": null, "kind": "metric", "text": "AI share of technology budget (Achievers, North America): 31%", "attrs": null, "canon": { "kind": { "name": "Metric", "slug": "metric", "status": "active", "canonId": "019de52c-f923-73bf-8081-d0b1a8c5264d", "version": 1, "description": "Big-number or KPI value." }, "tool": { "name": "Quantification", "slug": "quantification", "status": "active", "bestFor": null, "canonId": "019dd9e1-47ab-72ce-a079-aab1f5299e88", "version": 1, "bodyDocId": null, "description": "Translating a claim into numbers, charts, or tables.", "familyLabel": null }, "subkind": null, "framework": null }, "subkind": "primary", "groupRole": null, "confidence": null, "extraction": { "at": "2026-04-23 22:43:04+00", "model": "claude-code-default", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "019dd951-9f64-72ba-b3ff-c70ed9d23edb", "parentComponentId": null }, { "bbox": { "h": 0.255, "w": 0.215, "x": 0.742, "y": 0.345 }, "kind": "paragraph", "text": "As part of its efforts to create a more data-driven organization that can offer customers highly personalized digital service, a global retail company migrated from legacy databases to advanced cloud databases and analytics. It also built approximately 100 high-value AI products that create detailed customer profiles, help the company better optimize inventory and prices, and deliver next-generation services that will improve the lives of its valuable customers.", "attrs": null, "canon": { "kind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "5f2affc0-941d-4d07-959d-4bfc1930cea4", "version": 1, "description": "Single prose block in the body of a slide." }, "tool": null, "subkind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "019de52c-fb80-75af-aa5c-a7a4bfac2433", "version": 1, "description": null }, "framework": null }, "subkind": "paragraph", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:49:09.642+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "0aa62ce1-d8e0-4153-9511-2459129400bd", "parentComponentId": null }, { "bbox": { "h": 0.155, "w": 0.215, "x": 0.515, "y": 0.505 }, "kind": "paragraph", "text": "Achievers also understand that their AI investment journey doesn't have a finish line. There is, as they frequently note, no \"peak AI.\" For Achievers, continued investment largely involves expanding the scope of AI to deliver maximum impact, while \"cross-pollinating\" AI solutions and redeploying resources in the process.", "attrs": null, "canon": { "kind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "5f2affc0-941d-4d07-959d-4bfc1930cea4", "version": 1, "description": "Single prose block in the body of a slide." }, "tool": null, "subkind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "019de52c-fb80-75af-aa5c-a7a4bfac2433", "version": 1, "description": null }, "framework": null }, "subkind": "paragraph", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:49:09.642+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "303f193c-7c38-4c04-aab4-3c42d3b87250", "parentComponentId": null }, { "bbox": { "h": 0.115, "w": 0.215, "x": 0.515, "y": 0.345 }, "kind": "paragraph", "text": "To avoid being left behind, most companies need to increase their spending on data and AI. One reason Achievers get more out of AI is simply because they invest more in it.", "attrs": null, "canon": { "kind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "5f2affc0-941d-4d07-959d-4bfc1930cea4", "version": 1, "description": "Single prose block in the body of a slide." }, "tool": null, "subkind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "019de52c-fb80-75af-aa5c-a7a4bfac2433", "version": 1, "description": null }, "framework": null }, "subkind": "paragraph", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:49:09.642+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "d47ea24b-2f4c-4ec8-b5ab-fa8a44c02d97", "parentComponentId": null }, { "bbox": { "h": 0.215, "w": 0.268, "x": 0.173, "y": 0.318 }, "kind": "paragraph", "text": "In 2018, Achievers in North America devoted 11% of their total technology budgets to AI. In 2021, that rose to 25%. By 2024, they plan to devote 31%.", "attrs": null, "canon": { "kind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "5f2affc0-941d-4d07-959d-4bfc1930cea4", "version": 1, "description": "Single prose block in the body of a slide." }, "tool": null, "subkind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "019de52c-fb80-75af-aa5c-a7a4bfac2433", "version": 1, "description": null }, "framework": null }, "subkind": "paragraph", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:49:09.642+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "e62f37c7-dc3f-4de0-9507-204d92376c1e", "parentComponentId": null }, { "bbox": { "h": 0.092, "w": 0.415, "x": 0.515, "y": 0.198 }, "kind": "title", "text": "Prioritize long- and short-term AI investments", "attrs": null, "canon": { "kind": { "name": "Title", "slug": "title", "status": "active", "canonId": "019de52c-f7dd-76d9-b848-b1f12bd85cf4", "version": 1, "description": "Slide title or headline." }, "tool": null, "subkind": { "name": "Action title", "slug": "action-title", "status": "active", "canonId": "019de52c-fb31-734c-a0f5-a3935b73135d", "version": 1, "description": null }, "framework": null }, "subkind": "action-title", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:49:09.642+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "ee65ba9e-4743-471d-97cc-a27b1ed25266", "parentComponentId": null }, { "bbox": { "h": 0.025, "w": 0.163, "x": 0.515, "y": 0.125 }, "kind": "title", "text": "Success Factor 05", "attrs": null, "canon": { "kind": { "name": "Title", "slug": "title", "status": "active", "canonId": "019de52c-f7dd-76d9-b848-b1f12bd85cf4", "version": 1, "description": "Slide title or headline." }, "tool": null, "subkind": { "name": "Subtitle", "slug": "subtitle", "status": "active", "canonId": "019de52c-fb09-739d-900c-815b0d9ac526", "version": 1, "description": null }, "framework": null }, "subkind": "subtitle", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:49:09.642+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "cf3d0840-be9a-4393-9f31-705f1a0b8f9e", "parentComponentId": null } ], "metrics": [ { "metricRaw": "AI share of technology budget (Achievers, North America)", "numberRaw": "31%", "numberKind": "percent", "actionTitle": "Prioritize long- and short-term AI investments", "calloutText": "In 2018, Achievers in North America devoted 11% of their total technology budgets to AI. In 2021, that rose to 25%. By 2024, they plan to devote 31%.", "numberScale": null, "numberValue": 31, "metricFamily": "market_size", "numberCurrency": null } ], "tools": [ { "tool": { "name": "Action Titles", "slug": "action-titles", "status": "active", "bestFor": "Any decision-grade deliverable — strategy recommendation, board update, investment memo, M&A review, post-mortem — where the reader is being asked to agree, decide, or act and will skim the title bar at speed.", "canonId": "019dd956-ac70-700b-a608-ba58e78f5dcc", "version": 1, "bodyDocId": "816dad3c-9983-41c1-a86e-978ebd582841", "description": "The McKinsey-bred discipline of writing every slide title as a complete declarative sentence with a verb and an insight, not a topic label. Each title is a sub-claim that ladders up to the deck's governing thought; read in sequence, the titles reconstruct the executive summary.", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Architect", "layer": "slide", "agents": [ "Architect" ], "matchId": "019dd95a-0f08-73d3-987d-492757d85e68", "evidence": "Action title 'Prioritize long- and short-term AI investments'.", "pageRefs": null, "priority": "Core", "whenToUse": "Any decision-grade deliverable — strategy recommendation, board update, investment memo, M&A review, post-mortem — where the reader is being asked to agree, decide, or act and will skim the title bar at speed.", "confidence": 90, "extraction": { "at": "2026-04-29 13:07:31.336924+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 28, "whyItWorks": "Solves two failure modes at once. (1) The buried claim: action titles place the conclusion on the page before any analysis is read, so a busy reader doesn't reverse-engineer it from the chart. (2) The spineless deck: because each title is a claim, slides have to ladder up to the governing thought; logical gaps become visible as topic-shaped titles in a sequence that no longer reads as a story.", "antipattern": "Topic labels disguised as titles — Volume by quarter, Key findings, Pricing strategy, Margins have been impacted. No verb, or a passive verb with no agent, or a fact (Revenue grew 12%) without the so-what. Also: titles that overreach the chart's evidence, multi-claim X-grew-but-Y-fell welded titles, and mechanical repetition of the same X-drove-Y template across the deck.", "cardinality": null, "narrativePurpose": "Forces the deck to carry its argument in the title bar so a senior reader can extract the recommendation without opening a single slide; converts a binder of topics into a navigable pyramid where every slide is a node defending the apex." }, { "tool": { "name": "Concrete Language", "slug": "concrete-language", "status": "active", "bestFor": null, "canonId": "019dd956-bcd4-7398-9723-6aa72346170b", "version": 1, "bodyDocId": null, "description": "Using specific sensory details instead of abstract terms", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Storyteller", "layer": "slide", "agents": [ "Storyteller" ], "matchId": "019dd95a-0f08-73d3-987d-4f80b0164f8c", "evidence": "Budget share trajectory 11% -> 25% -> 31%.", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 85, "extraction": { "at": "2026-04-29 13:07:31.336924+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 28, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null } ], "frameworks": [], "arcBeats": [ { "to": 28, "arc": { "name": "The Consultant's Gambit", "slug": "consultants-gambit", "status": "active", "bestFor": "Business cases, project proposals, strategic recommendations", "canonId": "019dd956-5e0a-73c8-b305-81c38c959e9c", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "Situation & Context -> Problem & Complication -> Solution & Approach -> Evidence & Proof -> Impact & Next Steps", "description": null, "familyLabel": null }, "from": 18, "name": "Solution & Approach", "beatId": "019dd95a-0682-776c-8e32-9637b6b2b41d", "matchId": "019dd95a-0542-7728-a78e-666792080e8f", "beatType": { "name": "Evidence & Proof", "slug": "consultants-gambit-evidence-proof", "status": "active", "canonId": "019dd9b8-07b1-7688-8e1e-7637fec3802a", "version": 1, "description": null }, "evidence": "Five success factors: leadership, talent, AI core, responsible AI, investment.", "position": 4, "isPrimaryArc": true, "parentBeatType": { "name": "Evidence", "slug": "evidence", "status": "active", "canonId": "019dd9b8-03f9-772a-b84a-4f07b415b77a", "version": 1, "description": "A dedicated proof beat exists in only ~4 arcs (Gambit, Sequoia, AIDA, Monroes). Other arcs embed evidence inline within development." }, "alignedBlockIds": null, "matchConfidence": 88 }, { "to": 32, "arc": { "name": "The Triple Take", "slug": "triple-take", "status": "active", "bestFor": "Data-driven presentations, research findings", "canonId": "019dd956-6221-73ad-bc12-378f8eb1f018", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "The Facts (What) -> The Implications (So What) -> The Action (Now What)", "description": null, "familyLabel": null }, "from": 18, "name": "The Action (Now What)", "beatId": "019dd95a-0682-776c-8e32-a6c160fdc8c9", "matchId": "019dd95a-0542-7728-a78e-68cfbfb51150", "beatType": { "name": "The Action (Now What)", "slug": "triple-take-the-action-now-what", "status": "active", "canonId": "019dd9b8-0a5e-735a-bf53-3a1ba629b7aa", "version": 1, "description": null }, "evidence": "Five success factors plus C-suite self-assessment.", "position": 3, "isPrimaryArc": false, "parentBeatType": { "name": "Resolution", "slug": "resolution", "status": "active", "canonId": "019dd9b8-045d-703b-8dd7-e92aba3ba91b", "version": 1, "description": "How the deck ends. Required in 19/20 arcs. The exception (Sparkline) ends with new bliss which is functionally a resolution." }, "alignedBlockIds": null, "matchConfidence": 60 } ], "loops": [ { "to": 28, "from": 20, "loop": { "name": "40_mece_breakdown", "slug": "40-mece-breakdown", "status": "active", "bestFor": "Problem structuring, ensuring completeness, strategic analysis", "canonId": "019dd956-763c-765e-8b68-6ee3ae1ef184", "version": 1, "bodyDocId": "019df22a-2420-77be-bc41-ded96d08cb21", "structure": "The Whole -> Category A (distinct) -> Category B (distinct) -> Category C (distinct) -> Complete Coverage", "description": "Divide a complex topic into mutually exclusive, collectively exhaustive categories", "familyLabel": null }, "matchId": "019dd95a-07fe-70ce-8d3a-633fdd7803ae", "evidence": "Five labelled 'Success Factor 0X' sections each pairing recommendation + case study.", "position": 5, "objective": "Lay out five MECE success factors with evidence and cases", "confidence": 88, "extraction": { "at": "2026-04-29 13:07:29.547081+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null } } ], "locked": true }, { "page": 29, "type": "setup", "title": "The slide uses a dramatic background image to emphasize the key message.", "function": "summarize", "rawType": "thesis_headline", "block": null, "metadata": { "slideType": "thesis_headline", "slideTypeCanon": { "name": "Thesis headline", "slug": "thesis_headline", "status": "active", "canonId": "019de52d-073a-70cb-b9f6-772a597bb5af", "version": 1, "description": null }, "function": "summarize", "functionCanon": { "name": "Summarize", "slug": "summarize", "status": "active", "canonId": "019de52d-1541-704f-b86f-bf7b75056373", "version": 1, "description": null }, "density": "balanced", "densityScore": 26, "componentCount": 4, "textChars": 321, "nDataPoints": 2, "notes": "The slide uses a dramatic background image to emphasize the key message.", "elementsJson": [ "headline_text", "action_title", "photo" ], "confidence": 1, "extraction": { "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "at": "2026-05-02 19:49:09.444+00", "seconds": 2.634, "promptVersion": "v2-canon-conditioned" } }, "links": { "slide": "/slides/019dd923-5ca1-7489-b633-7fa84bbf490b/29", "deck": "/decks/019dd923-5ca1-7489-b633-7fa84bbf490b", "deckAnchor": "/decks/019dd923-5ca1-7489-b633-7fa84bbf490b#slide-29", "deckJson": "/decks/019dd923-5ca1-7489-b633-7fa84bbf490b.json" }, "components": [ { "bbox": null, "kind": "callout", "text": "The share of AI Achievers in North America will increase rapidly and significantly, nearly tripling from the current 7% to 20% by 2024.", "attrs": null, "canon": { "kind": { "name": "Callout", "slug": "callout", "status": "active", "canonId": "019de52c-f8d3-761a-8953-7d37080de5e2", "version": 1, "description": "Highlighted callout box." }, "tool": { "name": "Visual emphasis", "slug": "visual-emphasis", "status": "active", "bestFor": null, "canonId": "019dd9e1-474b-736b-a8eb-a794dd88241c", "version": 1, "bodyDocId": null, "description": "Drawing the eye to one element above the rest of the slide.", "familyLabel": null }, "subkind": null, "framework": null }, "subkind": null, "groupRole": null, "confidence": null, "extraction": { "at": "2026-04-23 