{ "schemaVersion": "deck-intelligence.v1", "id": "019dd923-5e88-73ef-bd5d-e266bb5de1d1", "slug": "f327bfb5f83e3c7e", "title": "2024 ROI of AI", "subtitle": "Morning Consult", "author": "Morning Consult", "pageCount": 77, "kind": "consulting-deck", "orientation": "landscape", "aspectRatio": 1.778, "document": { "id": "019dd923-5e88-73ef-bd5d-e266bb5de1d1", "slug": "f327bfb5f83e3c7e", "title": "2024 ROI of AI", "rawTitle": "2024 ROI of AI", "authorId": "IBM", "authorName": "Morning Consult", "authorDisplay": "Morning Consult", "kind": { "slug": "consulting-deck", "label": "Consulting deck" }, "sourceType": { "slug": "strategy_consulting", "label": "Strategy consulting" }, "fileName": "2024-ROI-of-AI.pdf", "sourceUrl": null, "sourceDate": "2024-01-01 00:00:00", "presentationDate": null, "ingestedAt": "2026-04-25 11:55:51+00", "status": "ready", "pageCount": 77, "orientation": "landscape", "aspectRatio": 1.778, "targetCompany": null, "targetTicker": null, "metadata": { "local_root": "/tmp/legacy-images/f327bfb5f83e3c7e", "origin_corpus": "consulting" } }, "coverage": { "pageCount": 77, "pagesIndexed": 77, "pagesWithImages": 77, "pagesWithMetadata": 77, "imageCoveragePct": 100, "metadataCoveragePct": 100, "componentCount": 406, "chartCount": 45, "metricSlides": 0, "toolMatches": 46, "documentToolMatches": 0, "frameworkMatches": 1, "arcMatches": 1, "beatMatches": 5, "loopMatches": 3, "patternMatches": 0, "storymakersMatch": false, "scoreAvailable": true, "reviewAvailable": true, "activistThesisAvailable": false, "pitchdeckMetadataAvailable": false, "pitchdeckProfileAvailable": false }, "blocks": [], "matches": { "arcs": [ { "arc": { "name": "The Sparkline", "slug": "sparkline", "status": "active", "bestFor": "Keynotes, TED-style talks", "canonId": "019dd956-606e-720c-905a-42607ac0bf50", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "What Is -> What Could Be -> What Is -> What Could Be -> New Bliss", "description": null, "familyLabel": null, "categoryName": "Narrative & Transformation", "categorySlug": "narrative-transformation" }, "matchId": "bf9fcf67-d39d-4c8d-8724-bdd9506a6c64", "evidence": "The deck follows a sparkline narrative arc, starting with an overview of the current landscape, highlighting challenges, and concluding with future plans and strategies.", "isPrimary": true, "confidence": 0.8, "extraction": { "at": "2026-07-16 21:24:12.1719+00", "model": "or:meta-llama/llama-4-scout", "runId": null, "seconds": null, "promptVersion": "doc-narrative-v1" } } ], "beats": [ { "to": 4, "arc": { "name": "The Sparkline", "slug": "sparkline", "status": "active", "bestFor": "Keynotes, TED-style talks", "canonId": "019dd956-606e-720c-905a-42607ac0bf50", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "What Is -> What Could Be -> What Is -> What Could Be -> New Bliss", "description": null, "familyLabel": null, "categoryName": "Narrative & Transformation", "categorySlug": "narrative-transformation" }, "from": 1, "name": "Setup", "beatId": "2d39221b-3db7-473d-ba20-268e74c68406", "matchId": "bf9fcf67-d39d-4c8d-8724-bdd9506a6c64", "beatType": { "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." }, "evidence": "The deck begins with an introduction to the topic, methodology, and key findings.", "position": 0, "isPrimaryArc": true, "parentBeatType": null, "alignedBlockIds": null, "matchConfidence": 0.8 }, { "to": 12, "arc": { "name": "The Sparkline", "slug": "sparkline", "status": "active", "bestFor": "Keynotes, TED-style talks", "canonId": "019dd956-606e-720c-905a-42607ac0bf50", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "What Is -> What Could Be -> What Is -> What Could Be -> New Bliss", "description": null, "familyLabel": null, "categoryName": "Narrative & Transformation", "categorySlug": "narrative-transformation" }, "from": 6, "name": "Industry Trends", "beatId": "44ba47c2-bd64-44fb-b74b-8b42654de485", "matchId": "bf9fcf67-d39d-4c8d-8724-bdd9506a6c64", "beatType": null, "evidence": "The deck presents industry trends and data on the current landscape of AI investments and ROI.", "position": 1, "isPrimaryArc": true, "parentBeatType": null, "alignedBlockIds": null, "matchConfidence": 0.8 }, { "to": 21, "arc": { "name": "The Sparkline", "slug": "sparkline", "status": "active", "bestFor": "Keynotes, TED-style talks", "canonId": "019dd956-606e-720c-905a-42607ac0bf50", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "What Is -> What Could Be -> What Is -> What Could Be -> New Bliss", "description": null, "familyLabel": null, "categoryName": "Narrative & Transformation", "categorySlug": "narrative-transformation" }, "from": 20, "name": "Complication", "beatId": "720f580e-8d58-4365-a3b1-f2b9161624b6", "matchId": "bf9fcf67-d39d-4c8d-8724-bdd9506a6c64", "beatType": { "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." }, "evidence": "The deck highlights the challenges of AI implementation, including data quality and availability issues.", "position": 2, "isPrimaryArc": true, "parentBeatType": null, "alignedBlockIds": null, "matchConfidence": 0.8 }, { "to": 26, "arc": { "name": "The Sparkline", "slug": "sparkline", "status": "active", "bestFor": "Keynotes, TED-style talks", "canonId": "019dd956-606e-720c-905a-42607ac0bf50", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "What Is -> What Could Be -> What Is -> What Could Be -> New Bliss", "description": null, "familyLabel": null, "categoryName": "Narrative & Transformation", "categorySlug": "narrative-transformation" }, "from": 23, "name": "Development", "beatId": "22874121-9055-4ce2-b5b1-e6a4c001108a", "matchId": "bf9fcf67-d39d-4c8d-8724-bdd9506a6c64", "beatType": { "name": "Development", "slug": "development", "status": "active", "canonId": "019dd9b8-0332-7008-b3aa-11b0840a57b1", "version": 1, "description": "The middle stretch in arcs that have one. Often where length problems creep in." }, "evidence": "The deck discusses the future of AI investments and plans for 2025.", "position": 3, "isPrimaryArc": true, "parentBeatType": null, "alignedBlockIds": null, "matchConfidence": 0.8 }, { "to": 77, "arc": { "name": "The Sparkline", "slug": "sparkline", "status": "active", "bestFor": "Keynotes, TED-style talks", "canonId": "019dd956-606e-720c-905a-42607ac0bf50", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "What Is -> What Could Be -> What Is -> What Could Be -> New Bliss", "description": null, "familyLabel": null, "categoryName": "Narrative & Transformation", "categorySlug": "narrative-transformation" }, "from": 29, "name": "Evidence", "beatId": "5bb325e2-e460-48c2-ba3f-ded31b7b7818", "matchId": "bf9fcf67-d39d-4c8d-8724-bdd9506a6c64", "beatType": { "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." }, "evidence": "The deck provides extensive data and evidence to support its findings and recommendations.", "position": 4, "isPrimaryArc": true, "parentBeatType": null, "alignedBlockIds": null, "matchConfidence": 0.8 } ], "loops": [ { "to": 21, "from": 20, "loop": { "name": "27_cost_of_inaction", "slug": "27-cost-of-inaction", "status": "active", "bestFor": "Urgent budget requests, compliance, risk mitigation", "canonId": "019dd956-70d1-7395-a15b-857ba858b394", "version": 1, "bodyDocId": "019df22a-2420-77be-bc41-ded96d08cb21", "structure": "The Status Quo -> The Hidden Costs Accumulating -> The Future State of Inaction -> The Tipping Point", "description": "Quantify what happens if the audience does nothing", "familyLabel": null, "categoryName": "Urgency", "categorySlug": "urgency" }, "matchId": "f4039535-f8b3-4195-8482-c0b0a421a4ab", "evidence": "The deck highlights the challenges of AI implementation and the need to address them.", "position": 0, "objective": "What are the consequences of not addressing AI implementation challenges?", "confidence": 0.7, "extraction": { "at": "2026-07-16 21:24:12.414721+00", "model": "or:meta-llama/llama-4-scout", "runId": null, "seconds": null, "promptVersion": "doc-narrative-v1" } }, { "to": 26, "from": 23, "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": "d7f608c3-cad7-441c-9fc4-3ef2dbe8a2c7", "evidence": "The deck discusses the future of AI investments and plans for 2025.", "position": 1, "objective": "Why is now the right time to invest in AI?", "confidence": 0.7, "extraction": { "at": "2026-07-16 21:24:12.45473+00", "model": "or:meta-llama/llama-4-scout", "runId": null, "seconds": null, "promptVersion": "doc-narrative-v1" } }, { "to": 62, "from": 60, "loop": { "name": "51_voice_of_customer", "slug": "51-voice-of-customer", "status": "active", "bestFor": "Product strategy, customer experience, market research", "canonId": "019dd956-7aaf-750b-950b-af0df38f5266", "version": 1, "bodyDocId": "019df22a-2420-77be-bc41-ded96d08cb21", "structure": "What Customers Say (Verbatim) -> The Pattern Across Voices -> The Insight -> The Response", "description": "Let customer quotes and feedback drive the narrative and validate the insight", "familyLabel": null, "categoryName": "Validation", "categorySlug": "validation" }, "matchId": "a3d9a36f-4000-4605-982d-a9adbd34243f", "evidence": "The deck presents data on the obstacles faced when implementing AI pilot projects.", "position": 2, "objective": "What are the key obstacles faced when implementing AI pilot projects?", "confidence": 0.6, "extraction": { "at": "2026-07-16 21:24:12.49511+00", "model": "or:meta-llama/llama-4-scout", "runId": null, "seconds": null, "promptVersion": "doc-narrative-v1" } } ], "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? 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": "95209b11-21b2-455a-86a5-24b695315539", "evidence": "paragraph/paragraph: This survey was fielded October 30 to November 13, 2024, among a sample of 2,413 IT Decision Makers (ITDMS) in US, Canada, Mexico, Brazil, UK, France, Germany, Spain, India, Singapore, Indonesia, and", "pageRefs": null, "priority": "Core", "whenToUse": null, "confidence": 0.7, "extraction": { "at": "2026-07-17 03:21:16.763156+00", "model": "or:meta-llama/llama-4-scout", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 3, "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": "f7d64907-044e-4501-b75e-a9808f6a7e31", "evidence": "title/headline: Current Landscape of AI: ROI – Drivers, Measurements, & Achievements", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 0.9, "extraction": { "at": "2026-07-17 03:21:16.893187+00", "model": "or:meta-llama/llama-4-scout", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 5, "whyItWorks": null, "antipattern": null, "cardinality": "common", "narrativePurpose": null }, { "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": "8a641f23-25cc-43bc-ad41-63816d6e30a7", "evidence": "ITDMs = 2,413", "pageRefs": null, "priority": "Core", "whenToUse": null, "confidence": 0.6, "extraction": { "at": "2026-07-17 03:21:16.320285+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": "Call to action", "slug": "call-to-action", "status": "active", "bestFor": null, "canonId": "019dd9e1-4bbb-702a-9ead-82daf188bb7c", "version": 1, "bodyDocId": null, "description": "Explicit prescription of what the audience should do next.", "familyLabel": null, "categoryName": null, "categorySlug": null }, "agent": null, "layer": "slide", "agents": null, "matchId": "f10ebcb6-79e7-4cd8-92ed-62cc597b4dcc", "evidence": "The primary motivation driving AI implementation at your company?", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 0.7, "extraction": { "at": "2026-07-17 03:21:16.271985+00", "model": "or:meta-llama/llama-4-scout", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 7, "whyItWorks": null, "antipattern": null, "cardinality": "common", "narrativePurpose": null }, { "tool": { "name": "Chartjunk Elimination", "slug": "chartjunk-elimination", "status": "active", "bestFor": null, "canonId": "019dd956-b49e-7453-ab01-b60f338eeda1", "version": 1, "bodyDocId": null, "description": "Remove decorative elements that don't convey data: 3D effects, shadows, unnecessary gridlines", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Designer", "layer": "slide", "agents": [ "Designer" ], "matchId": "f185c3a8-d2b5-42b9-9976-a19612898a03", "evidence": "clear and simple bar chart presentation", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 0.7, "extraction": { "at": "2026-07-16 22:02:07.621517+00", "model": "or:meta-llama/llama-4-scout", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 8, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "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": "f027a20b-f5a6-42d8-99a5-0c321ef2cfd5", "evidence": "The slide mentions 'ITDMs' and provides sample size, indicating the audience is IT Decision Makers.", "pageRefs": null, "priority": "Core", "whenToUse": null, "confidence": 0.7, "extraction": { "at": "2026-07-16 22:02:16.081352+00", "model": "or:meta-llama/llama-4-scout", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 20, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "Problem Statement Canvas", "slug": "problem-statement-canvas", "status": "active", "bestFor": null, "canonId": "019dd956-839d-744b-ad11-9bf3e3642a18", "version": 1, "bodyDocId": null, "description": "Structured definition of the problem: What? Who? Where? When? Scale?", "familyLabel": null, "categoryName": "Block", "categorySlug": "block" }, "agent": "Architect", "layer": "slide", "agents": [ "Architect" ], "matchId": "02058c14-bbd0-4924-a990-920c4ee5ae8e", "evidence": "The slide highlights specific challenges companies face when moving AI projects from pilot to full implementation.", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 0.6, "extraction": { "at": "2026-07-16 22:02:16.163221+00", "model": "or:meta-llama/llama-4-scout", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 21, "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": "c881801d-f481-4ef3-bbd7-27b75e80c969", "evidence": "The slide implies a matrix or list of areas for AI investment, but no clear 2x2 matrix is visible.", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 0.5, "extraction": { "at": "2026-07-16 22:02:16.359146+00", "model": "or:meta-llama/llama-4-scout", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 25, "whyItWorks": null, "antipattern": null, "cardinality": "common", "narrativePurpose": null }, { "tool": { "name": "List presentation", "slug": "list-presentation", "status": "active", "bestFor": null, "canonId": "019dd9e1-4ef7-777d-ba68-9074c2b3bcf1", "version": 1, "bodyDocId": null, "description": "Bulleted, numbered, or checklist enumerations.", "familyLabel": null, "categoryName": null, "categorySlug": null }, "agent": null, "layer": "slide", "agents": null, "matchId": "474da381-ebe6-40b0-8dcc-f91478c7e97f", "evidence": "The slide presents a list of strategic changes to optimize AI implementation.", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 0.6, "extraction": { "at": "2026-07-16 22:02:16.477904+00", "model": "or:meta-llama/llama-4-scout", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 27, "whyItWorks": null, "antipattern": null, "cardinality": "common", "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": "2d3d8cdf-31f5-431b-9940-80ef520818c3", "evidence": "The slide uses a bar chart to show the projected AI pilot launch timeline.", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 0.7, "extraction": { "at": "2026-07-16 22:02:16.597912+00", "model": "or:meta-llama/llama-4-scout", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 29, "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": "6133c87f-63af-4fad-983f-2d2d461c62d1", "evidence": "The slide uses a bar chart to show areas likely to see AI investments reduced.", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 0.7, "extraction": { "at": "2026-07-16 22:02:16.676766+00", "model": "or:meta-llama/llama-4-scout", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 30, "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": "5f8b8b03-82ff-4dc7-bac2-f59a83e6c643", "evidence": "The slide uses a bar chart to show metrics used to measure ROI from AI investments.", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 0.7, "extraction": { "at": "2026-07-16 22:02:16.754989+00", "model": "or:meta-llama/llama-4-scout", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 31, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "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": "c8304500-b1a7-471d-adc7-140b5dc5caa3", "evidence": "Group 1: Advanced AI Ecosystems: Respondents from the US, Canada, the UK, France, Germany, Singapore, and South Korea displayed similar response patterns across multiple key questions.", "pageRefs": null, "priority": "Core", "whenToUse": null, "confidence": 0.7, "extraction": { "at": "2026-07-16 22:02:09.418528+00", "model": "or:meta-llama/llama-4-scout", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 33, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "Audience Segmentation", "slug": "audience-segmentation", "status": "active", "bestFor": null, "canonId": "019dd956-8079-7046-8e6b-ecdf1bf15590", "version": 1, "bodyDocId": null, "description": "Grouping audience by attitude toward your message: Champions, Neutrals, Skeptics", "familyLabel": null, "categoryName": "Block", "categorySlug": "block" }, "agent": "Storyteller", "layer": "slide", "agents": [ "Storyteller" ], "matchId": "8f18e8ab-a4ae-45ae-86ca-9052e33ac41f", "evidence": "Group 1: Advanced AI Ecosystems: Respondents from the US, Canada, the UK, France, Germany, Singapore, and South Korea displayed similar response patterns across multiple key questions. Group 2: Emerging AI Ecosystems: Respondents from Mexico, Spain, Brazil, India, and Indonesia also had distinct response patterns.", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 0.7, "extraction": { "at": "2026-07-16 22:02:09.452709+00", "model": "or:meta-llama/llama-4-scout", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 33, "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": "f61f84e6-8128-4745-905c-8bf234ece954", "evidence": "chart/bar-grouped: Grouped bar chart showing AI strategy progress levels", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 0.5, "extraction": { "at": "2026-07-16 22:02:09.520581+00", "model": "or:meta-llama/llama-4-scout", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 34, "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": "2bc78946-dad3-43be-b1d5-c88df9c9d185", "evidence": "chart/bar-grouped: Grouped bar chart showing distribution of AI pilots (None, 1-10, 11-20, 21-30, More than 30) for Advanced vs Emerging markets.", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 0.5, "extraction": { "at": "2026-07-16 22:02:09.58867+00", "model": "or:meta-llama/llama-4-scout", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 35, "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": "5831e3dd-f241-4d66-b006-832938fa2a63", "evidence": "chart/bar-grouped: Grouped bar chart showing distribution of open-source usage percentages (0%, 1-24%, 25-49%, 50-74%, 75-100%) for Advanced vs Emerging markets.", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 0.5, "extraction": { "at": "2026-07-16 22:02:09.658035+00", "model": "or:meta-llama/llama-4-scout", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 36, "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": "6b6ece98-1afd-4224-ad0a-6a56e44e8f8f", "evidence": "Grouped bar chart showing 9 categories of obstacles with percentages for two market types.", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 0.5, "extraction": { "at": "2026-07-16 22:02:09.728587+00", "model": "or:meta-llama/llama-4-scout", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 37, "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": "f3c025ae-5985-4947-bab8-f7ba49d19210", "evidence": "chart/bar-grouped: Grouped bar chart showing 7 categories of AI implementation challenges", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 0.5, "extraction": { "at": "2026-07-16 22:02:09.795049+00", "model": "or:meta-llama/llama-4-scout", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 38, "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": "3a469373-c229-4320-aff9-8dfc158803fa", "evidence": "chart/bar-grouped: Grouped bar chart showing distribution of AI pilots (None, 1-10, 11-20, 21-30, More than 30) for Advanced vs Emerging markets.", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 0.5, "extraction": { "at": "2026-07-16 22:02:09.861503+00", "model": "or:meta-llama/llama-4-scout", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 39, "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": "8a327cd1-7790-4592-90ca-9b1d95721d7a", "evidence": "chart/bar-stacked-100pct: Stacked bar chart comparing motivations for Advanced vs Emerging AI Ecosystems", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 0.5, "extraction": { "at": "2026-07-16 22:02:09.930567+00", "model": "or:meta-llama/llama-4-scout", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 40, "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": "6a62a76b-0c8b-4f67-976b-ac0fde6699cd", "evidence": "chart/bar-grouped: Grouped bar chart showing distribution of AI pilots planned for 2025", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 0.5, "extraction": { "at": "2026-07-16 22:02:09.997827+00", "model": "or:meta-llama/llama-4-scout", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 41, "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": "ec7e1308-705a-498b-a0b5-3822e09d7937", "evidence": "chart/bar-grouped: Grouped bar chart showing distribution of open-source usage percentages", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 0.5, "extraction": { "at": "2026-07-16 22:02:10.064766+00", "model": "or:meta-llama/llama-4-scout", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 42, "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": "f9e5fbbc-8fc7-4183-b984-06e4f4f0c560", "evidence": "legend: Completely innovation-driven, Mostly innovation-driven, Equally innovation-driven and ROI-driven, Mostly ROI-driven, Completely ROI-driven", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 0.5, "extraction": { "at": "2026-07-16 22:02:10.134398+00", "model": "or:meta-llama/llama-4-scout", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 43, "whyItWorks": null, "antipattern": null, "cardinality": "common", "narrativePurpose": null }, { "tool": { "name": "Chartjunk Elimination", "slug": "chartjunk-elimination", "status": "active", "bestFor": null, "canonId": "019dd956-b49e-7453-ab01-b60f338eeda1", "version": 1, "bodyDocId": null, "description": "Remove decorative elements that don't convey data: 3D effects, shadows, unnecessary gridlines", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Designer", "layer": "slide", "agents": [ "Designer" ], "matchId": "a2b5de1a-99c0-4f60-aef1-0947c56842cf", "evidence": "The slide contains a grouped bar chart with clear labels and a legend, showing a simple and effective visualization of data.", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 0.7, "extraction": { "at": "2026-07-16 22:02:11.148935+00", "model": "or:meta-llama/llama-4-scout", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 44, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "Data-Ink Ratio", "slug": "data-ink-ratio", "status": "active", "bestFor": null, "canonId": "019dd956-afc8-70da-b378-92834d36fde6", "version": 1, "bodyDocId": null, "description": "Maximize data, minimize non-data ink - remove chartjunk and decoration", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Designer", "layer": "slide", "agents": [ "Designer" ], "matchId": "787461ba-993c-4b74-ba0a-f0a3d6253c2e", "evidence": "The chart appears to have a high data-ink ratio, with a clear focus on presenting the data.", "pageRefs": null, "priority": "Core", "whenToUse": null, "confidence": 0.7, "extraction": { "at": "2026-07-16 22:02:11.18878+00", "model": "or:meta-llama/llama-4-scout", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 44, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "Chartjunk Elimination", "slug": "chartjunk-elimination", "status": "active", "bestFor": null, "canonId": "019dd956-b49e-7453-ab01-b60f338eeda1", "version": 1, "bodyDocId": null, "description": "Remove decorative elements that don't convey data: 3D effects, shadows, unnecessary gridlines", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Designer", "layer": "slide", "agents": [ "Designer" ], "matchId": "91ad31c8-2247-40e1-a1a6-99be5ecb3b1b", "evidence": "The slide contains a grouped bar chart with clear labels and a legend, showing a simple and effective visualization of data.", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 0.7, "extraction": { "at": "2026-07-16 22:02:11.267604+00", "model": "or:meta-llama/llama-4-scout", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 45, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "Data-Ink Ratio", "slug": "data-ink-ratio", "status": "active", "bestFor": null, "canonId": "019dd956-afc8-70da-b378-92834d36fde6", "version": 1, "bodyDocId": null, "description": "Maximize data, minimize non-data ink - remove chartjunk and decoration", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Designer", "layer": "slide", "agents": [ "Designer" ], "matchId": "09f11c63-1972-4385-9272-d52534582715", "evidence": "The chart appears to have a high data-ink ratio, with a clear focus on presenting the data.", "pageRefs": null, "priority": "Core", "whenToUse": null, "confidence": 0.7, "extraction": { "at": "2026-07-16 22:02:11.309017+00", "model": "or:meta-llama/llama-4-scout", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 45, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "Chartjunk