{ "schemaVersion": "deck-intelligence.v1", "id": "019dd923-5e88-73ef-bd5d-19f3d1409030", "slug": "f487de8c76cab714", "title": "2024 Executive Perspectives CEO s Guide to Maximizing Value Potential from AI in 2024", "subtitle": "BCG", "author": "BCG", "pageCount": 22, "kind": "consulting-deck", "orientation": "landscape", "aspectRatio": 1.778, "document": { "id": "019dd923-5e88-73ef-bd5d-19f3d1409030", "slug": "f487de8c76cab714", "title": "2024 Executive Perspectives CEO s Guide to Maximizing Value Potential from AI in 2024", "rawTitle": "2024 Executive Perspectives CEO s Guide to Maximizing Value Potential from AI in 2024", "authorId": "BCG", "authorName": "BCG", "authorDisplay": "BCG", "kind": { "slug": "consulting-deck", "label": "Consulting deck" }, "sourceType": { "slug": "strategy_consulting", "label": "Strategy consulting" }, "fileName": "2024-Executive-Perspectives-CEO-s-Guide-to-Maximizing-Value-Potential-from-AI-in-2024.pdf", "sourceUrl": null, "sourceDate": "2024-07-01 00:00:00", "presentationDate": null, "ingestedAt": "2026-04-25 11:55:49+00", "status": "ready", "pageCount": 22, "orientation": "landscape", "aspectRatio": 1.778, "targetCompany": null, "targetTicker": null, "metadata": { "local_root": "/tmp/legacy-images/f487de8c76cab714", "origin_corpus": "consulting" } }, "coverage": { "pageCount": 22, "pagesIndexed": 22, "pagesWithImages": 22, "pagesWithMetadata": 22, "imageCoveragePct": 100, "metadataCoveragePct": 100, "componentCount": 153, "chartCount": 2, "metricSlides": 0, "toolMatches": 95, "documentToolMatches": 0, "frameworkMatches": 25, "arcMatches": 2, "beatMatches": 8, "loopMatches": 5, "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-a78f-dfee38d7d88d", "evidence": "Classic BCG exec perspective: context (p.1-5), three-play solution (p.6-7), case proof (p.8-13), pillars + complication (p.14-17), next steps (p.18-21).", "isPrimary": true, "confidence": 82, "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-a78f-e037a8f09810", "evidence": "Facts (AI context p.1-5, evidence p.8-15) -> Implications (p.14-17) -> Action (p.18-20).", "isPrimary": false, "confidence": 55, "extraction": { "at": "2026-04-29 13:07:28.977035+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null } } ], "beats": [ { "to": 5, "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": 1, "name": "Situation & Context", "beatId": "019dd95a-0682-776c-8e38-80435600ee98", "matchId": "019dd95a-0542-7728-a78f-dfee38d7d88d", "beatType": { "name": "Situation & Context", "slug": "consultants-gambit-situation-context", "status": "active", "canonId": "019dd9b8-05ae-741b-992d-65ee83c639b3", "version": 1, "description": null }, "evidence": "Cover, intro, exec summary, AI maturity curve, tech evolution arrow", "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. 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The exception (Sparkline) ends with new bliss which is functionally a resolution." }, "alignedBlockIds": null, "matchConfidence": 55 } ], "loops": [ { "to": 5, "from": 3, "loop": { "name": "04_tale_two_worlds", "slug": "04-tale-two-worlds", "status": "active", "bestFor": "Competitive analysis, benchmarking, case for change", "canonId": "019dd956-674f-750b-b15d-f082e2717f4e", "version": 1, "bodyDocId": "019df22a-2420-77be-bc41-ded96d08cb21", "structure": "Current State -> Desired State / Benchmark -> The Gap & Implication", "description": "Show the gap between two states to drive urgency or highlight opportunity", "familyLabel": null, "categoryName": "Comparison", "categorySlug": "comparison" }, "matchId": "019dd95a-07fe-70ce-8d40-8f8debf0cc4b", "evidence": "AI-mature ~10% companies vs no-action ~40%, with +2.6x revenue growth gap; tech evolution arrow.", "position": 1, "objective": "Frame the AI maturity gap as widening lead vs laggards", "confidence": 78, "extraction": { "at": 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88, "extraction": { "at": "2026-04-29 13:07:29.547081+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null } }, { "to": 13, "from": 8, "loop": { "name": "02_pattern_hunter", "slug": "02-pattern-hunter", "status": "active", "bestFor": "Time-pressed audiences, building consensus, when data is strong", "canonId": "019dd956-6695-771a-be2e-f1748ef041a4", "version": 1, "bodyDocId": "019df22a-2420-77be-bc41-ded96d08cb21", "structure": "Evidence A -> Evidence B -> Evidence C -> Pattern/Conclusion", "description": "Group multiple pieces of evidence that together point to a pattern or conclusion", "familyLabel": null, "categoryName": "Logical Reasoning", "categorySlug": "logical-reasoning" }, "matchId": "019dd95a-07fe-70ce-8d40-95f5918f9b92", "evidence": "Sequential overviews (10-15%, 68%, 46%) plus ambitious-target benchmarks and two named company examples.", "position": 3, "objective": "Stack quantified case evidence to validate the plays", "confidence": 80, 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"extraction": { "at": "2026-04-29 13:07:29.547081+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null } } ], "tools": [ { "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? 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