22:42:58+00", "model": "claude-code-default", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "019dd951-9f64-72ba-b3ff-6fed3c6ac180", "parentComponentId": null }, { "bbox": { "h": 1, "w": 1, "x": 0, "y": 0 }, "kind": "image", "text": null, "attrs": null, "canon": { "kind": { "name": "Image", "slug": "image", "status": "active", "canonId": "019de52c-f978-701f-a720-51d029d769e7", "version": 1, "description": "Photo, illustration, screenshot or icon." }, "tool": null, "subkind": { "name": "Photo", "slug": "photo", "status": "active", "canonId": "019de52c-fd37-757f-b4a8-ca26d4888875", "version": 1, "description": null }, "framework": null }, "subkind": "photo", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:49:09.444+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "62ec1d73-c6d2-47ab-a59b-98f6b0960528", "parentComponentId": null }, { "bbox": null, "kind": "metric", "text": "Share of AI Achievers in North America by 2024: 20%", "attrs": null, "canon": { "kind": { "name": "Metric", "slug": "metric", "status": "active", "canonId": "019de52c-f923-73bf-8081-d0b1a8c5264d", "version": 1, "description": "Big-number or KPI value." }, "tool": { "name": "Quantification", "slug": "quantification", "status": "active", "bestFor": null, "canonId": "019dd9e1-47ab-72ce-a079-aab1f5299e88", "version": 1, "bodyDocId": null, "description": "Translating a claim into numbers, charts, or tables.", "familyLabel": null }, "subkind": null, "framework": null }, "subkind": "primary", "groupRole": null, "confidence": null, "extraction": { "at": "2026-04-23 22:42:58+00", "model": "claude-code-default", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "019dd951-9f64-72ba-b3ff-71fa7c301115", "parentComponentId": null }, { "bbox": { "h": 0.3, "w": 0.45, "x": 0.07, "y": 0.35 }, "kind": "title", "text": "The share of AI Achievers in North America will increase rapidly and significantly, nearly tripling from the current 7% to 20% by 2024.", "attrs": null, "canon": { "kind": { "name": "Title", "slug": "title", "status": "active", "canonId": "019de52c-f7dd-76d9-b848-b1f12bd85cf4", "version": 1, "description": "Slide title or headline." }, "tool": null, "subkind": { "name": "Action title", "slug": "action-title", "status": "active", "canonId": "019de52c-fb31-734c-a0f5-a3935b73135d", "version": 1, "description": null }, "framework": null }, "subkind": "action-title", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:49:09.444+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "f2a8a390-b353-4d23-a5a1-b35042599793", "parentComponentId": null } ], "metrics": [ { "metricRaw": "Share of AI Achievers in North America by 2024", "numberRaw": "20%", "numberKind": "percent", "actionTitle": "The share of AI Achievers in North America will increase rapidly and significantly, nearly tripling from the current 7% to 20% by 2024.", "calloutText": "The share of AI Achievers in North America will increase rapidly and significantly, nearly tripling from the current 7% to 20% by 2024.", "numberScale": null, "numberValue": 20, "metricFamily": "share_penetration", "numberCurrency": null } ], "tools": [ { "tool": { "name": "Payoff", "slug": "payoff", "status": "active", "bestFor": null, "canonId": "019dd956-a464-704b-b1a1-e1d483709f00", "version": 1, "bodyDocId": null, "description": "Delivering on earlier setup for satisfying resolution", "familyLabel": null, "categoryName": "Loop", "categorySlug": "loop" }, "agent": "Storyteller", "layer": "loop", "agents": [ "Storyteller" ], "matchId": "019dd95a-0f08-73d3-987d-5eadf790f13d", "evidence": "Delivers on the 7%->20% promise foreshadowed back on p5.", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 70, "extraction": { "at": "2026-04-29 13:07:31.336924+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 29, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "The Turn", "slug": "the-turn", "status": "active", "bestFor": null, "canonId": "019dd956-a2b1-7787-8ff6-60ba7e50b814", "version": 1, "bodyDocId": null, "description": "Pivotal moment where perspective shifts or insight emerges", "familyLabel": null, "categoryName": "Loop", "categorySlug": "loop" }, "agent": "Storyteller", "layer": "loop", "agents": [ "Storyteller" ], "matchId": "019dd95a-0f08-73d3-987d-5951407c1cdd", "evidence": "Pivot from past data to forward-looking 2024 trajectory.", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 75, "extraction": { "at": "2026-04-29 13:07:31.336924+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 29, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "Closing Techniques", "slug": "closing-techniques", "status": "active", "bestFor": null, "canonId": "019dd956-af13-774b-a4fd-7db0a3a88d51", "version": 1, "bodyDocId": null, "description": "Strong endings: Callback, challenge, vision, clear CTA, memorable line", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Storyteller", "layer": "slide", "agents": [ "Storyteller" ], "matchId": "019dd95a-0f08-73d3-987d-55f52d3b63a7", "evidence": "Vision statement designed as the deck's emotional crescendo.", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 75, "extraction": { "at": "2026-04-29 13:07:31.336924+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 29, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "Emotional Appeal", "slug": "emotional-appeal", "status": "active", "bestFor": null, "canonId": "019dd956-bde9-7668-8be7-0097678fec59", "version": 1, "bodyDocId": null, "description": "Connecting to audience feelings rather than just logic", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Storyteller", "layer": "slide", "agents": [ "Storyteller" ], "matchId": "019dd95a-0f08-73d3-987d-5377d11fdccf", "evidence": "Full-bleed silhouette with arms raised under the 7%->20% claim.", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 80, "extraction": { "at": "2026-04-29 13:07:31.336924+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 29, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "Picture Superiority Effect", "slug": "picture-superiority-effect", "status": "active", "bestFor": null, "canonId": "019dd956-c201-7014-bb58-3e85e3e11dfd", "version": 1, "bodyDocId": null, "description": "Pictures remembered 6x better than words - prioritize visuals over text", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Designer", "layer": "slide", "agents": [ "Designer" ], "matchId": "019dd95a-0f08-73d3-987d-6271fd647b61", "evidence": "Single hero image carries the whole vision statement.", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 70, "extraction": { "at": "2026-04-29 13:07:31.336924+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 29, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null } ], "frameworks": [], "arcBeats": [ { "to": 32, "arc": { "name": "The Consultant's Gambit", "slug": "consultants-gambit", "status": "active", "bestFor": "Business cases, project proposals, strategic recommendations", "canonId": "019dd956-5e0a-73c8-b305-81c38c959e9c", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "Situation & Context -> Problem & Complication -> Solution & Approach -> Evidence & Proof -> Impact & Next Steps", "description": null, "familyLabel": null }, "from": 29, "name": "Impact & Next Steps", "beatId": "019dd95a-0682-776c-8e32-99b1f355aefb", "matchId": "019dd95a-0542-7728-a78e-666792080e8f", "beatType": { "name": "Impact & Next Steps", "slug": "consultants-gambit-impact-next-steps", "status": "active", "canonId": "019dd9b8-0849-7728-9ee9-fd1609c4c655", "version": 1, "description": null }, "evidence": "7%->20% projection, 'practice makes progress', C-suite assessment table p32.", "position": 5, "isPrimaryArc": true, "parentBeatType": { "name": "Resolution", "slug": "resolution", "status": "active", "canonId": "019dd9b8-045d-703b-8dd7-e92aba3ba91b", "version": 1, "description": "How the deck ends. Required in 19/20 arcs. The exception (Sparkline) ends with new bliss which is functionally a resolution." }, "alignedBlockIds": null, "matchConfidence": 88 }, { "to": 32, "arc": { "name": "The Triple Take", "slug": "triple-take", "status": "active", "bestFor": "Data-driven presentations, research findings", "canonId": "019dd956-6221-73ad-bc12-378f8eb1f018", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "The Facts (What) -> The Implications (So What) -> The Action (Now What)", "description": null, "familyLabel": null }, "from": 18, "name": "The Action (Now What)", "beatId": "019dd95a-0682-776c-8e32-a6c160fdc8c9", "matchId": "019dd95a-0542-7728-a78e-68cfbfb51150", "beatType": { "name": "The Action (Now What)", "slug": "triple-take-the-action-now-what", "status": "active", "canonId": "019dd9b8-0a5e-735a-bf53-3a1ba629b7aa", "version": 1, "description": null }, "evidence": "Five success factors plus C-suite self-assessment.", "position": 3, "isPrimaryArc": false, "parentBeatType": { "name": "Resolution", "slug": "resolution", "status": "active", "canonId": "019dd9b8-045d-703b-8dd7-e92aba3ba91b", "version": 1, "description": "How the deck ends. Required in 19/20 arcs. The exception (Sparkline) ends with new bliss which is functionally a resolution." }, "alignedBlockIds": null, "matchConfidence": 60 } ], "loops": [ { "to": 32, "from": 29, "loop": { "name": "24_time_machine", "slug": "24-time-machine", "status": "active", "bestFor": "Vision casting, long-term strategy, investment pitches", "canonId": "019dd956-6f7f-70b2-b087-a16fe20515a7", "version": 1, "bodyDocId": "019df22a-2420-77be-bc41-ded96d08cb21", "structure": "Fast Forward to Success -> What Made It Possible -> Back to Today's Decision", "description": "Transport the audience to a future state where your solution has already succeeded", "familyLabel": null }, "matchId": "019dd95a-07fe-70ce-8d3a-67238c35e578", "evidence": "Full-bleed 7%->20% by 2024 vision slide, then C-suite questions to act now.", "position": 6, "objective": "Cast forward to 2024 vision and route back to today's assessment", "confidence": 78, "extraction": { "at": "2026-04-29 13:07:29.547081+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null } } ], "locked": true }, { "page": 30, "type": "setup", "title": "The slide uses a visual metaphor of hands shaping clay to represent the iterative nature of AI maturity.", "function": "transition", "rawType": "section_divider", "block": null, "metadata": { "slideType": "section_divider", "slideTypeCanon": { "name": "Section divider", "slug": "section_divider", "status": "active", "canonId": "019de52d-066a-7402-9554-6ae504999041", "version": 1, "description": null }, "function": "transition", "functionCanon": { "name": "Transition", "slug": "transition", "status": "active", "canonId": "019de52d-1365-7149-92aa-66df859e75fd", "version": 1, "description": null }, "density": "sparse", "densityScore": 6, "componentCount": 3, "textChars": 45, "nDataPoints": 0, "notes": "The slide uses a visual metaphor of hands shaping clay to represent the iterative nature of AI maturity.", "elementsJson": [ "headline_text", "photo" ], "confidence": 1, "extraction": { "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "at": "2026-05-02 19:49:10.746+00", "seconds": 3.874, "promptVersion": "v2-canon-conditioned" } }, "links": { "slide": "/slides/019dd923-5ca1-7489-b633-7fa84bbf490b/30", "deck": "/decks/019dd923-5ca1-7489-b633-7fa84bbf490b", "deckAnchor": "/decks/019dd923-5ca1-7489-b633-7fa84bbf490b#slide-30", "deckJson": "/decks/019dd923-5ca1-7489-b633-7fa84bbf490b.json" }, "components": [ { "bbox": { "h": 1, "w": 1, "x": 0, "y": 0 }, "kind": "image", "text": null, "attrs": null, "canon": { "kind": { "name": "Image", "slug": "image", "status": "active", "canonId": "019de52c-f978-701f-a720-51d029d769e7", "version": 1, "description": "Photo, illustration, screenshot or icon." }, "tool": null, "subkind": { "name": "Illustration", "slug": "illustration", "status": "active", "canonId": "019de52c-fe76-7772-a5ac-c0b7294d7615", "version": 1, "description": null }, "framework": null }, "subkind": "illustration", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:49:10.746+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "ca362f51-590a-46a3-9ba5-99cbdb9e46a6", "parentComponentId": null }, { "bbox": { "h": 0.08, "w": 0.58, "x": 0.21, "y": 0.48 }, "kind": "title", "text": "Practice makes progress", "attrs": null, "canon": { "kind": { "name": "Title", "slug": "title", "status": "active", "canonId": "019de52c-f7dd-76d9-b848-b1f12bd85cf4", "version": 1, "description": "Slide title or headline." }, "tool": null, "subkind": { "name": "Headline", "slug": "headline", "status": "active", "canonId": "019de52c-fae1-7463-9a7c-d60668eced0d", "version": 1, "description": null }, "framework": null }, "subkind": "headline", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:49:10.746+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "7fb88fdf-afe1-429a-8fc7-8ba09ff092c0", "parentComponentId": null }, { "bbox": { "h": 0.03, "w": 0.18, "x": 0.06, "y": 0.1 }, "kind": "title", "text": "The art of AI maturity", "attrs": null, "canon": { "kind": { "name": "Title", "slug": "title", "status": "active", "canonId": "019de52c-f7dd-76d9-b848-b1f12bd85cf4", "version": 1, "description": "Slide title or headline." }, "tool": null, "subkind": { "name": "Subtitle", "slug": "subtitle", "status": "active", "canonId": "019de52c-fb09-739d-900c-815b0d9ac526", "version": 1, "description": null }, "framework": null }, "subkind": "subtitle", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:49:10.746+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "13bcca69-c0e7-48fb-b8fa-af802de59d4c", "parentComponentId": null } ], "metrics": [], "tools": [ { "tool": { "name": "Section divider", "slug": "section-divider", "status": "active", "bestFor": null, "canonId": "019dd9e1-4c66-707d-8d1f-6e14547134c7", "version": 1, "bodyDocId": null, "description": "A transitional slide marking the start of a new section.", "familyLabel": null, "categoryName": null, "categorySlug": null }, "agent": null, "layer": "slide", "agents": null, "matchId": "dcdf4dea-6ee9-4237-88b3-3e996f6e4a52", "evidence": "Practice makes progress", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 0.8, "extraction": { "at": "2026-07-16 21:02:24.552402+00", "model": "or:meta-llama/llama-4-scout", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 30, "whyItWorks": null, "antipattern": null, "cardinality": "common", "narrativePurpose": null } ], "frameworks": [], "arcBeats": [ { "to": 32, "arc": { "name": "The Consultant's Gambit", "slug": "consultants-gambit", "status": "active", "bestFor": "Business cases, project proposals, strategic recommendations", "canonId": "019dd956-5e0a-73c8-b305-81c38c959e9c", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "Situation & Context -> Problem & Complication -> Solution & Approach -> Evidence & Proof -> Impact & Next Steps", "description": null, "familyLabel": null }, "from": 29, "name": "Impact & Next Steps", "beatId": "019dd95a-0682-776c-8e32-99b1f355aefb", "matchId": "019dd95a-0542-7728-a78e-666792080e8f", "beatType": { "name": "Impact & Next Steps", "slug": "consultants-gambit-impact-next-steps", "status": "active", "canonId": "019dd9b8-0849-7728-9ee9-fd1609c4c655", "version": 1, "description": null }, "evidence": "7%->20% projection, 'practice makes progress', C-suite assessment table