Elimination", "slug": "chartjunk-elimination", "status": "active", "bestFor": null, "canonId": "019dd956-b49e-7453-ab01-b60f338eeda1", "version": 1, "bodyDocId": null, "description": "Remove decorative elements that don't convey data: 3D effects, shadows, unnecessary gridlines", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Designer", "layer": "slide", "agents": [ "Designer" ], "matchId": "11fa36a3-1334-4e91-9b5a-ef94c717d562", "evidence": "The slide contains a grouped bar chart with clear labels and a legend, showing a simple and effective visualization of data.", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 0.7, "extraction": { "at": "2026-07-16 22:02:11.390655+00", "model": "or:meta-llama/llama-4-scout", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 46, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "Data-Ink Ratio", "slug": "data-ink-ratio", "status": "active", "bestFor": null, "canonId": "019dd956-afc8-70da-b378-92834d36fde6", "version": 1, "bodyDocId": null, "description": "Maximize data, minimize non-data ink - remove chartjunk and decoration", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Designer", "layer": "slide", "agents": [ "Designer" ], "matchId": "168634ce-84dd-463b-b781-f7304d3b5a61", "evidence": "The chart appears to have a high data-ink ratio, with a clear focus on presenting the data.", "pageRefs": null, "priority": "Core", "whenToUse": null, "confidence": 0.7, "extraction": { "at": "2026-07-16 22:02:11.430524+00", "model": "or:meta-llama/llama-4-scout", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 46, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "Chartjunk Elimination", "slug": "chartjunk-elimination", "status": "active", "bestFor": null, "canonId": "019dd956-b49e-7453-ab01-b60f338eeda1", "version": 1, "bodyDocId": null, "description": "Remove decorative elements that don't convey data: 3D effects, shadows, unnecessary gridlines", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Designer", "layer": "slide", "agents": [ "Designer" ], "matchId": "bed76c6f-3964-4bfb-a21d-8361f306b00d", "evidence": "The slide contains a grouped bar chart with clear labels and a legend, showing a simple and effective visualization of data.", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 0.7, "extraction": { "at": "2026-07-16 22:02:11.509383+00", "model": "or:meta-llama/llama-4-scout", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 47, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "Data-Ink Ratio", "slug": "data-ink-ratio", "status": "active", "bestFor": null, "canonId": "019dd956-afc8-70da-b378-92834d36fde6", "version": 1, "bodyDocId": null, "description": "Maximize data, minimize non-data ink - remove chartjunk and decoration", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Designer", "layer": "slide", "agents": [ "Designer" ], "matchId": "6a027ac1-dceb-46d7-84ed-253f8c51cdc7", "evidence": "The chart appears to have a high data-ink ratio, with a clear focus on presenting the data.", "pageRefs": null, "priority": "Core", "whenToUse": null, "confidence": 0.7, "extraction": { "at": "2026-07-16 22:02:11.548477+00", "model": "or:meta-llama/llama-4-scout", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 47, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "Chartjunk Elimination", "slug": "chartjunk-elimination", "status": "active", "bestFor": null, "canonId": "019dd956-b49e-7453-ab01-b60f338eeda1", "version": 1, "bodyDocId": null, "description": "Remove decorative elements that don't convey data: 3D effects, shadows, unnecessary gridlines", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Designer", "layer": "slide", "agents": [ "Designer" ], "matchId": "22ff21de-b09a-4cfd-81be-7601144b3bc4", "evidence": "The slide contains a grouped bar chart with clear labels and a legend, showing a simple and effective visualization of data.", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 0.7, "extraction": { "at": "2026-07-16 22:02:11.626623+00", "model": "or:meta-llama/llama-4-scout", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 48, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "Data-Ink Ratio", "slug": "data-ink-ratio", "status": "active", "bestFor": null, "canonId": "019dd956-afc8-70da-b378-92834d36fde6", "version": 1, "bodyDocId": null, "description": "Maximize data, minimize non-data ink - remove chartjunk and decoration", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Designer", "layer": "slide", "agents": [ "Designer" ], "matchId": "4841a190-35ee-4d1a-b9c5-5acbf68ad87c", "evidence": "The chart appears to have a high data-ink ratio, with a clear focus on presenting the data.", "pageRefs": null, "priority": "Core", "whenToUse": null, "confidence": 0.7, "extraction": { "at": "2026-07-16 22:02:11.666406+00", "model": "or:meta-llama/llama-4-scout", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 48, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "Chartjunk Elimination", "slug": "chartjunk-elimination", "status": "active", "bestFor": null, "canonId": "019dd956-b49e-7453-ab01-b60f338eeda1", "version": 1, "bodyDocId": null, "description": "Remove decorative elements that don't convey data: 3D effects, shadows, unnecessary gridlines", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Designer", "layer": "slide", "agents": [ "Designer" ], "matchId": "03d4edd9-984d-4bc9-9746-cc796ab25973", "evidence": "The slide contains a grouped bar chart with clear labels and a legend, showing a simple and effective visualization of data.", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 0.7, "extraction": { "at": "2026-07-16 22:02:11.74549+00", "model": "or:meta-llama/llama-4-scout", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 49, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "Data-Ink Ratio", "slug": "data-ink-ratio", "status": "active", "bestFor": null, "canonId": "019dd956-afc8-70da-b378-92834d36fde6", "version": 1, "bodyDocId": null, "description": "Maximize data, minimize non-data ink - remove chartjunk and decoration", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Designer", "layer": "slide", "agents": [ "Designer" ], "matchId": "bd2607e8-a869-45ea-837a-30712538c6cc", "evidence": "The chart appears to have a high data-ink ratio, with a clear focus on presenting the data.", "pageRefs": null, "priority": "Core", "whenToUse": null, "confidence": 0.7, "extraction": { "at": "2026-07-16 22:02:11.790318+00", "model": "or:meta-llama/llama-4-scout", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 49, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "Chartjunk Elimination", "slug": "chartjunk-elimination", "status": "active", "bestFor": null, "canonId": "019dd956-b49e-7453-ab01-b60f338eeda1", "version": 1, "bodyDocId": null, "description": "Remove decorative elements that don't convey data: 3D effects, shadows, unnecessary gridlines", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Designer", "layer": "slide", "agents": [ "Designer" ], "matchId": "72ab6d04-a0aa-4f5f-93f8-de1977cefdcf", "evidence": "The slide contains a grouped bar chart with clear labels and a legend, showing a simple and effective visualization of data.", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 0.7, "extraction": { "at": "2026-07-16 22:02:11.901332+00", "model": "or:meta-llama/llama-4-scout", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 50, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "Data-Ink Ratio", "slug": "data-ink-ratio", "status": "active", "bestFor": null, "canonId": "019dd956-afc8-70da-b378-92834d36fde6", "version": 1, "bodyDocId": null, "description": "Maximize data, minimize non-data ink - remove chartjunk and decoration", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Designer", "layer": "slide", "agents": [ "Designer" ], "matchId": "395fb11a-15d4-404b-b7de-bce833b28ddb", "evidence": "The chart appears to have a high data-ink ratio, with a clear focus on presenting the data.", "pageRefs": null, "priority": "Core", "whenToUse": null, "confidence": 0.7, "extraction": { "at": "2026-07-16 22:02:11.941509+00", "model": "or:meta-llama/llama-4-scout", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 50, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "Chartjunk Elimination", "slug": "chartjunk-elimination", "status": "active", "bestFor": null, "canonId": "019dd956-b49e-7453-ab01-b60f338eeda1", "version": 1, "bodyDocId": null, "description": "Remove decorative elements that don't convey data: 3D effects, shadows, unnecessary gridlines", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Designer", "layer": "slide", "agents": [ "Designer" ], "matchId": "df7dba5e-7cd8-49e1-85c2-a5dd6ec03247", "evidence": "The slide contains a grouped bar chart with clear labels and a legend, showing a simple and effective visualization of data.", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 0.7, "extraction": { "at": "2026-07-16 22:02:12.020396+00", "model": "or:meta-llama/llama-4-scout", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 51, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "Data-Ink Ratio", "slug": "data-ink-ratio", "status": "active", "bestFor": null, "canonId": "019dd956-afc8-70da-b378-92834d36fde6", "version": 1, "bodyDocId": null, "description": "Maximize data, minimize non-data ink - remove chartjunk and decoration", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Designer", "layer": "slide", "agents": [ "Designer" ], "matchId": "dd8dba90-21ba-438d-b703-8bfc0d40afe2", "evidence": "The chart appears to have a high data-ink ratio, with a clear focus on presenting the data.", "pageRefs": null, "priority": "Core", "whenToUse": null, "confidence": 0.7, "extraction": { "at": "2026-07-16 22:02:12.060077+00", "model": "or:meta-llama/llama-4-scout", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 51, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "Chartjunk Elimination", "slug": "chartjunk-elimination", "status": "active", "bestFor": null, "canonId": "019dd956-b49e-7453-ab01-b60f338eeda1", "version": 1, "bodyDocId": null, "description": "Remove decorative elements that don't convey data: 3D effects, shadows, unnecessary gridlines", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Designer", "layer": "slide", "agents": [ "Designer" ], "matchId": "6276ca88-478a-44d2-bee8-86257b7a225d", "evidence": "The slide contains a grouped bar chart with clear labels and a legend, showing a simple and effective visualization of data.", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 0.7, "extraction": { "at": "2026-07-16 22:02:12.139561+00", "model": "or:meta-llama/llama-4-scout", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 52, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "Data-Ink Ratio", "slug": "data-ink-ratio", "status": "active", "bestFor": null, "canonId": "019dd956-afc8-70da-b378-92834d36fde6", "version": 1, "bodyDocId": null, "description": "Maximize data, minimize non-data ink - remove chartjunk and decoration", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Designer", "layer": "slide", "agents": [ "Designer" ], "matchId": "70266368-d518-409b-895b-04e93376f0b4", "evidence": "The chart appears to have a high data-ink ratio, with a clear focus on presenting the data.", "pageRefs": null, "priority": "Core", "whenToUse": null, "confidence": 0.7, "extraction": { "at": "2026-07-16 22:02:12.179674+00", "model": "or:meta-llama/llama-4-scout", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 52, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "Chartjunk Elimination", "slug": "chartjunk-elimination", "status": "active", "bestFor": null, "canonId": "019dd956-b49e-7453-ab01-b60f338eeda1", "version": 1, "bodyDocId": null, "description": "Remove decorative elements that don't convey data: 3D effects, shadows, unnecessary gridlines", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Designer", "layer": "slide", "agents": [ "Designer" ], "matchId": "7241c8cb-e73a-47b1-b6a4-6bb36e74334c", "evidence": "The slide contains a grouped bar chart with clear labels and a legend, showing a simple and effective visualization of data.", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 0.7, "extraction": { "at": "2026-07-16 22:02:12.259275+00", "model": "or:meta-llama/llama-4-scout", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 53, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "Data-Ink Ratio", "slug": "data-ink-ratio", "status": "active", "bestFor": null, "canonId": "019dd956-afc8-70da-b378-92834d36fde6", "version": 1, "bodyDocId": null, "description": "Maximize data, minimize non-data ink - remove chartjunk and decoration", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Designer", "layer": "slide", "agents": [ "Designer" ], "matchId": "e8dcbcdb-b7d8-4fab-bed4-7a425ad133b7", "evidence": "The chart appears to have a high data-ink ratio, with a clear focus on