p32.", "position": 5, "isPrimaryArc": true, "parentBeatType": { "name": "Resolution", "slug": "resolution", "status": "active", "canonId": "019dd9b8-045d-703b-8dd7-e92aba3ba91b", "version": 1, "description": "How the deck ends. Required in 19/20 arcs. The exception (Sparkline) ends with new bliss which is functionally a resolution." }, "alignedBlockIds": null, "matchConfidence": 88 }, { "to": 32, "arc": { "name": "The Triple Take", "slug": "triple-take", "status": "active", "bestFor": "Data-driven presentations, research findings", "canonId": "019dd956-6221-73ad-bc12-378f8eb1f018", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "The Facts (What) -> The Implications (So What) -> The Action (Now What)", "description": null, "familyLabel": null }, "from": 18, "name": "The Action (Now What)", "beatId": "019dd95a-0682-776c-8e32-a6c160fdc8c9", "matchId": "019dd95a-0542-7728-a78e-68cfbfb51150", "beatType": { "name": "The Action (Now What)", "slug": "triple-take-the-action-now-what", "status": "active", "canonId": "019dd9b8-0a5e-735a-bf53-3a1ba629b7aa", "version": 1, "description": null }, "evidence": "Five success factors plus C-suite self-assessment.", "position": 3, "isPrimaryArc": false, "parentBeatType": { "name": "Resolution", "slug": "resolution", "status": "active", "canonId": "019dd9b8-045d-703b-8dd7-e92aba3ba91b", "version": 1, "description": "How the deck ends. Required in 19/20 arcs. The exception (Sparkline) ends with new bliss which is functionally a resolution." }, "alignedBlockIds": null, "matchConfidence": 60 } ], "loops": [ { "to": 32, "from": 29, "loop": { "name": "24_time_machine", "slug": "24-time-machine", "status": "active", "bestFor": "Vision casting, long-term strategy, investment pitches", "canonId": "019dd956-6f7f-70b2-b087-a16fe20515a7", "version": 1, "bodyDocId": "019df22a-2420-77be-bc41-ded96d08cb21", "structure": "Fast Forward to Success -> What Made It Possible -> Back to Today's Decision", "description": "Transport the audience to a future state where your solution has already succeeded", "familyLabel": null }, "matchId": "019dd95a-07fe-70ce-8d3a-67238c35e578", "evidence": "Full-bleed 7%->20% by 2024 vision slide, then C-suite questions to act now.", "position": 6, "objective": "Cast forward to 2024 vision and route back to today's assessment", "confidence": 78, "extraction": { "at": "2026-04-29 13:07:29.547081+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null } } ], "locked": true }, { "page": 31, "type": "resolution", "function": "summarize", "rawType": "key_takeaways", "block": null, "metadata": { "slideType": "key_takeaways", "slideTypeCanon": { "name": "Key takeaways", "slug": "key_takeaways", "status": "active", "canonId": "019de52d-06e7-7674-a891-9f7de3b11b6d", "version": 1, "description": null }, "function": "summarize", "functionCanon": { "name": "Summarize", "slug": "summarize", "status": "active", "canonId": "019de52d-1541-704f-b86f-bf7b75056373", "version": 1, "description": null }, "density": "dense", "densityScore": 70, "componentCount": 7, "textChars": 2202, "nDataPoints": 0, "notes": null, "elementsJson": [ "headline_text", "subtitle_text", "paragraph", "callout_box" ], "confidence": 1, "extraction": { "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "at": "2026-05-02 19:49:10.543+00", "seconds": 3.551, "promptVersion": "v2-canon-conditioned" } }, "links": { "slide": "/slides/019dd923-5ca1-7489-b633-7fa84bbf490b/31", "deck": "/decks/019dd923-5ca1-7489-b633-7fa84bbf490b", "deckAnchor": "/decks/019dd923-5ca1-7489-b633-7fa84bbf490b#slide-31", "deckJson": "/decks/019dd923-5ca1-7489-b633-7fa84bbf490b.json" }, "components": [ { "bbox": { "h": 0.025, "w": 0.275, "x": 0.658, "y": 0.818 }, "kind": "callout", "text": "How can AI help you differentiate?", "attrs": null, "canon": { "kind": { "name": "Callout", "slug": "callout", "status": "active", "canonId": "019de52c-f8d3-761a-8953-7d37080de5e2", "version": 1, "description": "Highlighted callout box." }, "tool": null, "subkind": { "name": "Primary callout", "slug": "primary", "status": "active", "canonId": "019de52c-fbd1-70eb-a9ce-8997f8674c1d", "version": 1, "description": null }, "framework": null }, "subkind": "primary", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:49:10.543+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "052bebf5-5214-4d06-9b5f-21b382e1b892", "parentComponentId": null }, { "bbox": null, "kind": "callout", "text": "Those that transform will be the ones whose teams master the art of AI maturity, using cloud as the enabler, data as the driver and AI as the differentiator.", "attrs": null, "canon": { "kind": { "name": "Callout", "slug": "callout", "status": "active", "canonId": "019de52c-f8d3-761a-8953-7d37080de5e2", "version": 1, "description": "Highlighted callout box." }, "tool": { "name": "Visual emphasis", "slug": "visual-emphasis", "status": "active", "bestFor": null, "canonId": "019dd9e1-474b-736b-a8eb-a794dd88241c", "version": 1, "bodyDocId": null, "description": "Drawing the eye to one element above the rest of the slide.", "familyLabel": null }, "subkind": null, "framework": null }, "subkind": null, "groupRole": null, "confidence": null, "extraction": { "at": "2026-04-23 22:43:01+00", "model": "claude-code-default", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "019dd951-9f64-72ba-b3ff-9798e2cf8c7b", "parentComponentId": null }, { "bbox": { "h": 0.405, "w": 0.275, "x": 0.358, "y": 0.296 }, "kind": "paragraph", "text": "AI Achievers are thriving. Across industries, they've moved past cloud migration to innovation. They've capitalized on cloud's scale and computing power to tap into new data sources and widely available AI technologies. But AI alone isn't their secret to superior performance. It's how they're approaching AI that makes them different. They've established that AI maturity is as much about people as it is about technology. As much about strategy as it is about implementation. As much about responsibility as it is about agility.\n\nWhile Achievers are advanced relative to their peers, they'll set even higher standards for performance as their own maturity evolves.", "attrs": null, "canon": { "kind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "5f2affc0-941d-4d07-959d-4bfc1930cea4", "version": 1, "description": "Single prose block in the body of a slide." }, "tool": null, "subkind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "019de52c-fb80-75af-aa5c-a7a4bfac2433", "version": 1, "description": null }, "framework": null }, "subkind": "paragraph", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:49:10.543+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "4730d412-db35-46bf-9b65-4cd865546fc8", "parentComponentId": null }, { "bbox": { "h": 0.405, "w": 0.275, "x": 0.658, "y": 0.296 }, "kind": "paragraph", "text": "Every organization should be asking questions to assess its own AI maturity. To help get started, Figure 7 has some sample questions for C-suite leaders, according to Accenture's AI maturity assessment. There are also tools available to help benchmark AI maturity and establish clear paths to progress and performance.\n\nAs AI technologies become more prevalent, the future of business is going to look very different—some companies will lead the change, but the majority will be subjected to it. Those that transform will be the ones whose teams master the art of AI maturity, using cloud as the enabler, data as the driver and AI as the differentiator.", "attrs": null, "canon": { "kind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "5f2affc0-941d-4d07-959d-4bfc1930cea4", "version": 1, "description": "Single prose block in the body of a slide." }, "tool": null, "subkind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "019de52c-fb80-75af-aa5c-a7a4bfac2433", "version": 1, "description": null }, "framework": null }, "subkind": "paragraph", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:49:10.543+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "d1fbb825-114e-4303-b350-9125cd7e5248", "parentComponentId": null }, { "bbox": { "h": 0.405, "w": 0.275, "x": 0.058, "y": 0.296 }, "kind": "paragraph", "text": "By 2019, there was evidence that scaling AI beyond proofs of concept had a significant impact on ROI. Then the pandemic hit. For many organizations, enterprise-wide transformation was a means of survival. For others, it quickly became a catalyst to thrive. The US saw a spectacular recovery in overall M&A activity, powered by key partnerships focused on enhancing research and development in AI. This, coupled with the boom in overall private investment for AI-funded companies, led to the emergence of the US as an AI investment hub (leading the world in overall private investment in funded AI companies).", "attrs": null, "canon": { "kind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "5f2affc0-941d-4d07-959d-4bfc1930cea4", "version": 1, "description": "Single prose block in the body of a slide." }, "tool": null, "subkind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "019de52c-fb80-75af-aa5c-a7a4bfac2433", "version": 1, "description": null }, "framework": null }, "subkind": "paragraph", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:49:10.543+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "f31a078a-15d3-486c-b8b4-59f26af0fc73", "parentComponentId": null }, { "bbox": { "h": 0.028, "w": 0.508, "x": 0.058, "y": 0.208 }, "kind": "title", "text": "The concept of using AI to solve business problems isn't new.", "attrs": null, "canon": { "kind": { "name": "Title", "slug": "title", "status": "active", "canonId": "019de52c-f7dd-76d9-b848-b1f12bd85cf4", "version": 1, "description": "Slide title or headline." }, "tool": null, "subkind": { "name": "Action title", "slug": "action-title", "status": "active", "canonId": "019de52c-fb31-734c-a0f5-a3935b73135d", "version": 1, "description": null }, "framework": null }, "subkind": "action-title", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:49:10.543+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "9cfe50eb-a7b8-4702-87d9-0389d1ac23a0", "parentComponentId": null }, { "bbox": { "h": 0.045, "w": 0.367, "x": 0.058, "y": 0.142 }, "kind": "title", "text": "Practice makes progress", "attrs": null, "canon": { "kind": { "name": "Title", "slug": "title", "status": "active", "canonId": "019de52c-f7dd-76d9-b848-b1f12bd85cf4", "version": 1, "description": "Slide title or headline." }, "tool": null, "subkind": { "name": "Headline", "slug": "headline", "status": "active", "canonId": "019de52c-fae1-7463-9a7c-d60668eced0d", "version": 1, "description": null }, "framework": null }, "subkind": "headline", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:49:10.543+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "0751382e-57a8-4e11-9a94-8e6e85de4054", "parentComponentId": null } ], "metrics": [], "tools": [ { "tool": { "name": "Tricolon", "slug": "tricolon", "status": "active", "bestFor": null, "canonId": "019dd956-a13d-7356-9038-da27abe565f8", "version": 1, "bodyDocId": null, "description": "Three parallel phrases of increasing length or intensity", "familyLabel": null, "categoryName": "Loop", "categorySlug": "loop" }, "agent": "Storyteller", "layer": "loop", "agents": [ "Storyteller" ], "matchId": "019dd95a-0f08-73d3-987d-6f5c5ea39eb0", "evidence": "Three parallel clauses: cloud-enabler / data-driver / AI-differentiator.", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 80, "extraction": { "at": "2026-04-29 13:07:31.336924+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 31, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "Action Titles", "slug": "action-titles", "status": "active", "bestFor": "Any decision-grade deliverable — strategy recommendation, board update, investment memo, M&A review, post-mortem — where the reader is being asked to agree, decide, or act and will skim the title bar at speed.", "canonId": "019dd956-ac70-700b-a608-ba58e78f5dcc", "version": 1, "bodyDocId": "816dad3c-9983-41c1-a86e-978ebd582841", "description": "The McKinsey-bred discipline of writing every slide title as a complete declarative sentence with a verb and an insight, not a topic label. Each title is a sub-claim that ladders up to the deck's governing thought; read in sequence, the titles reconstruct the executive summary.", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Architect", "layer": "slide", "agents": [ "Architect" ], "matchId": "019dd95a-0f08-73d3-987d-679eabe98641", "evidence": "'Practice makes progress' is a memorable verbal hook.", "pageRefs": null, "priority": "Core", "whenToUse": "Any decision-grade deliverable — strategy recommendation, board update, investment memo, M&A review, post-mortem — where the reader is being asked to agree, decide, or act and will skim the title bar at speed.", "confidence": 75, "extraction": { "at": "2026-04-29 13:07:31.336924+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 31, "whyItWorks": "Solves two failure modes at once. (1) The buried claim: action titles place the conclusion on the page before any analysis is read, so a busy reader doesn't reverse-engineer it from the chart. (2) The spineless deck: because each title is a claim, slides have to ladder up to the governing thought; logical gaps become visible as topic-shaped titles in a sequence that no longer reads as a story.", "antipattern": "Topic labels disguised as titles — Volume by quarter, Key findings, Pricing strategy, Margins have been impacted. No verb, or a passive verb with no agent, or a fact (Revenue grew 12%) without the so-what. Also: titles that overreach the chart's evidence, multi-claim X-grew-but-Y-fell welded titles, and mechanical repetition of the same X-drove-Y template across the deck.", "cardinality": null, "narrativePurpose": "Forces the deck to carry its argument in the title bar so a senior reader can extract the recommendation without opening a single slide; converts a binder of topics into a navigable pyramid where every slide is a node defending the apex." }, { "tool": { "name": "Closing Techniques", "slug": "closing-techniques", "status": "active", "bestFor": null, "canonId": "019dd956-af13-774b-a4fd-7db0a3a88d51", "version": 1, "bodyDocId": null, "description": "Strong endings: Callback, challenge, vision, clear CTA, memorable line", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Storyteller", "layer": "slide", "agents": [ "Storyteller" ], "matchId": "019dd95a-0f08-73d3-987d-6a7f6b0fbd4c", "evidence": "Coined phrase plus 'cloud as enabler, data as driver, AI as differentiator' tricolon.", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 75, "extraction": { "at": "2026-04-29 13:07:31.336924+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 31, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "Core Message Extraction", "slug": "core-message-extraction", "status": "active", "bestFor": "Any slide that carries an argument or finding. The diagnostic: if the slide has a chart on it, it needs a core message. Run extraction whenever the current title is a topic (Q3 performance, Customer satisfaction) rather than a claim, or when a reader could reasonably draw more than one conclusion from the visible evidence.", "canonId": "019dd956-bc71-707d-8867-1b2e810175cf", "version": 1, "bodyDocId": "f85613cb-4b77-462f-bfe6-3b862516e1a6", "description": "The