presenting the data.", "pageRefs": null, "priority": "Core", "whenToUse": null, "confidence": 0.7, "extraction": { "at": "2026-07-16 22:02:12.299346+00", "model": "or:meta-llama/llama-4-scout", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 53, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "Chartjunk Elimination", "slug": "chartjunk-elimination", "status": "active", "bestFor": null, "canonId": "019dd956-b49e-7453-ab01-b60f338eeda1", "version": 1, "bodyDocId": null, "description": "Remove decorative elements that don't convey data: 3D effects, shadows, unnecessary gridlines", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Designer", "layer": "slide", "agents": [ "Designer" ], "matchId": "a1be1005-2821-4229-9ab7-c8854cacb46d", "evidence": "The slide contains a grouped bar chart with clear labels and a legend, showing a simple and effective visualization of data.", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 0.7, "extraction": { "at": "2026-07-16 22:02:12.379781+00", "model": "or:meta-llama/llama-4-scout", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 54, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "Data-Ink Ratio", "slug": "data-ink-ratio", "status": "active", "bestFor": null, "canonId": "019dd956-afc8-70da-b378-92834d36fde6", "version": 1, "bodyDocId": null, "description": "Maximize data, minimize non-data ink - remove chartjunk and decoration", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Designer", "layer": "slide", "agents": [ "Designer" ], "matchId": "51cbe3e8-fe15-4f37-83af-48464d34e4d8", "evidence": "The chart appears to have a high data-ink ratio, with a clear focus on presenting the data.", "pageRefs": null, "priority": "Core", "whenToUse": null, "confidence": 0.7, "extraction": { "at": "2026-07-16 22:02:12.419511+00", "model": "or:meta-llama/llama-4-scout", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 54, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null } ], "frameworks": [ { "matchId": "50397989-f813-4278-87f9-fd7e4b88ecc5", "evidence": "The slide explicitly defines two distinct groups of markets based on response patterns and economic characteristics.", "framework": null, "confidence": 1, "extraction": { "at": "2026-05-02 17:31:40.605+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 33, "frameworkName": "audience-segmentation" } ], "patterns": [] }, "storymakers": null, "score": { "backend": "codex", "scoredAt": "2026-05-02 23:13:14.888+00", "subScores": { "scqa_arc": 43, "action_titles": 67, "mece_structure": 62, "closing_strength": 22, "evidence_quality": 85, "clarity_of_thesis": 56, "production_quality": 60, "visual_storytelling": 70 }, "totalScore": 58, "coveragePct": 100, "explanations": { "scqa_arc": "The deck has ingredients of Situation and Complication in slides 6-21 and an implicit Answer in slides 23-27, but it reads mostly as a sequential survey-data dump rather than an explicit SCQA arc.", "action_titles": "The main analytical run uses many insight-bearing titles, for example slide 10 says \"Less than half of ITDMs are seeing positive ROI from their AI investments,\" but appendix and section slides revert to labels.", "mece_structure": "The sectioning from ROI drivers to implementation, challenges, and future investment is broadly logical, but open-source, ROI, pilots, and geography recur across sections and appendices with overlap rather than a fully MECE architecture.", "closing_strength": "Slide 27 offers implicit future optimization themes, but the deck then moves into appendix material and ends on a logo slide rather than a recommendation, decision, or next-step call to action.", "evidence_quality": "Most claims are backed by survey charts, data points, sources, and sample-size notes, especially slides 6-27 and the detailed market appendix.", "clarity_of_thesis": "Slide 4 provides KEY FINDINGS, but the first five slides do not state a single declarative thesis beyond the broad ROI of AI report topic.", "production_quality": "The deck is consistent and source-disciplined, but long headlines, repeated section labels, dense callouts, and low action-title density in slides 34-76 reduce finish quality.", "visual_storytelling": "Slides generally match claims to bar charts, stacked bars, callouts, and tables, but dense layouts such as slides 7, 12, 18, and much of the appendix weaken the visual story." }, "slidesAnalyzed": 77 }, "review": { "backend": null, "verdict": "This is a competent research-report deck with a partial SCQA arc, useful action titles in the main body, and a weak Storymakers close because it never turns findings into a recommendation.", "reviewedAt": "2026-05-01 22:50:53.335+00", "slidesSeen": 77, "suggestions": [ "Move methodology after the key findings or into the appendix, so slide 3 can state the thesis and stakes.", "Add a one-slide synthesis after slide 27 that says what IBM wants the reader to do next based on the ROI gap, implementation barriers, and open-source/cloud findings.", "Rewrite section dividers as MECE claims, for example: 'AI adoption is broad but ROI remains uneven,' 'Scaling is blocked by data and integration,' and '2025 spend shifts toward open-source and managed services.'", "Convert repeated appendix labels into evidence titles or add an appendix guide that tells readers which cuts answer which business question." ], "closingScore": 46, "openingScore": 72, "topStrengths": [ "Slide 4 provides a real executive skim layer by naming strategic commitment, ROI friction, and future open-source/cloud moves before the data sections.", "The main story spine from current ROI (slides 5-12) to implementation (slides 13-18) to challenges (slides 19-21) to future outlook (slides 22-27) is easy to follow.", "Many core body titles are metric-led and declarative, especially slides 6, 10, 11, 18, and 24." ], "topWeaknesses": [ "The opening puts methodology on slide 3 before the answer, weakening the executive hook.", "The narrative stops at observed market intent; slides 23-27 do not translate the evidence into a recommendation, decision, or next step.", "Appendix volume dominates the document, with slides 28-76 largely functioning as supplemental data tables or repeated segment cuts rather than narrative support." ], "narrativeScore": 70, "pillarCritique": "The dividers on slides 5, 13, 19, and 22 are mostly topic chapters: current ROI, implementation, challenges, and future outlook. They are directionally MECE, but they do not read as mutually exclusive argument pillars with claims, and the appendix dividers become pure topic dumps.", "closingCritique": "The last non-appendix stretch (slides 23-27) closes with future investment patterns and optimization tactics, especially slide 27 on open-source and cloud-managed services. There is no explicit call to action, synthesis slide, or memorable final takeaway before the deck drops into appendix from slide 28 onward.", "openingCritique": "The first 5 slides establish context and stakes, but the answer does not arrive until slide 4 after cover, TOC, and methodology. Slide 4 gives useful key findings, yet it reads as a findings summary more than a sharp hook or thesis.", "extractionSeconds": 98.974, "narrativeCritique": "The deck has a recognizable setup -> tension -> analysis -> resolution arc: slide 4 states the key findings, slides 10-11 and 18-21 create ROI and implementation tension, and slides 23-27 move toward 2025 investment priorities. The missing act is a true resolution: the ending reports planned behaviors rather than making an explicit IBM recommendation or decision ask.", "titleQualityScore": 68, "titleQualityCritique": "The main analysis has several strong action titles, such as slide 10, 'Less than half of ITDMs are seeing positive ROI,' and slide 18, which names the pilot launch shortfall. Quality falls sharply in the appendix, where slides 34-54 repeat 'APPENDIX: ADVANCED VS. EMERGING AI ECOSYSTEM MARKETS' and slides 56-73 often use 'ITDMS BY MARKET' as a label." }, "activistThesis": null, "pitchdeck": { "metadata": null, "profile": null }, "slides": [ { "page": 1, "type": "setup", "function": "front_matter", "imagePath": "https://imgproxy.kitesheet.com/N2v9kTr-Vn1y0wD0X6CJLYfcRJXhwvOr2p3el4cPw6Y/rs:fit:1200:1200:0/q:82/f:webp/czM6Ly9raXRlc2hlZXQvY29ycHVzL3NsaWRlcy9mMzI3YmZiNWY4M2UzYzdlL3AwMDEuanBn", "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": 15, "componentCount": 4, "textChars": 150, "nDataPoints": 0, "notes": null, "elementsJson": [ "logo_grid", "photo" ], "confidence": 1, "extraction": { "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "at": "2026-05-02 17:31:31.901+00", "seconds": 3.229, "promptVersion": "v2-canon-conditioned" } }, "links": { "slide": "/slides/019dd923-5e88-73ef-bd5d-e266bb5de1d1/1", "deck": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1", "deckAnchor": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1#slide-1", "deckJson": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1.json" }, "components": [ { "bbox": { "h": 0.012, "w": 0.23, "x": 0.088, "y": 0.903 }, "kind": "disclaimer", "text": "© 2024 Morning Consult. All rights reserved.", "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 17:31:31.901+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "e1c70c7f-ece9-4cf1-a13e-1568b360daf8", "parentComponentId": null }, { "bbox": { "h": 0.035, "w": 0.448, "x": 0.088, "y": 0.135 }, "kind": "image", "text": "Morning Consult and IBM logos", "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": "Logo", "slug": "logo", "status": "active", "canonId": "019de52c-fdaf-743d-94c4-d7c6a0e55302", "version": 1, "description": null }, "framework": null }, "subkind": "logo", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 17:31:31.901+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "af809a1d-68ae-4aec-8ede-c35e3fce8681", "parentComponentId": null }, { "bbox": { "h": 0.07, "w": 0.398, "x": 0.088, "y": 0.58 }, "kind": "paragraph", "text": "For IBM\nDeveloped in collaboration with Lopez Research\nDECEMBER 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 17:31:31.901+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "360c6731-3e96-4f7f-be87-0da711ddf8ab", "parentComponentId": null }, { "bbox": { "h": 0.055, "w": 0.235, "x": 0.088, "y": 0.485 }, "kind": "title", "text": "ROI of 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 17:31:31.901+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "81542d6e-a845-4a84-9b0e-ea9124d1ae37", "parentComponentId": null } ], "metrics": [], "tools": [], "frameworks": [], "arcBeats": [ { "to": 4, "arc": { "name": "The Sparkline", "slug": "sparkline", "status": "active", "bestFor": "Keynotes, TED-style talks", "canonId": "019dd956-606e-720c-905a-42607ac0bf50", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "What Is -> What Could Be -> What Is -> What Could Be -> New Bliss", "description": null, "familyLabel": null }, "from": 1, "name": "Setup", "beatId": "2d39221b-3db7-473d-ba20-268e74c68406", "matchId": "bf9fcf67-d39d-4c8d-8724-bdd9506a6c64", "beatType": { "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." }, "evidence": "The deck begins with an introduction to the topic, methodology, and key findings.", "position": 0, "isPrimaryArc": true, "parentBeatType": null, "alignedBlockIds": null, "matchConfidence": 0.8 } ], "loops": [], "thumbSrc": "https://imgproxy.kitesheet.com/GOIBb7zw1tL_wEV1jUW9zGDmTWUa7NSJPZPpB_7ZSy0/rs:fit:480:480:0/q:78/f:webp/czM6Ly9raXRlc2hlZXQvY29ycHVzL3NsaWRlcy9mMzI3YmZiNWY4M2UzYzdlL3AwMDEuanBn", "imagePathAlt": "https://imgproxy.kitesheet.com/_T8N_9T5KicbiJKRdArFsGYteJ--3GhoETdj4h3ylx8/rs:fit:1200:1200:0/q:82/f:webp/czM6Ly9raXRlc2hlZXQvY29ycHVzL3NsaWRlcy9mMzI3YmZiNWY4M2UzYzdlL3AwMDEucG5n", "thumbSrcAlt": "https://imgproxy.kitesheet.com/_vw_4fzie2_sUSx1Tqt2OQP3yrX6p3MNfjTH5lngRTM/rs:fit:480:480:0/q:78/f:webp/czM6Ly9raXRlc2hlZXQvY29ycHVzL3NsaWRlcy9mMzI3YmZiNWY4M2UzYzdlL3AwMDEucG5n" }, { "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": 12, "componentCount": 2, "textChars": 134, "nDataPoints": 5, "notes": null, "elementsJson": [ "numbered_list" ], "confidence": 1, "extraction": { "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "at": "2026-05-02 17:31:31.111+00", "seconds": 2.11, "promptVersion": "v2-canon-conditioned" } }, "links": { "slide": "/slides/019dd923-5e88-73ef-bd5d-e266bb5de1d1/2", "deck": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1", "deckAnchor": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1#slide-2", "deckJson": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1.json" }, "components": [ { "bbox": { "h": 0.6, "w": 0.4, "x": 0.45, "y": 0.2 }, "kind": "list", "text": "3 Methodology & Key Findings\n5 Current Landscape of AI\n19 Challenges of AI Implementation\n22 Future of AI\n28 Appendix", "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 