discipline of distilling raw analysis, data, or content into a single declarative sentence — the slide's core message — that the audience would walk away with if they remembered nothing else. Process, not artefact: extraction questions run on the raw content until one sentence falls out.", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Architect", "layer": "slide", "agents": [ "Architect" ], "matchId": "019dd95a-0f08-73d3-987d-73600343e645", "evidence": "Synthesises the deck thesis in a single sentence.", "pageRefs": null, "priority": null, "whenToUse": "Any slide that carries an argument or finding. The diagnostic: if the slide has a chart on it, it needs a core message. Run extraction whenever the current title is a topic (Q3 performance, Customer satisfaction) rather than a claim, or when a reader could reasonably draw more than one conclusion from the visible evidence.", "confidence": 70, "extraction": { "at": "2026-04-29 13:07:31.336924+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 31, "whyItWorks": "Solves the two failure modes of slide writing simultaneously: the topic title (which outsources interpretation to the audience and produces three different conclusions in three different heads) and the multi-thesis stapler (which exceeds working memory and gets remembered as fragments). Aligns with how readers actually consume decks — Heath & Heath's Find the Core, the journalist's nut graf, and Minto's governing thought all converge on the same cognitive economics.", "antipattern": "Topic titles disguised as core messages (Customer satisfaction, no verb, no stake); multi-thesis sentences stapled with and; hedged sentences (may show signs of possible softening); chart-caption titles (Revenue fell 4%) that restate what the chart already shows instead of naming the so-what; meta-commentary (this slide explores...) that describes the slide rather than concluding it.", "cardinality": null, "narrativePurpose": "Forces the slide author to do the interpretive work before the slide ships, so the audience does not have to do it during the meeting. Wins the WYSIATI battle on purpose — the loudest fragment on the page becomes the author's chosen sentence rather than whichever chart label happens to be largest." } ], "frameworks": [ { "matchId": "378d7092-238a-4cd5-ad30-6bc4db81fce8", "evidence": "Mentions 'AI maturity' and 'benchmark AI maturity'", "framework": null, "confidence": 0.8, "extraction": { "at": "2026-05-02 19:49:10.543+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 31, "frameworkName": "maturity-model" } ], "arcBeats": [ { "to": 32, "arc": { "name": "The Consultant's Gambit", "slug": "consultants-gambit", "status": "active", "bestFor": "Business cases, project proposals, strategic recommendations", "canonId": "019dd956-5e0a-73c8-b305-81c38c959e9c", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "Situation & Context -> Problem & Complication -> Solution & Approach -> Evidence & Proof -> Impact & Next Steps", "description": null, "familyLabel": null }, "from": 29, "name": "Impact & Next Steps", "beatId": "019dd95a-0682-776c-8e32-99b1f355aefb", "matchId": "019dd95a-0542-7728-a78e-666792080e8f", "beatType": { "name": "Impact & Next Steps", "slug": "consultants-gambit-impact-next-steps", "status": "active", "canonId": "019dd9b8-0849-7728-9ee9-fd1609c4c655", "version": 1, "description": null }, "evidence": "7%->20% projection, 'practice makes progress', C-suite assessment table p32.", "position": 5, "isPrimaryArc": true, "parentBeatType": { "name": "Resolution", "slug": "resolution", "status": "active", "canonId": "019dd9b8-045d-703b-8dd7-e92aba3ba91b", "version": 1, "description": "How the deck ends. Required in 19/20 arcs. The exception (Sparkline) ends with new bliss which is functionally a resolution." }, "alignedBlockIds": null, "matchConfidence": 88 }, { "to": 32, "arc": { "name": "The Triple Take", "slug": "triple-take", "status": "active", "bestFor": "Data-driven presentations, research findings", "canonId": "019dd956-6221-73ad-bc12-378f8eb1f018", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "The Facts (What) -> The Implications (So What) -> The Action (Now What)", "description": null, "familyLabel": null }, "from": 18, "name": "The Action (Now What)", "beatId": "019dd95a-0682-776c-8e32-a6c160fdc8c9", "matchId": "019dd95a-0542-7728-a78e-68cfbfb51150", "beatType": { "name": "The Action (Now What)", "slug": "triple-take-the-action-now-what", "status": "active", "canonId": "019dd9b8-0a5e-735a-bf53-3a1ba629b7aa", "version": 1, "description": null }, "evidence": "Five success factors plus C-suite self-assessment.", "position": 3, "isPrimaryArc": false, "parentBeatType": { "name": "Resolution", "slug": "resolution", "status": "active", "canonId": "019dd9b8-045d-703b-8dd7-e92aba3ba91b", "version": 1, "description": "How the deck ends. Required in 19/20 arcs. The exception (Sparkline) ends with new bliss which is functionally a resolution." }, "alignedBlockIds": null, "matchConfidence": 60 } ], "loops": [ { "to": 32, "from": 29, "loop": { "name": "24_time_machine", "slug": "24-time-machine", "status": "active", "bestFor": "Vision casting, long-term strategy, investment pitches", "canonId": "019dd956-6f7f-70b2-b087-a16fe20515a7", "version": 1, "bodyDocId": "019df22a-2420-77be-bc41-ded96d08cb21", "structure": "Fast Forward to Success -> What Made It Possible -> Back to Today's Decision", "description": "Transport the audience to a future state where your solution has already succeeded", "familyLabel": null }, "matchId": "019dd95a-07fe-70ce-8d3a-67238c35e578", "evidence": "Full-bleed 7%->20% by 2024 vision slide, then C-suite questions to act now.", "position": 6, "objective": "Cast forward to 2024 vision and route back to today's assessment", "confidence": 78, "extraction": { "at": "2026-04-29 13:07:29.547081+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null } } ], "locked": true }, { "page": 32, "type": "setup", "title": "The slide uses a categorization framework to structure diagnostic questions for AI maturity.", "function": "present_framework", "rawType": "appendix_methodology", "block": null, "metadata": { "slideType": "appendix_methodology", "slideTypeCanon": { "name": "Appendix methodology", "slug": "appendix_methodology", "status": "active", "canonId": "019de52d-07d9-726c-8599-167f2d2ffaa7", "version": 1, "description": null }, "function": "present_framework", "functionCanon": { "name": "Present framework", "slug": "present_framework", "status": "active", "canonId": "019de52d-1403-7667-9100-d2ac6709f750", "version": 1, "description": null }, "density": "sparse", "densityScore": 15, "componentCount": 4, "textChars": 160, "nDataPoints": 0, "notes": "The slide uses a categorization framework to structure diagnostic questions for AI maturity.", "elementsJson": [ "headline_text", "comparison_table", "bullet_list", "footnote" ], "confidence": 1, "extraction": { "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "at": "2026-05-02 19:49:09.608+00", "seconds": 2.528, "promptVersion": "v2-canon-conditioned" } }, "links": { "slide": "/slides/019dd923-5ca1-7489-b633-7fa84bbf490b/32", "deck": "/decks/019dd923-5ca1-7489-b633-7fa84bbf490b", "deckAnchor": "/decks/019dd923-5ca1-7489-b633-7fa84bbf490b#slide-32", "deckJson": "/decks/019dd923-5ca1-7489-b633-7fa84bbf490b.json" }, "components": [ { "bbox": null, "kind": "framework", "text": "AI Maturity Assessment Framework", "attrs": null, "canon": { "kind": { "name": "Framework", "slug": "framework", "status": "active", "canonId": "019de52c-fa18-77c6-b10a-ccb8277ac0fa", "version": 1, "description": "Named conceptual framework instance." }, "tool": null, "subkind": { "name": "Framework instance", "slug": "instance", "status": "active", "canonId": "019de52d-05a2-72af-be0b-7edc60708a03", "version": 1, "description": null }, "framework": null }, "subkind": "instance", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:49:09.608+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "6a9f3fc5-c288-4756-831a-391330fc37e3", "parentComponentId": null }, { "bbox": { "h": 0.02, "w": 0.15, "x": 0.08, "y": 0.86 }, "kind": "source-note", "text": "Source: Accenture Research", "attrs": null, "canon": { "kind": { "name": "Source note", "slug": "source-note", "status": "active", "canonId": "23484952-494b-4a5e-b1ad-550d0d70e948", "version": 1, "description": "Attribution / source / caveat placed at the slide footer. Numbered footnotes use attrs.numbered." }, "tool": null, "subkind": null, "framework": null }, "subkind": null, "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:49:09.608+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "b6407d7c-a7a0-4738-a6a2-c6bd9bddc8fd", "parentComponentId": null }, { "bbox": { "h": 0.75, "w": 0.84, "x": 0.08, "y": 0.12 }, "kind": "table", "text": "Category and Key questions table", "attrs": null, "canon": { "kind": { "name": "Table", "slug": "table", "status": "active", "canonId": "019de52c-f9c8-7148-8119-eaac9594cd28", "version": 1, "description": "Tabular data layout." }, "tool": null, "subkind": { "name": "Data table", "slug": "data", "status": "active", "canonId": "019de52d-02d5-75b8-8abf-88e92bf63569", "version": 1, "description": null }, "framework": null }, "subkind": "data", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:49:09.608+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "819b5fc6-4a07-4e0d-b0cc-de48481aeb1d", "parentComponentId": null }, { "bbox": { "h": 0.03, "w": 0.4, "x": 0.08, "y": 0.08 }, "kind": "title", "text": "Figure 7: AI maturity assessment: sample questions for C-suite leaders", "attrs": null, "canon": { "kind": { "name": "Title", "slug": "title", "status": "active", "canonId": "019de52c-f7dd-76d9-b848-b1f12bd85cf4", "version": 1, "description": "Slide title or headline." }, "tool": null, "subkind": { "name": "Headline", "slug": "headline", "status": "active", "canonId": "019de52c-fae1-7463-9a7c-d60668eced0d", "version": 1, "description": null }, "framework": null }, "subkind": "headline", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:49:09.608+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "b49fbc23-6398-4e03-a8b2-b10f9351e301", "parentComponentId": null } ], "metrics": [], "tools": [ { "tool": { "name": "Chunking", "slug": "chunking", "status": "active", "bestFor": null, "canonId": "019dd956-abab-72ce-b64c-2924cc83cf39", "version": 1, "bodyDocId": null, "description": "Information grouped into chunks is remembered better - structure content in digestible units", "familyLabel": null, "categoryName": "Loop", "categorySlug": "loop" }, "agent": "Architect", "layer": "loop", "agents": [ "Architect" ], "matchId": "019dd95a-0f08-73d3-987d-7cd8bc816f72", "evidence": "Questions chunked into four MECE capability buckets.", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 70, "extraction": { "at": "2026-04-29 13:07:31.336924+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 32, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "Action Titles", "slug": "action-titles", "status": "active", "bestFor": "Any decision-grade deliverable — strategy recommendation, board update, investment memo, M&A review, post-mortem — where the reader is being asked to agree, decide, or act and will skim the title bar at speed.", "canonId": "019dd956-ac70-700b-a608-ba58e78f5dcc", "version": 1, "bodyDocId": "816dad3c-9983-41c1-a86e-978ebd582841", "description": "The McKinsey-bred discipline of writing every slide title as a complete declarative sentence with a verb and an insight, not a topic label. Each title is a sub-claim that ladders up to the deck's governing thought; read in sequence, the titles reconstruct the executive summary.", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Architect", "layer": "slide", "agents": [ "Architect" ], "matchId": "019dd95a-0f08-73d3-987d-75ffc593d341", "evidence": "Figure 7 framed as 'sample questions for C-suite leaders'.", "pageRefs": null, "priority": "Core", "whenToUse": "Any decision-grade deliverable — strategy recommendation, board update, investment memo, M&A review, post-mortem — where the reader is being asked to agree, decide, or act and will skim the title bar at speed.", "confidence": 70, "extraction": { "at": "2026-04-29 13:07:31.336924+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 32, "whyItWorks": "Solves two failure modes at once. (1) The buried claim: action titles place the conclusion on the page before any analysis is read, so a busy reader doesn't reverse-engineer it from the chart. (2) The spineless deck: because each title is a claim, slides have to ladder up to the governing thought; logical gaps become visible as topic-shaped titles in a sequence that no longer reads as a story.", "antipattern": "Topic labels disguised as titles — Volume by quarter, Key findings, Pricing strategy, Margins have been impacted. No verb, or a passive verb with no agent, or a fact (Revenue grew 12%) without the so-what. Also: titles that overreach the chart's evidence, multi-claim X-grew-but-Y-fell welded titles, and mechanical repetition of the same X-drove-Y template across the deck.", "cardinality": null, "narrativePurpose": "Forces the deck to carry its argument in the title bar so a senior reader can extract the recommendation without opening a single slide; converts a binder of topics into a navigable pyramid where every slide is a node defending the apex." }, { "tool": { "name": "Gestalt Principles", "slug": "gestalt-principles", "status": "active", "bestFor": null, "canonId": "019dd956-b266-7631-9b7e-44d83bd5d4f3", "version": 1, "bodyDocId": null, "description": "Proximity, Similarity, Enclosure, Continuity, Closure, Connection - how humans perceive visual groups", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Designer", "layer": "slide", "agents": [ "Designer", "Architect" ], "matchId": "019dd95a-0f08-73d3-987d-7aa1252abdbd", "evidence": "Coloured row labels group questions by capability category.", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 70, "extraction": { "at": "2026-04-29 13:07:31.336924+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 32, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "Nudge", "slug": "nudge", "status": "active", "bestFor": null, "canonId": "019dd956-c61a-72f9-920c-88acf4ecc336", "version": 1, "bodyDocId": null, "description": "Subtle hints can significantly affect decisions - strategic CTA placement", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Designer", "layer": "slide", "agents": [ "Architect", "Designer" ], "matchId": "019dd95a-0f08-73d3-987d-8297cb9ccde8", "evidence": "Self-diagnostic questions nudge readers toward an internal audit.", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 60, "extraction": { "at": "2026-04-29 13:07:31.336924+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 32, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null } ], "frameworks": [ { "matchId": "019dd95a-1ca5-70bb-bb9f-5b9f4ef5ba08", "evidence": "Four named pillars: Strategy & Sponsorship, Data & AI Core, Talent & Culture, Responsible AI.", "framework": null, "confidence": 85, "extraction": { "at": "2026-04-29 13:07:34.826634+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 32, "frameworkName": "AI Maturity Model" }, { "matchId": "3d5d0e70-7f6c-4c77-9e9e-ea1f534d2392", "evidence": "The slide explicitly labels the content as an 'AI maturity assessment' and categorizes questions into pillars of maturity.", "framework": null, "confidence": 1, "extraction": { "at": "2026-05-02 19:49:09.608+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 32, "frameworkName": "maturity-model" } ], "arcBeats": [ { "to": 32, "arc": { "name": "The Consultant's Gambit", "slug": "consultants-gambit", "status": "active", "bestFor": "Business cases, project proposals, strategic recommendations", "canonId": "019dd956-5e0a-73c8-b305-81c38c959e9c", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "Situation & Context -> Problem & Complication -> Solution & Approach -> Evidence & Proof -> Impact & Next Steps", "description": null, "familyLabel": null }, "from": 29, "name": "Impact & Next Steps", "beatId": "019dd95a-0682-776c-8e32-99b1f355aefb", "matchId": "019dd95a-0542-7728-a78e-666792080e8f", "beatType": { "name": "Impact & Next Steps", "slug": "consultants-gambit-impact-next-steps", "status": "active", "canonId": "019dd9b8-0849-7728-9ee9-fd1609c4c655", "version": 1, "description": null }, "evidence": "7%->20% projection, 'practice makes progress', C-suite assessment table p32.", "position": 5, "isPrimaryArc": true, "parentBeatType": { "name": "Resolution", "slug": "resolution", "status": "active", "canonId": "019dd9b8-045d-703b-8dd7-e92aba3ba91b", "version": 1, "description": "How the deck ends. Required in 19/20 arcs. The exception (Sparkline) ends with new bliss which is functionally a resolution." }, "alignedBlockIds": null, "matchConfidence": 88 }, { "to": 32, "arc": { "name": "The Triple Take", "slug": "triple-take", "status": "active", "bestFor": "Data-driven presentations, research findings", "canonId": "019dd956-6221-73ad-bc12-378f8eb1f018", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "The Facts (What) -> The Implications (So What) -> The Action (Now What)", "description": null, "familyLabel": null }, "from": 18, "name": "The Action (Now What)", "beatId": "019dd95a-0682-776c-8e32-a6c160fdc8c9", "matchId": "019dd95a-0542-7728-a78e-68cfbfb51150", "beatType": { "name": "The Action (Now What)", "slug": "triple-take-the-action-now-what", "status": "active", "canonId": "019dd9b8-0a5e-735a-bf53-3a1ba629b7aa", "version": 1, "description": null }, "evidence": "Five success factors plus C-suite self-assessment.", "position": 3, "isPrimaryArc": false, "parentBeatType": { "name": "Resolution", "slug": "resolution", "status": "active", "canonId": "019dd9b8-045d-703b-8dd7-e92aba3ba91b", "version": 1, "description": "How the deck ends. Required in 19/20 arcs. The exception (Sparkline) ends with new bliss which is functionally a resolution." }, "alignedBlockIds": null, "matchConfidence": 60 } ], "loops": [ { "to": 32, "from": 29, "loop": { "name": "24_time_machine", "slug": "24-time-machine", "status": "active", "bestFor": "Vision casting, long-term strategy, investment pitches", "canonId": "019dd956-6f7f-70b2-b087-a16fe20515a7", "version": 1, "bodyDocId": "019df22a-2420-77be-bc41-ded96d08cb21", "structure": "Fast Forward to Success -> What Made It Possible -> Back to Today's Decision", "description": "Transport the audience to a future state where your solution has already succeeded", "familyLabel": null }, "matchId": "019dd95a-07fe-70ce-8d3a-67238c35e578", "evidence": "Full-bleed 7%->20% by 2024 vision slide, then C-suite questions to act now.", "position": 6, "objective": "Cast forward to 2024 vision and route back to today's assessment", "confidence": 78, "extraction": { "at": "2026-04-29 13:07:29.547081+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null } } ], "locked": true }, { "page": 33, "type": "setup", "function": "other", "rawType": "team_bio", "block": null, "metadata": { "slideType": "team_bio", "slideTypeCanon": { "name": "Team bio", "slug": "team_bio", "status": "active", "canonId": "019de52d-0a7d-7394-ae5b-037478e71f1e", "version": 1, "description": null }, "function": "other", "functionCanon": { "name": "Other (fallback)", "slug": "other", "status": "active", "canonId": "019de52d-15e1-75bc-99dc-07732380e2ce", "version": 1, "description": null }, "density": "balanced", "densityScore": 43, "componentCount": 8, "textChars": 116, "nDataPoints": 0, "notes": null, "elementsJson": [ "headline_text", "headshot", "subtitle_text" ], "confidence": 1, "extraction": { "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "at": "2026-05-02 19:49:13.1+00", "seconds": 6.02, "promptVersion": "v2-canon-conditioned" } }, "links": { "slide": "/slides/019dd923-5ca1-7489-b633-7fa84bbf490b/33", "deck": "/decks/019dd923-5ca1-7489-b633-7fa84bbf490b", "deckAnchor": "/decks/019dd923-5ca1-7489-b633-7fa84bbf490b#slide-33", "deckJson": "/decks/019dd923-5ca1-7489-b633-7fa84bbf490b.json" }, "components": [ { "bbox": { "h": 0.13, "w": 0.073, "x": 0.111, "y": 0.508 }, "kind": "image", "text": "Lan Guan", "attrs": null, "canon": { "kind": { "name": "Image", "slug": "image", "status": "active", "canonId": "019de52c-f978-701f-a720-51d029d769e7", "version": 1, "description": "Photo, illustration, screenshot or icon." }, "tool": null, "subkind": { "name": "Headshot", "slug": "headshot", "status": "active", "canonId": "019de52c-fd5f-765c-9282-38b54f61bbbf", "version": 1, "description": null }, "framework": null }, "subkind": "headshot", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:49:13.1+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "2463e0c8-2334-443e-976f-b152316fe47a", "parentComponentId": null }, { "bbox": { "h": 0.13, "w": 0.073, "x": 0.342, "y": 0.508 }, "kind": "image", "text": "Ajay Vasal", "attrs": null, "canon": { "kind": { "name": "Image", "slug": "image", "status": "active", "canonId": "019de52c-f978-701f-a720-51d029d769e7", "version": 1, "description": "Photo, illustration, screenshot or icon." }, "tool": null, "subkind": { "name": "Headshot", "slug": "headshot", "status": "active", "canonId": "019de52c-fd5f-765c-9282-38b54f61bbbf", "version": 1, "description": null }, "framework": null }, "subkind": "headshot", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:49:13.1+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "66e68fb7-9c3e-4b2f-9cb5-fa1881494f35", "parentComponentId": null }, { "bbox": { "h": 0.13, "w": 0.073, "x": 0.111, "y": 0.679 }, "kind": "image", "text": "Philippe Roussiere", "attrs": null, "canon": { "kind": { "name": "Image", "slug": "image", "status": "active", "canonId": "019de52c-f978-701f-a720-51d029d769e7", "version": 1, "description": "Photo, illustration, screenshot or icon." }, "tool": null, "subkind": { "name": "Headshot", "slug": "headshot", "status": "active", "canonId": "019de52c-fd5f-765c-9282-38b54f61bbbf", "version": 1, "description": null }, "framework": null }, "subkind": "headshot", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:49:13.1+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "758ca8f1-d4a6-40b6-a942-52dac49bd4f9", "parentComponentId": null }, { "bbox": { "h": 0.13, "w": 0.073, "x": 0.342, "y": 0.343 }, "kind": "image", "text": "Arnab Chakraborty", "attrs": null, "canon": { "kind": { "name": "Image", "slug": "image", "status": "active", "canonId": "019de52c-f978-701f-a720-51d029d769e7", "version": 1, "description": "Photo, illustration, screenshot or icon." }, "tool": null, "subkind": { "name": "Headshot", "slug": "headshot", "status": "active", "canonId": "019de52c-fd5f-765c-9282-38b54f61bbbf", "version": 1, "description": null }, "framework": null }, "subkind": "headshot", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:49:13.1+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "96de1f7e-f9ad-4415-9b4e-9a96a22635ab", "parentComponentId": null }, { "bbox": { "h": 0.13, "w": 0.073, "x": 0.111, "y": 0.348 }, "kind": "image", "text": "Sanjeev Vohra", "attrs": null, "canon": { "kind": { "name": "Image", "slug": "image", "status": "active", "canonId": "019de52c-f978-701f-a720-51d029d769e7", "version": 1, "description": "Photo, illustration, screenshot or icon." }, "tool": null, "subkind": { "name": "Headshot", "slug": "headshot", "status": "active", "canonId": "019de52c-fd5f-765c-9282-38b54f61bbbf", "version": 1, "description": null }, "framework": null }, "subkind": "headshot", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:49:13.1+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "b20df657-dc14-426b-96e5-ac42d85fb658", "parentComponentId": null }, { "bbox": { "h": 0.13, "w": 0.073, "x": 0.628, "y": 0.337 }, "kind": "image", "text": "Praveen Tanguturi", "attrs": null, "canon": { "kind": { "name": "Image", "slug": "image", "status": "active", "canonId": "019de52c-f978-701f-a720-51d029d769e7", "version": 1, "description": "Photo, illustration, screenshot or icon." }, "tool": null, "subkind": { "name": "Headshot", "slug": "headshot", "status": "active", "canonId": "019de52c-fd5f-765c-9282-38b54f61bbbf", "version": 1, "description": null }, "framework": null }, "subkind": "headshot", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:49:13.1+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "c65f4cd2-5637-4b21-9d8c-a6859701f19c", "parentComponentId": null }, { "bbox": { "h": 0.042, "w": 0.214, "x": 0.628, "y": 0.198 }, "kind": "title", "text": "Research director", "attrs": null, "canon": { "kind": { "name": "Title", "slug": "title", "status": "active", "canonId": "019de52c-f7dd-76d9-b848-b1f12bd85cf4", "version": 1, "description": "Slide title or headline." }, "tool": null, "subkind": { "name": "Headline", "slug": "headline", "status": "active", "canonId": "019de52c-fae1-7463-9a7c-d60668eced0d", "version": 1, "description": null }, "framework": null }, "subkind": "headline", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:49:13.1+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "74639bc0-8a5d-4e25-8090-b2311ab6f1cd", "parentComponentId": null }, { "bbox": { "h": 0.042, "w": 0.286, "x": 0.108, "y": 0.198 }, "kind": "title", "text": "Meet the authors", "attrs": null, "canon": { "kind": { "name": "Title", "slug": "title", "status": "active", "canonId": "019de52c-f7dd-76d9-b848-b1f12bd85cf4", "version": 1, "description": "Slide title or headline." }, "tool": null, "subkind": { "name": "Headline", "slug": "headline", "status": "active", "canonId": "019de52c-fae1-7463-9a7c-d60668eced0d", "version": 1, "description": null }, "framework": null }, "subkind": "headline", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:49:13.1+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "e51eafd4-3cf6-4a25-9b27-356603c0de4d", "parentComponentId": null } ], "metrics": [], "tools": [], "frameworks": [], "arcBeats": [], "loops": [], "locked": true }, { "page": 34, "type": "appendix", "function": "other", "rawType": "appendix", "block": null, "metadata": { "slideType": "appendix", "slideTypeCanon": { "name": "Appendix", "slug": "appendix", "status": "active", "canonId": "019de52d-0762-71f8-b564-89ab863301cc", "version": 1, "description": null }, "function": "other", "functionCanon": { "name": "Other (fallback)", "slug": "other", "status": "active", "canonId": "019de52d-15e1-75bc-99dc-07732380e2ce", "version": 1, "description": null }, "density": "dense", "densityScore": 61, "componentCount": 8, "textChars": 541, "nDataPoints": 0, "notes": null, "elementsJson": [ "headline_text", "headshot", "paragraph", "subtitle_text" ], "confidence": 1, "extraction": { "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "at": "2026-05-02 19:49:10.378+00", "seconds": 3.172, "promptVersion": "v2-canon-conditioned" } }, "links": { "slide": "/slides/019dd923-5ca1-7489-b633-7fa84bbf490b/34", "deck": "/decks/019dd923-5ca1-7489-b633-7fa84bbf490b", "deckAnchor": "/decks/019dd923-5ca1-7489-b633-7fa84bbf490b#slide-34", "deckJson": "/decks/019dd923-5ca1-7489-b633-7fa84bbf490b.json" }, "components": [ { "bbox": { "h": 0.141, "w": 0.078, "x": 0.372, "y": 0.415 }, "kind": "image", "text": null, "attrs": null, "canon": { "kind": { "name": "Image", "slug": "image", "status": "active", "canonId": "019de52c-f978-701f-a720-51d029d769e7", "version": 1, "description": "Photo, illustration, screenshot or icon." }, "tool": null, "subkind": { "name": "Headshot", "slug": "headshot", "status": "active", "canonId": "019de52c-fd5f-765c-9282-38b54f61bbbf", "version": 1, "description": null }, "framework": null }, "subkind": "headshot", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:49:10.378+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "7953ad99-62f5-46ee-bf83-02a2ad7a17b0", "parentComponentId": null }, { "bbox": { "h": 0.141, "w": 0.078, "x": 0.108, "y": 0.415 }, "kind": "image", "text": null, "attrs": null, "canon": { "kind": { "name": "Image", "slug": "image", "status": "active", "canonId": "019de52c-f978-701f-a720-51d029d769e7", "version": 1, "description": "Photo, illustration, screenshot or icon." }, "tool": null, "subkind": { "name": "Headshot", "slug": "headshot", "status": "active", "canonId": "019de52c-fd5f-765c-9282-38b54f61bbbf", "version": 1, "description": null }, "framework": null }, "subkind": "headshot", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:49:10.378+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "85d3578c-6d6e-4603-b95c-61a7aa6fb4c3", "parentComponentId": null }, { "bbox": { "h": 0.051, "w": 0.115, "x": 0.453, "y": 0.418 }, "kind": "paragraph", "text": "Yuhui Xiong, Research Manager", "attrs": null, "canon": { "kind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "5f2affc0-941d-4d07-959d-4bfc1930cea4", "version": 1, "description": "Single prose block in the body of a slide." }, "tool": null, "subkind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "019de52c-fb80-75af-aa5c-a7a4bfac2433", "version": 1, "description": null }, "framework": null }, "subkind": "paragraph", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:49:10.378+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "a6717cb2-ab35-4a11-8dc0-9b4712a28322", "parentComponentId": null }, { "bbox": { "h": 0.085, "w": 0.415, "x": 0.108, "y": 0.609 }, "kind": "paragraph", "text": "Contributors: Rahul Basole, Mariusz Bidelski, Marcin Bodziak, Tomas Castagnino, Joe Depa, Ray Eitel-Porter, Michelle Ganchinho, Michal Hadrys, Andy Hickl, David Kimble, Carrie Kleiner, Andra Najem, Linda Ringnalda, Paridhi Sharma, Joanna Syczewska, Ezequiel Tacsir, Jonathan Thomas, Jakub Wiatrak and Yingchuan Zhu.", "attrs": null, "canon": { "kind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "5f2affc0-941d-4d07-959d-4bfc1930cea4", "version": 1, "description": "Single prose block in the body of a slide." }, "tool": null, "subkind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "019de52c-fb80-75af-aa5c-a7a4bfac2433", "version": 1, "description": null }, "framework": null }, "subkind": "paragraph", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:49:10.378+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "b187c5ba-79d9-487e-ab8f-0f45ed9674d1", "parentComponentId": null }, { "bbox": { "h": 0.042, "w": 0.415, "x": 0.108, "y": 0.739 }, "kind": "paragraph", "text": "Marketing + Communications: Alisyn Abney, Surabhi Chatterjee, Spurti Devadhar, Alexa Mouta, Karthick Paulraj and Venkat Subramanian.", "attrs": null, "canon": { "kind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "5f2affc0-941d-4d07-959d-4bfc1930cea4", "version": 1, "description": "Single