17:31:31.111+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "ea4da42f-03a2-4b86-9038-0becbf73fb20", "parentComponentId": null }, { "bbox": { "h": 0.15, "w": 0.25, "x": 0.1, "y": 0.4 }, "kind": "title", "text": "Table of 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 17:31:31.111+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "62612092-aa44-483b-b335-c04a3a0fdba6", "parentComponentId": null } ], "metrics": [], "tools": [], "frameworks": [], "arcBeats": [ { "to": 4, "arc": { "name": "The Sparkline", "slug": "sparkline", "status": "active", "bestFor": "Keynotes, TED-style talks", "canonId": "019dd956-606e-720c-905a-42607ac0bf50", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "What Is -> What Could Be -> What Is -> What Could Be -> New Bliss", "description": null, "familyLabel": null }, "from": 1, "name": "Setup", "beatId": "2d39221b-3db7-473d-ba20-268e74c68406", "matchId": "bf9fcf67-d39d-4c8d-8724-bdd9506a6c64", "beatType": { "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." }, "evidence": "The deck begins with an introduction to the topic, methodology, and key findings.", "position": 0, "isPrimaryArc": true, "parentBeatType": null, "alignedBlockIds": null, "matchConfidence": 0.8 } ], "loops": [], "locked": true }, { "page": 3, "type": "setup", "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": "dense", "densityScore": 69, "componentCount": 7, "textChars": 794, "nDataPoints": 24, "notes": null, "elementsJson": [ "paragraph", "bullet_list", "data_table" ], "confidence": 1, "extraction": { "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "at": "2026-05-02 17:31:31.751+00", "seconds": 2.705, "promptVersion": "v2-canon-conditioned" } }, "links": { "slide": "/slides/019dd923-5e88-73ef-bd5d-e266bb5de1d1/3", "deck": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1", "deckAnchor": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1#slide-3", "deckJson": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1.json" }, "components": [ { "bbox": { "h": 0.15, "w": 0.41, "x": 0.057, "y": 0.36 }, "kind": "list", "text": "ITDMs are respondents employed at companies with 101 employees or more, serving in director-level or higher roles within a technology industry/role, with decision-making authority over at least one of the following: management of business consultants/consulting services, purchasing for IT products, or purchasing for business consulting services.", "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 17:31:31.751+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "b69bc49b-1a3d-4fe0-b55b-bf318cc6d839", "parentComponentId": null }, { "bbox": null, "kind": "metric", "text": "Sample Size: 2,413", "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": "2026-04-25 12:20:03+00", "model": "or:google/gemini-3.1-flash-lite-preview", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "019dd952-5644-756a-a846-ac7897487781", "parentComponentId": null }, { "bbox": { "h": 0.06, "w": 0.41, "x": 0.057, "y": 0.58 }, "kind": "paragraph", "text": "The interviews were conducted online, and the data is unweighted. Global results have a margin of error of +/- 2 percentage points.", "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 17:31:31.751+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "845b1bdf-e694-4bb2-aa1c-7a0a55242c65", "parentComponentId": null }, { "bbox": { "h": 0.11, "w": 0.41, "x": 0.057, "y": 0.208 }, "kind": "paragraph", "text": "This survey was fielded October 30 to November 13, 2024, among a sample of 2,413 IT Decision Makers (ITDMS) in US, Canada, Mexico, Brazil, UK, France, Germany, Spain, India, Singapore, Indonesia, and South Korea.", "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 17:31:31.751+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "ba44c41e-6e10-486f-ab93-4e619f6425e6", "parentComponentId": null }, { "bbox": { "h": 0.61, "w": 0.41, "x": 0.524, "y": 0.195 }, "kind": "table", "text": "Table showing sample size and margin of error for ITDMs by country.", "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 17:31:31.751+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "fe12c528-dbb7-4d64-8bf6-67a64a14e366", "parentComponentId": null }, { "bbox": { "h": 0.038, "w": 0.212, "x": 0.057, "y": 0.125 }, "kind": "title", "text": "Methodology", "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 17:31:31.751+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "721f0481-528b-455a-8ee4-32a0c5477554", "parentComponentId": null }, { "bbox": { "h": 0.038, "w": 0.12, "x": 0.524, "y": 0.125 }, "kind": "title", "text": "Audience", "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 17:31:31.751+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "f5c881aa-e7ca-4192-bc46-617d92d3bf37", "parentComponentId": null } ], "metrics": [], "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? 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": "95209b11-21b2-455a-86a5-24b695315539", "evidence": "paragraph/paragraph: This survey was fielded October 30 to November 13, 2024, among a sample of 2,413 IT Decision Makers (ITDMS) in US, Canada, Mexico, Brazil, UK, France, Germany, Spain, India, Singapore, Indonesia, and", "pageRefs": null, "priority": "Core", "whenToUse": null, "confidence": 0.7, "extraction": { "at": "2026-07-17 03:21:16.763156+00", "model": "or:meta-llama/llama-4-scout", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 3, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null } ], "frameworks": [], "arcBeats": [ { "to": 4, "arc": { "name": "The Sparkline", "slug": "sparkline", "status": "active", "bestFor": "Keynotes, TED-style talks", "canonId": "019dd956-606e-720c-905a-42607ac0bf50", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "What Is -> What Could Be -> What Is -> What Could Be -> New Bliss", "description": null, "familyLabel": null }, "from": 1, "name": "Setup", "beatId": "2d39221b-3db7-473d-ba20-268e74c68406", "matchId": "bf9fcf67-d39d-4c8d-8724-bdd9506a6c64", "beatType": { "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." }, "evidence": "The deck begins with an introduction to the topic, methodology, and key findings.", "position": 0, "isPrimaryArc": true, "parentBeatType": null, "alignedBlockIds": null, "matchConfidence": 0.8 } ], "loops": [], "locked": true }, { "page": 4, "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": "balanced", "densityScore": 42, "componentCount": 4, "textChars": 756, "nDataPoints": 2, "notes": null, "elementsJson": [ "headline_text", "bullet_list" ], "confidence": 1, "extraction": { "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "at": "2026-05-02 17:31:32.006+00", "seconds": 2.874, "promptVersion": "v2-canon-conditioned" } }, "links": { "slide": "/slides/019dd923-5e88-73ef-bd5d-e266bb5de1d1/4", "deck": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1", "deckAnchor": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1#slide-4", "deckJson": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1.json" }, "components": [ { "bbox": { "h": 0.35, "w": 0.305, "x": 0.017, "y": 0.118 }, "kind": "list", "text": "Companies are betting on AI for the long term; many prioritize innovation and less than half have achieved positive ROI. Over 8 in 10 ITDMs report that their company has made progress executing their AI strategy, with 43% making significant progress.", "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 17:31:32.006+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "96c02998-51d8-4312-99f5-5241458b404b", "parentComponentId": null }, { "bbox": { "h": 0.35, "w": 0.305, "x": 0.353, "y": 0.118 }, "kind": "list", "text": "Data quality and integration are the most common obstacles for companies when implementing AI, but challenges are relatively diverse in scope. Data quality and availability and integration with existing systems are the most frequent difficulties.", "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 17:31:32.006+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "9d648ca2-7a6f-4fac-9fcb-999eef44e3bb", "parentComponentId": null }, { "bbox": { "h": 0.35, "w": 0.305, "x": 0.688, "y": 0.118 }, "kind": "list", "text": "Moving forward, ITDMs plan to focus on solutions like cloud managed services and open-source as they increase their AI investments. The majority of companies are planning to increase investment in AI and are more likely to be kicking-off AI pilots.", "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 17:31:32.006+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "aeb62ee8-affb-40fd-be5d-b459b54614a7", "parentComponentId": null }, { "bbox": { "h": 0.025, "w": 0.124, "x": 0.017, "y": 0.045 }, "kind": "title", "text": "KEY FINDINGS", "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 17:31:32.006+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "78053deb-f116-4eb4-887b-5f24c6153fb7", "parentComponentId": null } ], "metrics": [], "tools": [], "frameworks": [], "arcBeats": [ { "to": 4, "arc": { "name": "The Sparkline", "slug": "sparkline", "status": "active", "bestFor": "Keynotes, TED-style talks", "canonId": "019dd956-606e-720c-905a-42607ac0bf50", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "What Is -> What Could Be -> What Is -> What Could Be -> New Bliss", "description": null, "familyLabel": null }, "from": 1, "name": "Setup", "beatId": "2d39221b-3db7-473d-ba20-268e74c68406", "matchId": "bf9fcf67-d39d-4c8d-8724-bdd9506a6c64", "beatType": { "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." }, "evidence": "The deck begins with an introduction to the topic, methodology, and key findings.", "position": 0, "isPrimaryArc": true, "parentBeatType": null, "alignedBlockIds": null, "matchConfidence": 0.8 } ], "loops": [], "locked": true }, { "page": 5, "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": 4, "componentCount": 2, "textChars": 77, "nDataPoints": 0, "notes": null, "elementsJson": [ "headline_text" ], "confidence": 1, "extraction": { "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "at": "2026-05-02 17:31:34.083+00", "seconds": 4.868, "promptVersion": "v2-canon-conditioned" } }, "links": { "slide": "/slides/019dd923-5e88-73ef-bd5d-e266bb5de1d1/5", "deck": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1", "deckAnchor": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1#slide-5", "deckJson": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1.json" }, "components": [ { "bbox": { "h": 0.18, "w": 0.5, "x": 0.08, "y": 0.41 }, "kind": "title", "text": "Current Landscape of AI: ROI – Drivers, Measurements, & Achievements", "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 17:31:34.083+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "cb90cbed-4adb-4644-ac39-d455b51cfad0", "parentComponentId": null }, { "bbox": { "h": 0.02, "w": 0.08, "x": 0.08, "y": 0.34 }, "kind": "title", "text": "SECTION 1", "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 17:31:34.083+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "5782799b-c402-47a3-ac71-fbc5a497c5dd", "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": "f7d64907-044e-4501-b75e-a9808f6a7e31", "evidence": "title/headline: Current Landscape of AI: ROI – Drivers, Measurements, & Achievements", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 0.9, "extraction": { "at": "2026-07-17 03:21:16.893187+00", "model": "or:meta-llama/llama-4-scout", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 5, "whyItWorks": null, "antipattern": null, "cardinality": "common", "narrativePurpose": null } ], "frameworks": [], "arcBeats": [], "loops": [], "locked": true }, { "page": 6, "type": "analysis", "title": "Data source: Morning Consult, Sample Size: ITDMs = 2,413", "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": "dense", "densityScore": 54, "componentCount": 6, "textChars": 604, "nDataPoints": 7, "notes": "Data source: Morning Consult, Sample Size: ITDMs = 2,413", "elementsJson": [ "headline_text", "action_title", "bar_chart_horizontal", "callout_box" ], "confidence": 1, "extraction": { "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "at": "2026-05-02 17:31:31.837+00", "seconds": 2.325, "promptVersion": "v2-canon-conditioned" } }, "links": { "slide": "/slides/019dd923-5e88-73ef-bd5d-e266bb5de1d1/6", "deck": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1", "deckAnchor": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1#slide-6", "deckJson": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1.json" }, "components": [ { "bbox": { "h": 0.45, "w": 0.3, "x": 0.65, "y": 0.29 }, "kind": "callout", "text": "Data Deep Dive: Companies in India and Brazil are making notable progress... Companies with over 1,000 employees are making larger strides...", "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 17:31:31.837+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "cc4cad8b-2f22-4bf3-aff4-869cdf2c3b64", "parentComponentId": null }, { "bbox": null, "kind": "callout", "text": "Companies in India and Brazil are making notable progress in their AI strategy, with the majority of ITDMs reporting that their company has made significant progress in execution (Brazil = 61%, India = 87%).", "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": "2026-04-25 12:20:04+00", "model": "or:google/gemini-3.1-flash-lite-preview", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "019dd952-5644-756a-a847-4a301583fafc", "parentComponentId": null }, { "bbox": { "h": 0.55, "w": 0.55, "x": 0.05, "y": 0.295 }, "kind": "chart", "text": "Progress of AI Strategy", "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 17:31:31.837+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "8dd4e6d5-f8fd-4107-a3a4-a617b1dc270b", "parentComponentId": null }, { "bbox": null, "kind": "metric", "text": "Progress of AI Strategy: 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": "2026-04-25 12:20:04+00", "model": "or:google/gemini-3.1-flash-lite-preview", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "019dd952-5644-756a-a847-4f602f2596e9", "parentComponentId": null }, { "bbox": { "h": 0.06, "w": 0.9, "x": 0.05, "y": 0.12 }, "kind": "title", "text": "AI Strategy is advancing at full speed globally – 85% of ITDMs report that their company has made progress in executing their AI strategy", "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 17:31:31.837+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "398e0fbb-6be1-41cc-a300-75f8a340c2b4", "parentComponentId": null }, { "bbox": { "h": 0.03, "w": 0.6, "x": 0.05, "y": 0.07 }, "kind": "title", "text": "CURRENT LANDSCAPE OF AI: ROI – DRIVERS, MEASUREMENTS, & ACHIEVEMENTS", "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 17:31:31.837+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "22ec19b7-9703-477c-bf7d-6bd75f456bdb", "parentComponentId": null } ], "metrics": [], "tools": [], "frameworks": [], "arcBeats": [ { "to": 12, "arc": { "name": "The Sparkline", "slug": "sparkline", "status": "active", "bestFor": "Keynotes, TED-style talks", "canonId": "019dd956-606e-720c-905a-42607ac0bf50", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "What Is -> What Could Be -> What Is -> What Could Be -> New Bliss", "description": null, "familyLabel": null }, "from": 6, "name": "Industry Trends", "beatId": "44ba47c2-bd64-44fb-b74b-8b42654de485", "matchId": "bf9fcf67-d39d-4c8d-8724-bdd9506a6c64", "beatType": null, "evidence": "The deck presents industry trends and data on the current landscape of AI investments and ROI.", "position": 1, "isPrimaryArc": true, "parentBeatType": null, "alignedBlockIds": null, "matchConfidence": 0.8 } ], "loops": [], "locked": true }, { "page": 7, "type": "analysis", "title": "The chart uses a 100% stacked bar format to show the breakdown of motivations.", "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": 76, "componentCount": 8, "textChars": 869, "nDataPoints": 7, "notes": "The chart uses a 100% stacked bar format to show the breakdown of motivations.", "elementsJson": [ "headline_text", "bar_chart_100pct", "callout_box" ], "confidence": 1, "extraction": { "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "at": "2026-05-02 17:31:33.226+00", "seconds": 3.54, "promptVersion": "v2-canon-conditioned" } }, "links": { "slide": "/slides/019dd923-5e88-73ef-bd5d-e266bb5de1d1/7", "deck": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1", "deckAnchor": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1#slide-7", "deckJson": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1.json" }, "components": [ { "bbox": { "h": 0.25, "w": 0.3, "x": 0.65, "y": 0.295 }, "kind": "callout", "text": "Data Deep Dive: Companies in Brazil and Singapore are more likely to be innovation-driven when it comes to implementing AI", "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 17:31:33.226+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "efc39d54-b12f-4ba9-9302-15378aca37e6", "parentComponentId": null }, { "bbox": null, "kind": "callout", "text": "Companies in Brazil and Singapore are more likely to be innovation-driven when it comes to implementing AI (Brazil = 41% innovation-driven vs. 24% ROI-driven, Singapore 44% innovation-driven vs. 31% ROI-driven).", "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": "2026-04-25 12:20:04+00", "model": "or:google/gemini-3.1-flash-lite-preview", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "019dd952-5644-756a-a847-63e8e0ade888", "parentComponentId": null }, { "bbox": { "h": 0.22, "w": 0.63, "x": 0.06, "y": 0.47 }, "kind": "chart", "text": "Motivations Driving AI Implementation", "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": "Stacked bar chart (100%)", "slug": "bar-stacked-100pct", "status": "active", "canonId": "019de52c-ff14-71b8-8d88-860f8d7da84b", "version": 1, "description": null }, "framework": null }, "subkind": "bar-stacked-100pct", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 17:31:33.226+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "510a21e1-7f7a-40ec-b631-def27aaaaf96", "parentComponentId": null }, { "bbox": { "h": 0.03, "w": 0.3, "x": 0.18, "y": 0.94 }, "kind": "disclaimer", "text": "IBM11 What is the primary motivation driving AI implementation at your company? Sample Size: ITDMs = 2,413", "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 17:31:33.226+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "7dc3c5c7-63f1-4c85-b9ad-a320a1b95637", "parentComponentId": null }, { "bbox": { "h": 0.08, "w": 0.5, "x": 0.06, "y": 0.375 }, "kind": "legend", "text": "Completely innovation-driven, Mostly innovation-driven, Equally innovation-driven and ROI-driven, Mostly ROI-driven, Completely ROI-driven", "attrs": null, "canon": { "kind": { "name": "Legend", "slug": "legend", "status": "active", "canonId": "31361933-3d22-4c70-bbad-0801e9fffc0c", "version": 1, "description": "Color/symbol decoder placed adjacent to a chart or diagram." }, "tool": null, "subkind": null, "framework": null }, "subkind": null, "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 17:31:33.226+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "c5155d7b-dac5-4580-b995-c81b6fc89949", "parentComponentId": null }, { "bbox": null, "kind": "metric", "text": "ITDM motivation: 41%", "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": "2026-04-25 12:20:04+00", "model": "or:google/gemini-3.1-flash-lite-preview", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "019dd952-5644-756a-a847-641be465d3a1", "parentComponentId": null }, { "bbox": { "h": 0.06, "w": 0.9, "x": 0.05, "y": 0.12 }, "kind": "title", "text": "ROI is not necessarily the primary driver of AI investments at organizations globally – 41% of ITDMs say their organization is equally innovation-driven and ROI-driven", "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 17:31:33.226+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "6578c5cb-e801-4891-9069-019cce2dd173", "parentComponentId": null }, { "bbox": { "h": 0.03, "w": 0.6, "x": 0.05, "y": 0.07 }, "kind": "title", "text": "CURRENT LANDSCAPE OF AI: ROI – DRIVERS, MEASUREMENTS, & ACHIEVEMENTS", "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 17:31:33.226+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "4344b827-a49e-40c1-b7a9-5d2cfc48d26e", "parentComponentId": null } ], "metrics": [], "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? 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": "8a641f23-25cc-43bc-ad41-63816d6e30a7", "evidence": "ITDMs = 2,413", "pageRefs": null, "priority": "Core", "whenToUse": null, "confidence": 0.6, "extraction": { "at": "2026-07-17 03:21:16.320285+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": "Call to action", "slug": "call-to-action", "status": "active", "bestFor": null, "canonId": "019dd9e1-4bbb-702a-9ead-82daf188bb7c", "version": 1, "bodyDocId": null, "description": "Explicit prescription of what the audience should do next.", "familyLabel": null, "categoryName": null, "categorySlug": null }, "agent": null, "layer": "slide", "agents": null, "matchId": "f10ebcb6-79e7-4cd8-92ed-62cc597b4dcc", "evidence": "The primary motivation driving AI implementation at your company?", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 0.7, "extraction": { "at": "2026-07-17 03:21:16.271985+00", "model": "or:meta-llama/llama-4-scout", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 7, "whyItWorks": null, "antipattern": null, "cardinality": "common", "narrativePurpose": null } ], "frameworks": [], "arcBeats": [ { "to": 12, "arc": { "name": "The Sparkline", "slug": "sparkline", "status": "active", "bestFor": "Keynotes, TED-style talks", "canonId": "019dd956-606e-720c-905a-42607ac0bf50", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "What Is -> What Could Be -> What Is -> What Could Be -> New Bliss", "description": null, "familyLabel": null }, "from": 6, "name": "Industry Trends", "beatId": "44ba47c2-bd64-44fb-b74b-8b42654de485", "matchId": "bf9fcf67-d39d-4c8d-8724-bdd9506a6c64", "beatType": null, "evidence": "The deck presents industry trends and data on the current landscape of AI investments and ROI.", "position": 1, "isPrimaryArc": true, "parentBeatType": null, "alignedBlockIds": null, "matchConfidence": 0.8 } ], "loops": [], "locked": true }, { "page": 8, "type": "analysis", "title": "Data source: Morning Consult, Sample Size: ITDMs = 2,413", "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": "dense", "densityScore": 54, "componentCount": 6, "textChars": 618, "nDataPoints": 5, "notes": "Data source: Morning Consult, Sample Size: ITDMs = 2,413", "elementsJson": [ "headline_text", "bar_chart_horizontal", "callout_box" ], "confidence": 1, "extraction": { "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "at": "2026-05-02 17:31:32.11+00", "seconds": 2.29, "promptVersion": "v2-canon-conditioned" } }, "links": { "slide": "/slides/019dd923-5e88-73ef-bd5d-e266bb5de1d1/8", "deck": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1", "deckAnchor": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1#slide-8", "deckJson": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1.json" }, "components": [ { "bbox": { "h": 0.55, "w": 0.3, "x": 0.65, "y": 0.295 }, "kind": "callout", "text": "Data Deep Dive: Open-Source Insight, South Korea troubleshooting, India/Indonesia innovation", "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 17:31:32.11+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "e80e9437-34fa-424b-8f21-f0963a03fb96", "parentComponentId": null }, { "bbox": null, "kind": "callout", "text": "Faster innovation is a more critical metric at organizations utilizing open-source for AI tooling (26% vs. 19% at companies not using open-source).", "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": "2026-04-25 12:20:03+00", "model": "or:google/gemini-3.1-flash-lite-preview", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "019dd952-5644-756a-a847-311f174e521c", "parentComponentId": null }, { "bbox": { "h": 0.6, "w": 0.45, "x": 0.05, "y": 0.28 }, "kind": "chart", "text": "Most Important Metric When Calculating ROI from AI Investments", "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 17:31:32.11+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "3eb49811-2826-47ca-8727-a09f379b5235", "parentComponentId": null }, { "bbox": null, "kind": "metric", "text": "Most Important Metric When Calculating ROI from AI Investments: 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": "2026-04-25 12:20:03+00", "model": "or:google/gemini-3.1-flash-lite-preview", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "019dd952-5644-756a-a847-363ca28aef78", "parentComponentId": null }, { "bbox": { "h": 0.08, "w": 0.9, "x": 0.05, "y": 0.12 }, "kind": "title", "text": "AI drives value within organizations in different ways based on their values; Companies are more likely to value productivity and efficiency ROI measurements over hard dollar savings", "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 17:31:32.11+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "f6033ce4-129f-4c7c-915e-99622c53a3a2", "parentComponentId": null }, { "bbox": { "h": 0.03, "w": 0.6, "x": 0.05, "y": 0.07 }, "kind": "title", "text": "CURRENT LANDSCAPE OF AI: ROI - DRIVERS, MEASUREMENTS, & ACHIEVEMENTS", "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 17:31:32.11+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "0236059c-a88e-4e44-b536-fbae11a503a5", "parentComponentId": null } ], "metrics": [], "tools": [ { "tool": { "name": "Chartjunk Elimination", "slug": "chartjunk-elimination", "status": "active", "bestFor": null, "canonId": "019dd956-b49e-7453-ab01-b60f338eeda1", "version": 1, "bodyDocId": null, "description": "Remove decorative elements that don't convey data: 3D effects, shadows, unnecessary