prose block in the body of a slide." }, "tool": null, "subkind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "019de52c-fb80-75af-aa5c-a7a4bfac2433", "version": 1, "description": null }, "framework": null }, "subkind": "paragraph", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:49:10.378+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "bef2655e-d755-4fb6-ac8b-9465a52043a5", "parentComponentId": null }, { "bbox": { "h": 0.051, "w": 0.115, "x": 0.189, "y": 0.418 }, "kind": "paragraph", "text": "Deeksha Khare Patnaik, Research Manager", "attrs": null, "canon": { "kind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "5f2affc0-941d-4d07-959d-4bfc1930cea4", "version": 1, "description": "Single prose block in the body of a slide." }, "tool": null, "subkind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "019de52c-fb80-75af-aa5c-a7a4bfac2433", "version": 1, "description": null }, "framework": null }, "subkind": "paragraph", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:49:10.378+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "bfc659a9-a90e-434b-9086-fa17f9db7a6f", "parentComponentId": null }, { "bbox": { "h": 0.042, "w": 0.175, "x": 0.108, "y": 0.198 }, "kind": "title", "text": "Contributors", "attrs": null, "canon": { "kind": { "name": "Title", "slug": "title", "status": "active", "canonId": "019de52c-f7dd-76d9-b848-b1f12bd85cf4", "version": 1, "description": "Slide title or headline." }, "tool": null, "subkind": { "name": "Headline", "slug": "headline", "status": "active", "canonId": "019de52c-fae1-7463-9a7c-d60668eced0d", "version": 1, "description": null }, "framework": null }, "subkind": "headline", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:49:10.378+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "cba85637-5b4e-4972-a650-f7099e39a4ee", "parentComponentId": null }, { "bbox": { "h": 0.018, "w": 0.095, "x": 0.108, "y": 0.351 }, "kind": "title", "text": "Research Leads", "attrs": null, "canon": { "kind": { "name": "Title", "slug": "title", "status": "active", "canonId": "019de52c-f7dd-76d9-b848-b1f12bd85cf4", "version": 1, "description": "Slide title or headline." }, "tool": null, "subkind": { "name": "Subtitle", "slug": "subtitle", "status": "active", "canonId": "019de52c-fb09-739d-900c-815b0d9ac526", "version": 1, "description": null }, "framework": null }, "subkind": "subtitle", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:49:10.378+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "b121bee0-09f6-407b-8626-b325c6fad81d", "parentComponentId": null } ], "metrics": [], "tools": [], "frameworks": [], "arcBeats": [], "loops": [], "locked": true }, { "page": 35, "type": "appendix", "title": "Includes specific regression model notation and details on K-fold cross-validation.", "function": "appendix", "rawType": "appendix_methodology", "block": null, "metadata": { "slideType": "appendix_methodology", "slideTypeCanon": { "name": "Appendix methodology", "slug": "appendix_methodology", "status": "active", "canonId": "019de52d-07d9-726c-8599-167f2d2ffaa7", "version": 1, "description": null }, "function": "appendix", "functionCanon": { "name": "Appendix", "slug": "appendix", "status": "active", "canonId": "019de52d-138d-750b-83c3-49b4bc7a7a38", "version": 1, "description": null }, "density": "dense", "densityScore": 66, "componentCount": 7, "textChars": 748, "nDataPoints": 6, "notes": "Includes specific regression model notation and details on K-fold cross-validation.", "elementsJson": [ "headline_text", "paragraph", "callout_box", "numbered_list" ], "confidence": 1, "extraction": { "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "at": "2026-05-02 19:49:10.638+00", "seconds": 3.08, "promptVersion": "v2-canon-conditioned" } }, "links": { "slide": "/slides/019dd923-5ca1-7489-b633-7fa84bbf490b/35", "deck": "/decks/019dd923-5ca1-7489-b633-7fa84bbf490b", "deckAnchor": "/decks/019dd923-5ca1-7489-b633-7fa84bbf490b#slide-35", "deckJson": "/decks/019dd923-5ca1-7489-b633-7fa84bbf490b.json" }, "components": [ { "bbox": { "h": 0.25, "w": 0.22, "x": 0.51, "y": 0.18 }, "kind": "callout", "text": "R_i represents the level and evolution of a company's AI-influenced revenues... The model is a linear probability Lasso model, a K-fold cross-validation with 10 folds performed.", "attrs": null, "canon": { "kind": { "name": "Callout", "slug": "callout", "status": "active", "canonId": "019de52c-f8d3-761a-8953-7d37080de5e2", "version": 1, "description": "Highlighted callout box." }, "tool": null, "subkind": { "name": "Primary callout", "slug": "primary", "status": "active", "canonId": "019de52c-fbd1-70eb-a9ce-8997f8674c1d", "version": 1, "description": null }, "framework": null }, "subkind": "primary", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:49:10.638+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "b31a4aac-10c8-43f1-ae70-a056cde3aecd", "parentComponentId": null }, { "bbox": { "h": 0.1, "w": 0.18, "x": 0.32, "y": 0.77 }, "kind": "callout", "text": "R_i = β_0 + β_1 X_it + β_2 Capabilities_it-1 + β_3 ΔCapabilities_it + β_4 Capabilities Interactions_it,t-1 + e_it", "attrs": null, "canon": { "kind": { "name": "Callout", "slug": "callout", "status": "active", "canonId": "019de52c-f8d3-761a-8953-7d37080de5e2", "version": 1, "description": "Highlighted callout box." }, "tool": null, "subkind": { "name": "Primary callout", "slug": "primary", "status": "active", "canonId": "019de52c-fbd1-70eb-a9ce-8997f8674c1d", "version": 1, "description": null }, "framework": null }, "subkind": "primary", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:49:10.638+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "e0911c83-85e2-4194-849e-7999e8633031", "parentComponentId": null }, { "bbox": null, "kind": "callout", "text": "The median maturity index of all companies is 36/100.", "attrs": null, "canon": { "kind": { "name": "Callout", "slug": "callout", "status": "active", "canonId": "019de52c-f8d3-761a-8953-7d37080de5e2", "version": 1, "description": "Highlighted callout box." }, "tool": { "name": "Visual emphasis", "slug": "visual-emphasis", "status": "active", "bestFor": null, "canonId": "019dd9e1-474b-736b-a8eb-a794dd88241c", "version": 1, "bodyDocId": null, "description": "Drawing the eye to one element above the rest of the slide.", "familyLabel": null }, "subkind": null, "framework": null }, "subkind": null, "groupRole": null, "confidence": null, "extraction": { "at": "2026-04-23 22:43:33+00", "model": "claude-code-default", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "019dd951-9f64-72ba-b400-196c8fbab3f8", "parentComponentId": null }, { "bbox": { "h": 0.7, "w": 0.25, "x": 0.05, "y": 0.18 }, "kind": "list", "text": "Survey: 1,615 C-suite executives, 16 industries, 15 countries. Interviews: 25 CEOs/CDOs/CAOs, academic experts, 40+ case studies. Design thinking: MURAL session with 15 senior data scientists.", "attrs": null, "canon": { "kind": { "name": "List", "slug": "list", "status": "active", "canonId": "019de52c-f94b-779b-a53b-fd4904a5f4d2", "version": 1, "description": "Bullet or numbered list." }, "tool": null, "subkind": { "name": "Bullet list", "slug": "bullet", "status": "active", "canonId": "019de52c-fc98-7169-a083-5cab805076ca", "version": 1, "description": null }, "framework": null }, "subkind": "bullet", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:49:10.638+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "334575a2-620d-4eff-b01a-bf6465e44832", "parentComponentId": null }, { "bbox": null, "kind": "metric", "text": "Median maturity index: 36/100", "attrs": null, "canon": { "kind": { "name": "Metric", "slug": "metric", "status": "active", "canonId": "019de52c-f923-73bf-8081-d0b1a8c5264d", "version": 1, "description": "Big-number or KPI value." }, "tool": { "name": "Quantification", "slug": "quantification", "status": "active", "bestFor": null, "canonId": "019dd9e1-47ab-72ce-a079-aab1f5299e88", "version": 1, "bodyDocId": null, "description": "Translating a claim into numbers, charts, or tables.", "familyLabel": null }, "subkind": null, "framework": null }, "subkind": "primary", "groupRole": null, "confidence": null, "extraction": { "at": "2026-04-23 22:43:33+00", "model": "claude-code-default", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "019dd951-9f64-72ba-b400-1c60caccd62d", "parentComponentId": null }, { "bbox": { "h": 0.7, "w": 0.63, "x": 0.32, "y": 0.18 }, "kind": "paragraph", "text": "Economic modeling and data science: 1. Identified key capabilities of AI maturity. 2. Defined 'foundational' and 'differentiation' capabilities. 3. Built the AI maturity index.", "attrs": null, "canon": { "kind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "5f2affc0-941d-4d07-959d-4bfc1930cea4", "version": 1, "description": "Single prose block in the body of a slide." }, "tool": null, "subkind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "019de52c-fb80-75af-aa5c-a7a4bfac2433", "version": 1, "description": null }, "framework": null }, "subkind": "paragraph", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:49:10.638+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "2472d2f3-f287-4132-8647-e9429b50a4d9", "parentComponentId": null }, { "bbox": { "h": 0.05, "w": 0.15, "x": 0.05, "y": 0.1 }, "kind": "title", "text": "Appendix", "attrs": null, "canon": { "kind": { "name": "Title", "slug": "title", "status": "active", "canonId": "019de52c-f7dd-76d9-b848-b1f12bd85cf4", "version": 1, "description": "Slide title or headline." }, "tool": null, "subkind": { "name": "Headline", "slug": "headline", "status": "active", "canonId": "019de52c-fae1-7463-9a7c-d60668eced0d", "version": 1, "description": null }, "framework": null }, "subkind": "headline", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:49:10.638+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "082b35ee-1a4a-4c8f-85a2-1e116fad33a2", "parentComponentId": null } ], "metrics": [ { "metricRaw": "Median maturity index", "numberRaw": "36/100", "numberKind": "plain", "actionTitle": null, "calloutText": "The median maturity index of all companies is 36/100.", "numberScale": null, "numberValue": 36, "metricFamily": "index_score", "numberCurrency": null } ], "tools": [ { "tool": { "name": "Concrete Language", "slug": "concrete-language", "status": "active", "bestFor": null, "canonId": "019dd956-bcd4-7398-9723-6aa72346170b", "version": 1, "bodyDocId": null, "description": "Using specific sensory details instead of abstract terms", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Storyteller", "layer": "slide", "agents": [ "Storyteller" ], "matchId": "019dd95a-0f08-73d3-987d-84e76c6be040", "evidence": "Median maturity index of 36/100 quoted in callout.", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 70, "extraction": { "at": "2026-04-29 13:07:31.336924+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 35, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null } ], "frameworks": [ { "matchId": "f454066a-9439-477b-9de4-cc73c40e3880", "evidence": "Description of regression modeling and K-fold cross-validation", "framework": null, "confidence": 0.9, "extraction": { "at": "2026-05-02 19:49:10.638+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 35, "frameworkName": "analytical-method" } ], "arcBeats": [], "loops": [], "locked": true }, { "page": 36, "type": "setup", "title": "This slide details the analytical approach for a study on AI maturity, specifically focusing on clustering, regression modeling, and NLP-based trend analysis.", "function": "summarize", "rawType": "appendix_methodology", "block": null, "metadata": { "slideType": "appendix_methodology", "slideTypeCanon": { "name": "Appendix methodology", "slug": "appendix_methodology", "status": "active", "canonId": "019de52d-07d9-726c-8599-167f2d2ffaa7", "version": 1, "description": null }, "function": "summarize", "functionCanon": { "name": "Summarize", "slug": "summarize", "status": "active", "canonId": "019de52d-1541-704f-b86f-bf7b75056373", "version": 1, "description": null }, "density": "sparse", "densityScore": 24, "componentCount": 3, "textChars": 472, "nDataPoints": 0, "notes": "This slide details the analytical approach for a study on AI maturity, specifically focusing on clustering, regression modeling, and NLP-based trend analysis.", "elementsJson": [ "headline_text", "bullet_list", "paragraph", "numbered_list" ], "confidence": 1, "extraction": { "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "at": "2026-05-02 19:49:09.948+00", "seconds": 2.265, "promptVersion": "v2-canon-conditioned" } }, "links": { "slide": "/slides/019dd923-5ca1-7489-b633-7fa84bbf490b/36", "deck": "/decks/019dd923-5ca1-7489-b633-7fa84bbf490b", "deckAnchor": "/decks/019dd923-5ca1-7489-b633-7fa84bbf490b#slide-36", "deckJson": "/decks/019dd923-5ca1-7489-b633-7fa84bbf490b.json" }, "components": [ { "bbox": null, "kind": "callout", "text": "The difference between Achievers and other companies is highly statistically significant (p < 0.01) for customer experience and sustainability.", "attrs": null, "canon": { "kind": { "name": "Callout", "slug": "callout", "status": "active", "canonId": "019de52c-f8d3-761a-8953-7d37080de5e2", "version": 1, "description": "Highlighted callout box." }, "tool": { "name": "Visual emphasis", "slug": "visual-emphasis", "status": "active", "bestFor": null, "canonId": "019dd9e1-474b-736b-a8eb-a794dd88241c", "version": 1, "bodyDocId": null, "description": "Drawing the eye to one element above the rest of the slide.", "familyLabel": null }, "subkind": null, "framework": null }, "subkind": null, "groupRole": null, "confidence": null, "extraction": { "at": "2026-04-23 22:43:30+00", "model": "claude-code-default", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "019dd951-9f64-72ba-b3ff-ff4b9759130e", "parentComponentId": null }, { "bbox": { "h": 0.8, "w": 0.9, "x": 0.05, "y": 0.1 }, "kind": "list", "text": "4. Constructed AI profiles based on foundational and differentiation capabilities. 5. Measured Achievers' financial premium. 6. Measured Achievers' stakeholder performance. 7. Measured the speed of AI transformation vs. the speed of digital transformation.", "attrs": null, "canon": { "kind": { "name": "List", "slug": "list", "status": "active", "canonId": "019de52c-f94b-779b-a53b-fd4904a5f4d2", "version": 1, "description": "Bullet or numbered list." }, "tool": null, "subkind": { "name": "Bullet list", "slug": "bullet", "status": "active", "canonId": "019de52c-fc98-7169-a083-5cab805076ca", "version": 1, "description": null }, "framework": null }, "subkind": "bullet", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:49:09.948+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "6631f89c-dfa3-41cc-8744-b8f80ce52a1d", "parentComponentId": null }, { "bbox": null, "kind": "metric", "text": "AI Achievers foundational & differentiation median maturity index: 64/100", "attrs": null, "canon": { "kind": { "name": "Metric", "slug": "metric", "status": "active", "canonId": "019de52c-f923-73bf-8081-d0b1a8c5264d", "version": 1, "description": "Big-number or KPI value." }, "tool": { "name": "Quantification", "slug": "quantification", "status": "active", "bestFor": null, "canonId": "019dd9e1-47ab-72ce-a079-aab1f5299e88", "version": 1, "bodyDocId": null, "description": "Translating a claim into numbers, charts, or tables.", "familyLabel": null }, "subkind": null, "framework": null }, "subkind": "primary", "groupRole": null, "confidence": null, "extraction": { "at": "2026-04-23 22:43:30+00", "model": "claude-code-default", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "019dd951-9f64-72ba-b400-03037419297a", "parentComponentId": null } ], "metrics": [ { "metricRaw": "AI Achievers foundational & differentiation median maturity index", "numberRaw": "64/100", "numberKind": "plain", "actionTitle": null, "calloutText": "The difference between Achievers and other companies is highly statistically significant (p < 0.01) for customer experience and sustainability.", "numberScale": null, "numberValue": 64, "metricFamily": "index_score", "numberCurrency": null } ], "tools": [ { "tool": { "name": "Authority Bias", "slug": "authority-bias", "status": "active", "bestFor": null, "canonId": "019dd956-c38d-70b9-a284-b2b479763356", "version": 1, "bodyDocId": null, "description": "Expert opinions are weighted more heavily - cite credible sources", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Storyteller", "layer": "slide", "agents": [ "Architect", "Storyteller" ], "matchId": "019dd95a-0f08-73d3-987d-8e40eb36dfe4", "evidence": "Statistical-significance language adds methodological credibility.", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 65, "extraction": { "at": "2026-04-29 13:07:31.336924+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 36, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "Concrete Language", "slug": "concrete-language", "status": "active", "bestFor": null, "canonId": "019dd956-bcd4-7398-9723-6aa72346170b", "version": 1, "bodyDocId": null, "description": "Using specific sensory details instead of abstract terms", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Storyteller", "layer": "slide", "agents": [ "Storyteller" ], "matchId": "019dd95a-0f08-73d3-987d-8a56f27d2031", "evidence": "p < 0.01 significance for CX and sustainability differences.", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 70, "extraction": { "at": "2026-04-29 13:07:31.336924+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 36, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null } ], "frameworks": [ { "matchId": "ff1a1e4f-08c7-48ce-a58a-52295c1abe5c", "evidence": "The slide outlines the specific statistical and analytical steps taken to derive study conclusions.", "framework": null, "confidence": 0.9, "extraction": { "at": "2026-05-02 19:49:09.948+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 36, "frameworkName": "analytical-method" } ], "arcBeats": [], "loops": [], "locked": true }, { "page": 37, "type": "setup", "title": "The slide presents a numbered list of 10 capabilities, though the formatting is slightly fragmented across columns.", "function": "present_framework", "rawType": "initiative_list", "block": null, "metadata": { "slideType": "initiative_list", "slideTypeCanon": { "name": "Initiative list", "slug": "initiative_list", "status": "active", "canonId": "019de52d-0caf-770e-9b91-b99239121f50", "version": 1, "description": null }, "function": "present_framework", "functionCanon": { "name": "Present framework", "slug": "present_framework", "status": "active", "canonId": "019de52d-1403-7667-9100-d2ac6709f750", "version": 1, "description": null }, "density": "balanced", "densityScore": 40, "componentCount": 2, "textChars": 2524, "nDataPoints": 0, "notes": "The slide presents a numbered list of 10 capabilities, though the formatting is slightly fragmented across columns.", "elementsJson": [ "headline_text", "numbered_list", "paragraph" ], "confidence": 0.9, "extraction": { "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "at": "2026-05-02 19:49:10.678+00", "seconds": 2.981, "promptVersion": "v2-canon-conditioned" } }, "links": { "slide": "/slides/019dd923-5ca1-7489-b633-7fa84bbf490b/37", "deck": "/decks/019dd923-5ca1-7489-b633-7fa84bbf490b", "deckAnchor": "/decks/019dd923-5ca1-7489-b633-7fa84bbf490b#slide-37", "deckJson": "/decks/019dd923-5ca1-7489-b633-7fa84bbf490b.json" }, "components": [ { "bbox": null, "kind": "list", "text": "1. Senior Sponsorship: Organizations have an AI strategy that is developed by the Chief Analytics Officer, Chief Data Officer, Chief Digital Officer or an equivalent. The CEO and the Board actively sponsor and share accountability for the strategy and associated AI initiatives.\n2. AI Strategy: Organizations not only have a core AI strategy aligned to the overall business strategy, but they also dedicate tools and tactics to execute it and continuously track their performance against that strategy.\n3. Proactive vs. Reactive: Organizations have the resources (such as technology, talent and patents) to proactively define and demonstrate how AI can create value vs. apply AI as a reaction to a need. They're first-movers instead of fast followers in terms of applying AI for business value.\n4. Readily Available AI and ML tools: Organizations work with an ecosystem of technology partners to access machine learning models and tools to help innovate new products and services.\n5. Readily Available Developer Networks: Organizations tap into an ecosystem of technology partners to access developer networks that support the development of new products and services.\n6. Build vs. Buy: Organizations develop custom-built AI applications or work with a partner who offers solutions-as-a-service, vs. purchase “off-the-shelf” AI solutions with little-to-no customization.\n7. Platform and Technology: Organizations apply the necessary cloud, data and AI infrastructure, software, self-serve capabilities and industry best practices, and they adopt the latest tools available from platform and technology partners.\n8. Experimentation Data—Change: Organizations improved their use of experimentation data between 2018 and 2021, effectively translating into a higher data and AI maturity. Experimentation data is the use of internal and external data to design new models and generate new insights. To do that, organizations use enterprise-grade cloud platforms to keep data clean and trustworthy, and to support decision making at greater speed and scale.\n9. Data Management and Governance: Organizations scale their data management and governance practices to increase data quality, trust and ethics across entities—e.g. by implementing master data management and ensuring security, compliance and interoperability.\n10. Data Management and Governance—Change: Organizations improved their data management and governance practices between 2018 and 2021, effectively translating into a higher data and AI maturity.", "attrs": null, "canon": { "kind": { "name": "List", "slug": "list", "status": "active", "canonId": "019de52c-f94b-779b-a53b-fd4904a5f4d2", "version": 1, "description": "Bullet or numbered list." }, "tool": null, "subkind": { "name": "Numbered list", "slug": "numbered", "status": "active", "canonId": "019de52c-fcc0-7718-a284-a4250c805df2", "version": 1, "description": null }, "framework": null }, "subkind": "numbered", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:49:10.678+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "746e2619-d23c-42bf-83e2-3ad5cac54df7", "parentComponentId": null }, { "bbox": { "h": 0.05, "w": 0.2, "x": 0.05, "y": 0.1 }, "kind": "title", "text": "Key Capabilities", "attrs": null, "canon": { "kind": { "name": "Title", "slug": "title", "status": "active", "canonId": "019de52c-f7dd-76d9-b848-b1f12bd85cf4", "version": 1, "description": "Slide title or headline." }, "tool": null, "subkind": { "name": "Headline", "slug": "headline", "status": "active", "canonId": "019de52c-fae1-7463-9a7c-d60668eced0d", "version": 1, "description": null }, "framework": null }, "subkind": "headline", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:49:10.678+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "c2847619-52ac-42d6-8c5d-fed826f4cf41", "parentComponentId": null } ], "metrics": [], "tools": [], "frameworks": [], "arcBeats": [], "loops": [], "locked": true }, { "page": 38, "type": "setup", "title": "Part of a larger list of AI maturity initiatives.", "function": "summarize", "rawType": "initiative_list", "block": null, "metadata": { "slideType": "initiative_list", "slideTypeCanon": { "name": "Initiative list", "slug": "initiative_list", "status": "active", "canonId": "019de52d-0caf-770e-9b91-b99239121f50", "version": 1, "description": null }, "function": "summarize", "functionCanon": { "name": "Summarize", "slug": "summarize", "status": "active", "canonId": "019de52d-1541-704f-b86f-bf7b75056373", "version": 1, "description": null }, "density": "dense", "densityScore": 51, "componentCount": 6, "textChars": 727, "nDataPoints": 0, "notes": "Part of a larger list of AI maturity initiatives.", "elementsJson": [ "numbered_list", "paragraph", "headline_text" ], "confidence": 1, "extraction": { "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "at": "2026-05-02 19:49:10.539+00", "seconds": 2.757, "promptVersion": "v2-canon-conditioned" } }, "links": { "slide": "/slides/019dd923-5ca1-7489-b633-7fa84bbf490b/38", "deck": "/decks/019dd923-5ca1-7489-b633-7fa84bbf490b", "deckAnchor": "/decks/019dd923-5ca1-7489-b633-7fa84bbf490b#slide-38", "deckJson": "/decks/019dd923-5ca1-7489-b633-7fa84bbf490b.json" }, "components": [ { "bbox": { "h": 0.73, "w": 0.26, "x": 0.058, "y": 0.218 }, "kind": "list", "text": "11. Mandatory AI Training: Organizations enforce AI-specific training programs to improve AI fluency... 12. Employee Competency in AI-Related Skills: Organizations regularly measure the competency level...", "attrs": null, "canon": { "kind": { "name": "List", "slug": "list", "status": "active", "canonId": "019de52c-f94b-779b-a53b-fd4904a5f4d2", "version": 1, "description": "Bullet or numbered list." }, "tool": null, "subkind": { "name": "Numbered list", "slug": "numbered", "status": "active", "canonId": "019de52c-fcc0-7718-a284-a4250c805df2", "version": 1, "description": null }, "framework": null }, "subkind": "numbered", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:49:10.539+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "51d6988f-eccc-4986-a469-3ac6d4d8ff35", "parentComponentId": null }, { "bbox": { "h": 0.78, "w": 0.26, "x": 0.312, "y": 0.165 }, "kind": "list", "text": "13. Innovation Culture Embedded: Organizations ensure innovation is part of the day-to-day work environment... 14. Innovation Culture Encouraged: Organizations promote and reward innovative mindsets... 15. AI Talent Strategy: Organizations have an AI talent strategy...", "attrs": null, "canon": { "kind": { "name": "List", "slug": "list", "status": "active", "canonId": "019de52c-f94b-779b-a53b-fd4904a5f4d2", "version": 1, "description": "Bullet or numbered list." }, "tool": null, "subkind": { "name": "Numbered list", "slug": "numbered", "status": "active", "canonId": "019de52c-fcc0-7718-a284-a4250c805df2", "version": 1, "description": null }, "framework": null }, "subkind": "numbered", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:49:10.539+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "76bfeb59-0ece-4151-9c12-2b29bb6c70f5", "parentComponentId": null }, { "bbox": { "h": 0.58, "w": 0.26, "x": 0.566, "y": 0.218 }, "kind": "list", "text": "16. Responsible AI: Organizations have an industrialized, responsible approach to data and AI... 17. Responsible AI—Change: Organizations have improved their responsible data and AI practices...", "attrs": null, "canon": { "kind": { "name": "List", "slug": "list", "status": "active", "canonId": "019de52c-f94b-779b-a53b-fd4904a5f4d2", "version": 1, "description": "Bullet or numbered list." }, "tool": null, "subkind": { "name": "Numbered list", "slug": "numbered", "status": "active", "canonId": "019de52c-fcc0-7718-a284-a4250c805df2", "version": 1, "description": null }, "framework": null }, "subkind": "numbered", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:49:10.539+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "ad21b620-1a92-4baf-bdfc-36f82e9d6898", "parentComponentId": null }, { "bbox": { "h": 0.018, "w": 0.11, "x": 0.566, "y": 0.165 }, "kind": "title", "text": "Responsible AI", "attrs": null, "canon": { "kind": { "name": "Title", "slug": "title", "status": "active", "canonId": "019de52c-f7dd-76d9-b848-b1f12bd85cf4", "version": 1, "description": "Slide title or headline." }, "tool": null, "subkind": { "name": "Headline", "slug": "headline", "status": "active", "canonId": "019de52c-fae1-7463-9a7c-d60668eced0d", "version": 1, "description": null }, "framework": null }, "subkind": "headline", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:49:10.539+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "4eee0a2c-4ba0-4a43-8140-dc63a6209d48", "parentComponentId": null }, { "bbox": { "h": 0.018, "w": 0.2, "x": 0.312, "y": 0.165 }, "kind": "title", "text": "Innovation Culture Embedded", "attrs": null, "canon": { "kind": { "name": "Title", "slug": "title", "status": "active", "canonId": "019de52c-f7dd-76d9-b848-b1f12bd85cf4", "version": 1, "description": "Slide title or headline." }, "tool": null, "subkind": { "name": "Headline", "slug": "headline", "status": "active", "canonId": "019de52c-fae1-7463-9a7c-d60668eced0d", "version": 1, "description": null }, "framework": null }, "subkind": "headline", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:49:10.539+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "58b63e87-cc2c-4ab0-972c-7e07803dacb4", "parentComponentId": null }, { "bbox": { "h": 0.018, "w": 0.145, "x": 0.058, "y": 0.165 }, "kind": "title", "text": "Talent and culture", "attrs": null, "canon": { "kind": { "name": "Title", "slug": "title", "status": "active", "canonId": "019de52c-f7dd-76d9-b848-b1f12bd85cf4", "version": 1, "description": "Slide title or headline." }, "tool": null, "subkind": { "name": "Headline", "slug": "headline", "status": "active", "canonId": "019de52c-fae1-7463-9a7c-d60668eced0d", "version": 1, "description": null }, "framework": null }, "subkind": "headline", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:49:10.539+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "a44bc3e0-4025-4fe3-8e16-1cb78473b50c", "parentComponentId": null } ], "metrics": [], "tools": [], "frameworks": [], "arcBeats": [], "loops": [], "locked": true }, { "page": 39, "type": "appendix", "function": "appendix", "rawType": "appendix_disclosure", "block": null, "metadata": { "slideType": "appendix_disclosure", "slideTypeCanon": { "name": "Appendix disclosure", "slug": "appendix_disclosure", "status": "active", "canonId": "019de52d-07b2-7549-8e8b-932a19f6e616", "version": 1, "description": null }, "function": "appendix", "functionCanon": { "name": "Appendix", "slug": "appendix", "status": "active", "canonId": "019de52d-138d-750b-83c3-49b4bc7a7a38", "version": 1, "description": null }, "density": "dense", "densityScore": 54, "componentCount": 5, "textChars": 1097, "nDataPoints": 2, "notes": null, "elementsJson": [ "headline_text", "paragraph", "bullet_list" ], "confidence": 1, "extraction": { "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "at": "2026-05-02 19:49:11.194+00", "seconds": 3.101, "promptVersion": "v2-canon-conditioned" } }, "links": { "slide": "/slides/019dd923-5ca1-7489-b633-7fa84bbf490b/39", "deck": "/decks/019dd923-5ca1-7489-b633-7fa84bbf490b", "deckAnchor": "/decks/019dd923-5ca1-7489-b633-7fa84bbf490b#slide-39", "deckJson": "/decks/019dd923-5ca1-7489-b633-7fa84bbf490b.json" }, "components": [ { "bbox": null, "kind": "callout", "text": "46% of these CEOs mentioned AI in their earnings calls, in 2021 up from ~35% in 2017.", "attrs": null, "canon": { "kind": { "name": "Callout", "slug": "callout", "status": "active", "canonId": "019de52c-f8d3-761a-8953-7d37080de5e2", "version": 1, "description": "Highlighted callout box." }, "tool": { "name": "Visual emphasis", "slug": "visual-emphasis", "status": "active", "bestFor": null, "canonId": "019dd9e1-474b-736b-a8eb-a794dd88241c", "version": 1, "bodyDocId": null, "description": "Drawing the eye to one element above the rest of the slide.", "familyLabel": null }, "subkind": null, "framework": null }, "subkind": null, "groupRole": null, "confidence": null, "extraction": { "at": "2026-04-23 22:43:39+00", "model": "claude-code-default", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "019dd951-9f64-72ba-b400-409a046c73b1", "parentComponentId": null }, { "bbox": { "h": 0.085, "w": 0.247, "x": 0.058, "y": 0.192 }, "kind": "list", "text": "https://news.stanford.edu/news/2011/october/john-mccarthy-obit-102511.html#:~:text=John%20McCarthy%2C%20a%20professor%20emeritus,He%20was%202084", "attrs": null, "canon": { "kind": { "name": "List", "slug": "list", "status": "active", "canonId": "019de52c-f94b-779b-a53b-fd4904a5f4d2", "version": 1, "description": "Bullet or numbered list." }, "tool": null, "subkind": { "name": "Bullet list", "slug": "bullet", "status": "active", "canonId": "019de52c-fc98-7169-a083-5cab805076ca", "version": 1, "description": null }, "framework": null }, "subkind": "bullet", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:49:11.194+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "48e54a5b-210f-48b8-875f-b82ec72f5775", "parentComponentId": null }, { "bbox": { "h": 0.681, "w": 0.496, "x": 0.286, "y": 0.192 }, "kind": "list", "text": "Accenture Interview\nhttps://www.nytimes.com/2020/07/13/business/coronavirus-retraining-workers.html\nhttps://global.rakuten.com/corp/careers/topics/engineering3/\nhttps://economictimes.indiatimes.com/tech/software/american-express-sets-up-data-analytics-risk-technology-lab-in-iit-madras/articleshow/77925793.cms\nhttps://www.novartis.com/about/strategy/data-and-digital/artificial-intelligence/our-commitment-ethical-and-responsible-use-ai\nhttps://www.accenture.com/us-en/insights/artificial-intelligence/ai-investments", "attrs": null, "canon": { "kind": { "name": "List", "slug": "list", "status": "active", "canonId": "019de52c-f94b-779b-a53b-fd4904a5f4d2", "version": 1, "description": "Bullet or numbered list." }, "tool": null, "subkind": { "name": "Bullet list", "slug": "bullet", "status": "active", "canonId": "019de52c-fc98-7169-a083-5cab805076ca", "version": 1, "description": null }, "framework": null }, "subkind": "bullet", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:49:11.194+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "75e088d2-9882-4a55-ba97-85588e963110", "parentComponentId": null }, { "bbox": { "h": 0.175, "w": 0.253, "x": 0.058, "y": 0.347 }, "kind": "paragraph", "text": "Accenture Research analysis of the world's 2,000 largest companies by market capitalization mentioning AI in their earnings calls. Formula is based on CEOs of companies that had earnings call in 2020, and CEO was present at the call, and CEO mentioned AI. 46% of these CEOs mentioned AI in their earnings calls, in 2021 up from ~35% in 2017.", "attrs": null, "canon": { "kind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "5f2affc0-941d-4d07-959d-4bfc1930cea4", "version": 1, "description": "Single prose block in the body of a slide." }, "tool": null, "subkind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "019de52c-fb80-75af-aa5c-a7a4bfac2433", "version": 1, "description": null }, "framework": null }, "subkind": "paragraph", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:49:11.194+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "ab11267c-1af7-45b8-8c16-45ee2bd90e07", "parentComponentId": null }, { "bbox": { "h": 0.055, "w": 0.175, "x": 0.058, "y": 0.118 }, "kind": "title", "text": "References", "attrs": null, "canon": { "kind": { "name": "Title", "slug": "title", "status": "active", "canonId": "019de52c-f7dd-76d9-b848-b1f12bd85cf4", "version": 1, "description": "Slide title or headline." }, "tool": null, "subkind": { "name": "Headline", "slug": "headline", "status": "active", "canonId": "019de52c-fae1-7463-9a7c-d60668eced0d", "version": 1, "description": null }, "framework": null }, "subkind": "headline", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:49:11.194+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "9cdb7778-839e-4a1c-abbc-76ed0cf3f606", "parentComponentId": null } ], "metrics": [], "tools": [], "frameworks": [], "arcBeats": [], "loops": [], "locked": true }, { "page": 40, "type": "setup", "function": "summarize", "rawType": "appendix_disclosure", "block": null, "metadata": { "slideType": "appendix_disclosure", "slideTypeCanon": { "name": "Appendix disclosure", "slug": "appendix_disclosure", "status": "active", "canonId": "019de52d-07b2-7549-8e8b-932a19f6e616", "version": 1, "description": null }, "function": "summarize", "functionCanon": { "name": "Summarize", "slug": "summarize", "status": "active", "canonId": "019de52d-1541-704f-b86f-bf7b75056373", "version": 1, "description": null }, "density": "overcrowded", "densityScore": 83, "componentCount": 8, "textChars": 2169, "nDataPoints": 4, "notes": null, "elementsJson": [ "headline_text", "paragraph", "footnote" ], "confidence": 1, "extraction": { "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "at": "2026-05-02 19:49:16.394+00", "seconds": 8.244, "promptVersion": "v2-canon-conditioned" } }, "links": { "slide": "/slides/019dd923-5ca1-7489-b633-7fa84bbf490b/40", "deck": "/decks/019dd923-5ca1-7489-b633-7fa84bbf490b", "deckAnchor": "/decks/019dd923-5ca1-7489-b633-7fa84bbf490b#slide-40", "deckJson": "/decks/019dd923-5ca1-7489-b633-7fa84bbf490b.json" }, "components": [ { "bbox": { "h": 0.1, "w": 0.8, "x": 0.058, "y": 0.738 }, "kind": "disclaimer", "text": "This content is provided for general information purposes and is not intended to be used in place of consultation with our professional advisors. This document makes descriptive reference to trademarks that may be owned by others. The use of such trademarks herein is not an assertion of ownership of such trademarks by Accenture and is not intended to represent or imply the existence of an association between Accenture and the lawful owners of such trademarks. Copyright © 2023 Accenture. All rights reserved. Accenture and its logo are registered trademarks of Accenture.", "attrs": null, "canon": { "kind": { "name": "Disclaimer", "slug": "disclaimer", "status": "active", "canonId": "91173477-d91f-4024-bbaf-d4f93e3f82dc", "version": 1, "description": "Legal/cautionary text that occupies most of the body of its slide." }, "tool": null, "subkind": null, "framework": null }, "subkind": null, "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:49:16.394+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "ca8d09b7-050b-4fab-b7a6-5dca7f5dd73a", "parentComponentId": null }, { "bbox": { "h": 0.2, "w": 0.3, "x": 0.058, "y": 0.27 }, "kind": "paragraph", "text": "Accenture is a global professional services company with leading capabilities in digital, cloud and security. Combining unmatched experience and specialized skills across more than 40 industries, we offer Strategy and Consulting, Interactive, Technology and Operations services—all powered by the world's largest network of Advanced Technology and Intelligent Operations centers. Our 738,000 people deliver on the promise of technology and human ingenuity every day, serving clients in more than 120 countries. We embrace the power of change to create value and shared success for our clients, people, shareholders, partners and communities. Visit us at www.accenture.com.", "attrs": null, "canon": { "kind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "5f2affc0-941d-4d07-959d-4bfc1930cea4", "version": 1, "description": "Single prose block in the body of a slide." }, "tool": null, "subkind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "019de52c-fb80-75af-aa5c-a7a4bfac2433", "version": 1, "description": null }, "framework": null }, "subkind": "paragraph", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:49:16.394+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "311e30ac-d180-4480-a835-d35672180f16", "parentComponentId": null }, { "bbox": { "h": 0.2, "w": 0.3, "x": 0.36, "y": 0.27 }, "kind": "paragraph", "text": "Accenture Research creates thought leadership about the most pressing business issues organizations face. Combining innovative research techniques, such as data science led analysis, with a deep understanding of industry and technology, our team of 300 researchers in 20 countries publish hundreds of reports, articles and points of view every year. Our thought-provoking research developed with world leading organizations helps our clients embrace change, create value, and deliver on the power of technology and human ingenuity.", "attrs": null, "canon": { "kind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "5f2affc0-941d-4d07-959d-4bfc1930cea4", "version": 1, "description": "Single prose block in the body of a slide." }, "tool": null, "subkind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "019de52c-fb80-75af-aa5c-a7a4bfac2433", "version": 1, "description": null }, "framework": null }, "subkind": "paragraph", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:49:16.394+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "62868d11-b2c9-473c-b52f-2261a53135c2", "parentComponentId": null }, { "bbox": { "h": 0.15, "w": 0.3, "x": 0.666, "y": 0.27 }, "kind": "paragraph", "text": "Applied Intelligence is Accenture's approach to scaling AI for clients by embedding AI-powered data, analytics and automation capabilities into business workflows, accelerating time to value with a powerful global alliance, innovation and delivery network that can deploy and scale AI within any market and industry.", "attrs": null, "canon": { "kind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "5f2affc0-941d-4d07-959d-4bfc1930cea4", "version": 1, "description": "Single prose block in the body of a slide." }, "tool": null, "subkind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "019de52c-fb80-75af-aa5c-a7a4bfac2433", "version": 1, "description": null }, "framework": null }, "subkind": "paragraph", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:49:16.394+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "de6a0c7d-723d-4b33-b000-70ab8309179b", "parentComponentId": null }, { "bbox": { "h": 0.018, "w": 0.1, "x": 0.058, "y": 0.688 }, "kind": "title", "text": "Disclaimer", "attrs": null, "canon": { "kind": { "name": "Title", "slug": "title", "status": "active", "canonId": "019de52c-f7dd-76d9-b848-b1f12bd85cf4", "version": 1, "description": "Slide title or headline." }, "tool": null, "subkind": { "name": "Headline", "slug": "headline", "status": "active", "canonId": "019de52c-fae1-7463-9a7c-d60668eced0d", "version": 1, "description": null }, "framework": null }, "subkind": "headline", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:49:16.394+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "2f375ebb-454b-4801-b36b-58bdb8ad4d79", "parentComponentId": null }, { "bbox": { "h": 0.018, "w": 0.144, "x": 0.058, "y": 0.22 }, "kind": "title", "text": "About Accenture", "attrs": null, "canon": { "kind": { "name": "Title", "slug": "title", "status": "active", "canonId": "019de52c-f7dd-76d9-b848-b1f12bd85cf4", "version": 1, "description": "Slide title or headline." }, "tool": null, "subkind": { "name": "Headline", "slug": "headline", "status": "active", "canonId": "019de52c-fae1-7463-9a7c-d60668eced0d", "version": 1, "description": null }, "framework": null }, "subkind": "headline", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:49:16.394+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "52ee222b-c8ec-46b1-bd66-f19ce0f2eebe", "parentComponentId": null }, { "bbox": { "h": 0.018, "w": 0.2, "x": 0.666, "y": 0.22 }, "kind": "title", "text": "About Applied Intelligence", "attrs": null, "canon": { "kind": { "name": "Title", "slug": "title", "status": "active", "canonId": "019de52c-f7dd-76d9-b848-b1f12bd85cf4", "version": 1, "description": "Slide title or headline." }, "tool": null, "subkind": { "name": "Headline", "slug": "headline", "status": "active", "canonId": "019de52c-fae1-7463-9a7c-d60668eced0d", "version": 1, "description": null }, "framework": null }, "subkind": "headline", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:49:16.394+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "a123c7e6-eace-4929-bbd4-31f58d8b8feb", "parentComponentId": null }, { "bbox": { "h": 0.018, "w": 0.2, "x": 0.36, "y": 0.22 }, "kind": "title", "text": "About Accenture Research", "attrs": null, "canon": { "kind": { "name": "Title", "slug": "title", "status": "active", "canonId": "019de52c-f7dd-76d9-b848-b1f12bd85cf4", "version": 1, "description": "Slide title or headline." }, "tool": null, "subkind": { "name": "Headline", "slug": "headline", "status": "active", "canonId": "019de52c-fae1-7463-9a7c-d60668eced0d", "version": 1, "description": null }, "framework": null }, "subkind": "headline", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:49:16.394+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "cc8eb8b4-54e4-4c02-a902-f1692a70547f", "parentComponentId": null } ], "metrics": [], "tools": [], "frameworks": [], "arcBeats": [], "loops": [], "locked": true } ], "arcBeats": [ { "from": 3, "to": 8, "label": "Situation & Context", "description": "AI is essential, transformation 16 months faster than digital." }, { "from": 9, "to": 13, "label": "Problem & Complication", "description": "AI maturity defined; only 7% qualify as Achievers (Fig 3 2x2)." }, { "from": 14, "to": 17, "label": "Evidence & Proof", "description": "Achievers enjoy 50% greater revenue growth, scale pilots more, lead on sustainability." }, { "from": 18, "to": 28, "label": "Solution & Approach", "description": "Five success factors: leadership, talent, AI core, responsible AI, investment." }, { "from": 29, "to": 32, "label": "Impact & Next Steps", "description": "7%->20% projection, 'practice makes progress', C-suite assessment table p32." } ], "loops": [ { "from": 3, "to": 5, "label": "Aha Moment", "description": "Open with the question and the 7%/20% reveal" }, { "from": 7, "to": 8, "label": "Why Now", "description": "Justify urgency of acting on AI maturity" }, { "from": 10, "to": 13, "label": "2x2 Matrix", "description": "Segment firms via the AI Foundation x Differentiation 2x2" }, { "from": 15, "to": 17, "label": "Benchmark Gap", "description": "Quantify the performance gap between Achievers and others" }, { "from": 20, "to": 28, "label": "Mece Breakdown", "description": "Lay out five MECE success factors with evidence and cases" }, { "from": 29, "to": 32, "label": "Time Machine", "description": "Cast forward to 2024 vision and route back to today's assessment" } ] }