gridlines", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Designer", "layer": "slide", "agents": [ "Designer" ], "matchId": "f185c3a8-d2b5-42b9-9976-a19612898a03", "evidence": "clear and simple bar chart presentation", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 0.7, "extraction": { "at": "2026-07-16 22:02:07.621517+00", "model": "or:meta-llama/llama-4-scout", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 8, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null } ], "frameworks": [], "arcBeats": [ { "to": 12, "arc": { "name": "The Sparkline", "slug": "sparkline", "status": "active", "bestFor": "Keynotes, TED-style talks", "canonId": "019dd956-606e-720c-905a-42607ac0bf50", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "What Is -> What Could Be -> What Is -> What Could Be -> New Bliss", "description": null, "familyLabel": null }, "from": 6, "name": "Industry Trends", "beatId": "44ba47c2-bd64-44fb-b74b-8b42654de485", "matchId": "bf9fcf67-d39d-4c8d-8724-bdd9506a6c64", "beatType": null, "evidence": "The deck presents industry trends and data on the current landscape of AI investments and ROI.", "position": 1, "isPrimaryArc": true, "parentBeatType": null, "alignedBlockIds": null, "matchConfidence": 0.8 } ], "loops": [], "locked": true }, { "page": 9, "type": "analysis", "title": "The slide uses a clear hierarchy to present survey data on AI strategy success metrics.", "function": "summarize", "rawType": "kpi_dashboard", "block": null, "metadata": { "slideType": "kpi_dashboard", "slideTypeCanon": { "name": "KPI dashboard", "slug": "kpi_dashboard", "status": "active", "canonId": "019de52d-0be5-7295-af4d-b850fe7b7e65", "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": 67, "componentCount": 7, "textChars": 776, "nDataPoints": 7, "notes": "The slide uses a clear hierarchy to present survey data on AI strategy success metrics.", "elementsJson": [ "headline_text", "bar_chart_horizontal", "callout_box" ], "confidence": 1, "extraction": { "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "at": "2026-05-02 17:31:32.943+00", "seconds": 3.069, "promptVersion": "v2-canon-conditioned" } }, "links": { "slide": "/slides/019dd923-5e88-73ef-bd5d-e266bb5de1d1/9", "deck": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1", "deckAnchor": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1#slide-9", "deckJson": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1.json" }, "components": [ { "bbox": { "h": 0.25, "w": 0.3, "x": 0.65, "y": 0.29 }, "kind": "callout", "text": "Data Deep Dive: Open-Source Insight: Companies utilizing open-source (23%) place more value on greater product innovation as an indicator of a successful AI strategy than those not using open-source (18%).", "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 17:31:32.943+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "759e7b57-5b5d-47d6-b445-f8b5cfa20cc0", "parentComponentId": null }, { "bbox": null, "kind": "callout", "text": "Companies utilizing open-source (23%) place more value on greater product innovation as an indicator of a successful AI strategy than those not using open-source (18%).", "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": "2026-04-25 12:20:04+00", "model": "or:google/gemini-3.1-flash-lite-preview", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "019dd952-5644-756a-a847-e2051bf696e2", "parentComponentId": null }, { "bbox": { "h": 0.5, "w": 0.4, "x": 0.05, "y": 0.28 }, "kind": "chart", "text": "Most Important Indicators of a Successful AI Strategy", "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 17:31:32.943+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "db149241-5c82-4db3-8880-dba93d288715", "parentComponentId": null }, { "bbox": null, "kind": "metric", "text": "Most Important Indicators of a Successful AI Strategy: 32%", "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": "2026-04-25 12:20:04+00", "model": "or:google/gemini-3.1-flash-lite-preview", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "019dd952-5644-756a-a847-e5411a35d3e7", "parentComponentId": null }, { "bbox": { "h": 0.03, "w": 0.4, "x": 0.18, "y": 0.93 }, "kind": "source-note", "text": "IBM13 Which outcome is most important to demonstrate the success of your company's AI strategy? Sample Size: ITDMs = 2,413", "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 17:31:32.943+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "d010de01-6e73-4e53-b5ce-a8e51c72b1c3", "parentComponentId": null }, { "bbox": { "h": 0.06, "w": 0.8, "x": 0.05, "y": 0.12 }, "kind": "title", "text": "Increased IT operations efficiency emerges as the most important indicator of a successful AI strategy", "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 17:31:32.943+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "f3d16167-1e17-4183-a4d2-5ba8de0389f7", "parentComponentId": null }, { "bbox": { "h": 0.03, "w": 0.6, "x": 0.05, "y": 0.07 }, "kind": "title", "text": "CURRENT LANDSCAPE OF AI: ROI - DRIVERS, MEASUREMENTS, & ACHIEVEMENTS", "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 17:31:32.943+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "b2ec4087-9b7d-4377-8eee-12747e54c18f", "parentComponentId": null } ], "metrics": [], "tools": [], "frameworks": [], "arcBeats": [ { "to": 12, "arc": { "name": "The Sparkline", "slug": "sparkline", "status": "active", "bestFor": "Keynotes, TED-style talks", "canonId": "019dd956-606e-720c-905a-42607ac0bf50", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "What Is -> What Could Be -> What Is -> What Could Be -> New Bliss", "description": null, "familyLabel": null }, "from": 6, "name": "Industry Trends", "beatId": "44ba47c2-bd64-44fb-b74b-8b42654de485", "matchId": "bf9fcf67-d39d-4c8d-8724-bdd9506a6c64", "beatType": null, "evidence": "The deck presents industry trends and data on the current landscape of AI investments and ROI.", "position": 1, "isPrimaryArc": true, "parentBeatType": null, "alignedBlockIds": null, "matchConfidence": 0.8 } ], "loops": [], "locked": true }, { "page": 10, "type": "analysis", "title": "The slide uses a horizontal bar chart to visualize survey results regarding AI ROI.", "function": "analyze_data", "rawType": "market_landscape", "block": null, "metadata": { "slideType": "market_landscape", "slideTypeCanon": { "name": "Market landscape", "slug": "market_landscape", "status": "active", "canonId": "019de52d-0b6d-75db-a946-9ac362e3afc2", "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": "dense", "densityScore": 57, "componentCount": 7, "textChars": 461, "nDataPoints": 6, "notes": "The slide uses a horizontal bar chart to visualize survey results regarding AI ROI.", "elementsJson": [ "bar_chart_horizontal", "callout_box" ], "confidence": 1, "extraction": { "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "at": "2026-05-02 17:31:33.709+00", "seconds": 3.632, "promptVersion": "v2-canon-conditioned" } }, "links": { "slide": "/slides/019dd923-5e88-73ef-bd5d-e266bb5de1d1/10", "deck": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1", "deckAnchor": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1#slide-10", "deckJson": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1.json" }, "components": [ { "bbox": { "h": 0.45, "w": 0.3, "x": 0.65, "y": 0.29 }, "kind": "callout", "text": "Data Deep Dive: Open-Source Insight and France regional performance", "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 17:31:33.709+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "fedf1c96-76cb-45aa-8879-9a647890f9d6", "parentComponentId": null }, { "bbox": null, "kind": "callout", "text": "Companies utilizing open-source ecosystems are achieving positive ROI at greater rates than those that are not.", "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": "2026-04-25 12:20:03+00", "model": "or:google/gemini-3.1-flash-lite-preview", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "019dd952-5644-756a-a847-004bda63e19a", "parentComponentId": null }, { "bbox": { "h": 0.5, "w": 0.35, "x": 0.05, "y": 0.28 }, "kind": "chart", "text": "ROI From 2024 AI Investments", "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 17:31:33.709+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "1244b07e-a31b-4d2e-9b7f-a363f1b92faa", "parentComponentId": null }, { "bbox": null, "kind": "metric", "text": "ROI status: 47%", "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": "2026-04-25 12:20:03+00", "model": "or:google/gemini-3.1-flash-lite-preview", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "019dd952-5644-756a-a847-04e709b823fc", "parentComponentId": null }, { "bbox": { "h": 0.03, "w": 0.3, "x": 0.18, "y": 0.94 }, "kind": "source-note", "text": "IBM14 How would you rate ROI from your company's AI investments in 2024? Sample Size: ITDMs = 2,413", "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 17:31:33.709+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "b6879009-bb4d-4f20-8907-60c81150482e", "parentComponentId": null }, { "bbox": { "h": 0.04, "w": 0.7, "x": 0.05, "y": 0.12 }, "kind": "title", "text": "Less than half of ITDMs are seeing positive ROI from their 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 17:31:33.709+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "cab5d05d-4534-48e5-8cc1-e946d0986a3a", "parentComponentId": null }, { "bbox": { "h": 0.03, "w": 0.6, "x": 0.05, "y": 0.07 }, "kind": "title", "text": "CURRENT LANDSCAPE OF AI: ROI – DRIVERS, MEASUREMENTS, & ACHIEVEMENTS", "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 17:31:33.709+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "32c91095-564d-4bde-aea2-d33bd507cf7b", "parentComponentId": null } ], "metrics": [], "tools": [], "frameworks": [], "arcBeats": [ { "to": 12, "arc": { "name": "The Sparkline", "slug": "sparkline", "status": "active", "bestFor": "Keynotes, TED-style talks", "canonId": "019dd956-606e-720c-905a-42607ac0bf50", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "What Is -> What Could Be -> What Is -> What Could Be -> New Bliss", "description": null, "familyLabel": null }, "from": 6, "name": "Industry Trends", "beatId": "44ba47c2-bd64-44fb-b74b-8b42654de485", "matchId": "bf9fcf67-d39d-4c8d-8724-bdd9506a6c64", "beatType": null, "evidence": "The deck presents industry trends and data on the current landscape of AI investments and ROI.", "position": 1, "isPrimaryArc": true, "parentBeatType": null, "alignedBlockIds": null, "matchConfidence": 0.8 } ], "loops": [], "locked": true }, { "page": 11, "type": "analysis", "title": "Sample size: 1,132 ITDMs at companies not currently seeing positive ROI from AI.", "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": "balanced", "densityScore": 40, "componentCount": 5, "textChars": 449, "nDataPoints": 6, "notes": "Sample size: 1,132 ITDMs at companies not currently seeing positive ROI from AI.", "elementsJson": [ "headline_text", "bar_chart_horizontal", "footnote" ], "confidence": 1, "extraction": { "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "at": "2026-05-02 17:31:32.29+00", "seconds": 2.118, "promptVersion": "v2-canon-conditioned" } }, "links": { "slide": "/slides/019dd923-5e88-73ef-bd5d-e266bb5de1d1/11", "deck": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1", "deckAnchor": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1#slide-11", "deckJson": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1.json" }, "components": [ { "bbox": { "h": 0.5, "w": 0.9, "x": 0.05, "y": 0.295 }, "kind": "chart", "text": "Expected Timeline for Achieving Positive ROI", "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 17:31:32.29+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "b3f52a02-c849-4d13-8c7a-5cbe6e00df2e", "parentComponentId": null }, { "bbox": null, "kind": "metric", "text": "Expected timeline for positive ROI: 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": "2026-04-25 12:20:04+00", "model": "or:google/gemini-3.1-flash-lite-preview", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "019dd952-5644-756a-a847-96aea39fa7f3", "parentComponentId": null }, { "bbox": { "h": 0.04, "w": 0.4, "x": 0.18, "y": 0.93 }, "kind": "source-note", "text": "IBM15 When do you expect your company will see positive ROI from its AI investments? Sample Size: ITDMs at Companies Not Currently Seeing Positive ROI from AI = 1,132", "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 17:31:32.29+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "81664a83-e25f-4ed4-b1c4-10542c9fed80", "parentComponentId": null }, { "bbox": { "h": 0.06, "w": 0.9, "x": 0.05, "y": 0.12 }, "kind": "title", "text": "Among ITDMs at companies not currently achieving positive ROI from AI, only about 1 in 4 expect to see positive ROI in the next year", "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 17:31:32.29+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "7e753edb-dadb-41b7-895c-12311e494144", "parentComponentId": null }, { "bbox": { "h": 0.03, "w": 0.6, "x": 0.05, "y": 0.07 }, "kind": "title", "text": "CURRENT LANDSCAPE OF AI: ROI - DRIVERS, MEASUREMENTS, & ACHIEVEMENTS", "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 17:31:32.29+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "d9cccb31-f57c-404a-87bd-7df13df4df1d", "parentComponentId": null } ], "metrics": [], "tools": [], "frameworks": [], "arcBeats": [ { "to": 12, "arc": { "name": "The Sparkline", "slug": "sparkline", "status": "active", "bestFor": "Keynotes, TED-style talks", "canonId": "019dd956-606e-720c-905a-42607ac0bf50", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "What Is -> What Could Be -> What Is -> What Could Be -> New Bliss", "description": null, "familyLabel": null }, "from": 6, "name": "Industry Trends", "beatId": "44ba47c2-bd64-44fb-b74b-8b42654de485", "matchId": "bf9fcf67-d39d-4c8d-8724-bdd9506a6c64", "beatType": null, "evidence": "The deck presents industry trends and data on the current landscape of AI investments and ROI.", "position": 1, "isPrimaryArc": true, "parentBeatType": null, "alignedBlockIds": null, "matchConfidence": 0.8 } ], "loops": [], "locked": true }, { "page": 12, "type": "analysis", "title": "Data source: Morning Consult, Sample Size: ITDMs = 2,413", "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": "balanced", "densityScore": 44, "componentCount": 5, "textChars": 489, "nDataPoints": 16, "notes": "Data source: Morning Consult, Sample Size: ITDMs = 2,413", "elementsJson": [ "bar_chart_100pct", "headline_text" ], "confidence": 1, "extraction": { "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "at": "2026-05-02 17:31:33.769+00", "seconds": 3.423, "promptVersion": "v2-canon-conditioned" } }, "links": { "slide": "/slides/019dd923-5e88-73ef-bd5d-e266bb5de1d1/12", "deck": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1", "deckAnchor": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1#slide-12", "deckJson": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1.json" }, "components": [ { "bbox": { "h": 0.6, "w": 0.8, "x": 0.12, "y": 0.28 }, "kind": "chart", "text": "Most Influential Factors Impacting the ROI of AI Investments", "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": "Stacked bar chart (100%)", "slug": "bar-stacked-100pct", "status": "active", "canonId": "019de52c-ff14-71b8-8d88-860f8d7da84b", "version": 1, "description": null }, "framework": null }, "subkind": "bar-stacked-100pct", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 17:31:33.769+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "544384a7-44a2-441d-a076-c419ce4fdc4b", "parentComponentId": null }, { "bbox": null, "kind": "metric", "text": "ROI impact ranking: 33%", "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": "2026-04-25 12:20:04+00", "model": "or:google/gemini-3.1-flash-lite-preview", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "019dd952-5644-756a-a847-ae923e33c738", "parentComponentId": null }, { "bbox": { "h": 0.04, "w": 0.7, "x": 0.18, "y": 0.093 }, "kind": "source-note", "text": "IBM16 What factors do you think most impact the ROI of your company's AI investments? Please rank the top 4 options, with 1 being the most impactful and 4 being the fourth most impactful. Sample Size: ITDMs = 2,413", "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 17:31:33.769+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "02f45a5c-ee3e-47d4-b811-700c97a2da30", "parentComponentId": null }, { "bbox": { "h": 0.06, "w": 0.85, "x": 0.05, "y": 0.12 }, "kind": "title", "text": "ITDMs are most likely to consider business value/vision the most impactful factor influencing the ROI of AI at their company", "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 17:31:33.769+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "31b9a35f-3fd2-4cf0-be48-19adde1ec95e", "parentComponentId": null }, { "bbox": { "h": 0.03, "w": 0.6, "x": 0.05, "y": 0.07 }, "kind": "title", "text": "CURRENT LANDSCAPE OF AI: ROI – DRIVERS, MEASUREMENTS, & ACHIEVEMENTS", "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 17:31:33.769+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "289f1c89-25c9-4a1b-8d6f-587e16e93f0d", "parentComponentId": null } ], "metrics": [], "tools": [], "frameworks": [], "arcBeats": [ { "to": 12, "arc": { "name": "The Sparkline", "slug": "sparkline", "status": "active", "bestFor": "Keynotes, TED-style talks", "canonId": "019dd956-606e-720c-905a-42607ac0bf50", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "What Is -> What Could Be -> What Is -> What Could Be -> New Bliss", "description": null, "familyLabel": null }, "from": 6, "name": "Industry Trends", "beatId": "44ba47c2-bd64-44fb-b74b-8b42654de485", "matchId": "bf9fcf67-d39d-4c8d-8724-bdd9506a6c64", "beatType": null, "evidence": "The deck presents industry trends and data on the current landscape of AI investments and ROI.", "position": 1, "isPrimaryArc": true, "parentBeatType": null, "alignedBlockIds": null, "matchConfidence": 0.8 } ], "loops": [], "locked": true }, { "page": 13, "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": 3, "componentCount": 2, "textChars": 51, "nDataPoints": 0, "notes": null, "elementsJson": [ "headline_text" ], "confidence": 1, "extraction": { "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "at": "2026-05-02 17:31:35.063+00", "seconds": 4.602, "promptVersion": "v2-canon-conditioned" } }, "links": { "slide": "/slides/019dd923-5e88-73ef-bd5d-e266bb5de1d1/13", "deck": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1", "deckAnchor": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1#slide-13", "deckJson": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1.json" }, "components": [ { "bbox": { "h": 0.13, "w": 0.45, "x": 0.08, "y": 0.41 }, "kind": "title", "text": "Current Landscape of AI: AI Implementation", "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 17:31:35.063+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "a4aaf1e1-dcc0-473d-bb05-733e5c847ce0", "parentComponentId": null }, { "bbox": { "h": 0.03, "w": 0.08, "x": 0.08, "y": 0.34 }, "kind": "title", "text": "SECTION 1", "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 17:31:35.063+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "e30dc573-9206-4fa2-b956-ed72a2d01985", "parentComponentId": null } ], "metrics": [], "tools": [], "frameworks": [], "arcBeats": [], "loops": [], "locked": true }, { "page": 14, "type": "analysis", "title": "The slide uses a callout box to provide regional context for open-source adoption.", "function": "analyze_data", "rawType": "market_landscape", "block": null, "metadata": { "slideType": "market_landscape", "slideTypeCanon": { "name": "Market landscape", "slug": "market_landscape", "status": "active", "canonId": "019de52d-0b6d-75db-a946-9ac362e3afc2", "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": "dense", "densityScore": 68, "componentCount": 7, "textChars": 818, "nDataPoints": 8, "notes": "The slide uses a callout box to provide regional context for open-source adoption.", "elementsJson": [ "bar_chart_horizontal", "callout_box" ], "confidence": 1, "extraction": { "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "at": "2026-05-02 17:31:33.688+00", "seconds": 3.123, "promptVersion": "v2-canon-conditioned" } }, "links": { "slide": "/slides/019dd923-5e88-73ef-bd5d-e266bb5de1d1/14", "deck": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1", "deckAnchor": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1#slide-14", "deckJson": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1.json" }, "components": [ { "bbox": { "h": 0.3, "w": 0.3, "x": 0.65, "y": 0.29 }, "kind": "callout", "text": "Data Deep Dive: Open-source is especially popular in Mexico (65%), Spain (66%), Indonesia (73%), South Korea (75%), and India (89%), where two-thirds or more indicate that their company is sourcing their AI tools via open-source ecosystems.", "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 17:31:33.688+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "a15968f2-e7fc-4b16-9ac0-900784a59b89", "parentComponentId": null }, { "bbox": null, "kind": "callout", "text": "Open-source is especially popular in Mexico (65%), Spain (66%), Indonesia (73%), South Korea (75%), and India (89%), where two-thirds or more indicate that their company is sourcing their AI tools via open-source ecosystems.", "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": "2026-04-25 12:20:05+00", "model": "or:google/gemini-3.1-flash-lite-preview", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "019dd952-5644-756a-a848-101f8f9f86f4", "parentComponentId": null }, { "bbox": { "h": 0.5, "w": 0.5, "x": 0.05, "y": 0.3 }, "kind": "chart", "text": "Source of AI Tools", "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 17:31:33.688+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "c477b241-ce46-4c92-86e3-f954448f1e5e", "parentComponentId": null }, { "bbox": { "h": 0.03, "w": 0.4, "x": 0.05, "y": 0.94 }, "kind": "disclaimer", "text": "IBM6 Where does your company source your AI tools? Please select all that apply. Sample Size: ITDMs = 2,413", "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 17:31:33.688+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "e80da575-2375-4e2f-828c-4ad40cb2970a", "parentComponentId": null }, { "bbox": null, "kind": "metric", "text": "AI tool sourcing preference: 61%", "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": "2026-04-25 12:20:05+00", "model": "or:google/gemini-3.1-flash-lite-preview", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "019dd952-5644-756a-a848-1463de8b6034", "parentComponentId": null }, { "bbox": { "h": 0.08, "w": 0.9, "x": 0.05, "y": 0.12 }, "kind": "title", "text": "Open-source ecosystems are crucial to AI strategy, with 6-in-10 ITDMs reporting that their company is using open-source ecosystems to source their AI tools", "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 17:31:33.688+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "cec6e577-ab3c-4b05-b606-8552b2a4711b", "parentComponentId": null }, { "bbox": { "h": 0.03, "w": 0.4, "x": 0.05, "y": 0.07 }, "kind": "title", "text": "CURRENT LANDSCAPE OF AI: AI IMPLEMENTATION", "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 17:31:33.688+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "f1f9281e-9aa3-4a56-b935-518288809275", "parentComponentId": null } ], "metrics": [], "tools": [], "frameworks": [], "arcBeats": [], "loops": [], "locked": true }, { "page": 15, "type": "analysis", "title": "The slide uses a 100% stacked bar chart to visualize the distribution of open-source adoption in AI.", "function": "summarize", "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": "summarize", "functionCanon": { "name": "Summarize", "slug": "summarize", "status": "active", "canonId": "019de52d-1541-704f-b86f-bf7b75056373", "version": 1, "description": null }, "density": "dense", "densityScore": 67, "componentCount": 7, "textChars": 749, "nDataPoints": 9, "notes": "The slide uses a 100% stacked bar chart to visualize the distribution of open-source adoption in AI.", "elementsJson": [ "bar_chart_100pct", "callout_box" ], "confidence": 1, "extraction": { "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "at": "2026-05-02 17:31:37.155+00", "seconds": 6.44, "promptVersion": "v2-canon-conditioned" } }, "links": { "slide": "/slides/019dd923-5e88-73ef-bd5d-e266bb5de1d1/15", "deck": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1", "deckAnchor": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1#slide-15", "deckJson": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1.json" }, "components": [ { "bbox": { "h": 0.4, "w": 0.3, "x": 0.65, "y": 0.295 }, "kind": "callout", "text": "Data Deep Dive: A significant proportion (over 50%) of AI solutions at companies in Brazil (44%), India (48%), Mexico (50%), and Indonesia (56%) are based on open-source. As company size increases, so does the likelihood...", "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 17:31:37.155+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "1a93baa3-c7ee-4459-9e04-b3d7e0b45000", "parentComponentId": null }, { "bbox": null, "kind": "callout", "text": "A significant proportion (over 50%) of AI solutions at companies in Brazil (44%), Mexico (50%), and Indonesia (56%) are based on open-source.", "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": "2026-04-25 12:20:05+00", "model": "or:google/gemini-3.1-flash-lite-preview", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "019dd952-5644-756a-a847-faa201232f29", "parentComponentId": null }, { "bbox": { "h": 0.4, "w": 0.6, "x": 0.07, "y": 0.3 }, "kind": "chart", "text": "Percentage of AI Solutions Based on Open-Source", "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": "Stacked bar chart (100%)", "slug": "bar-stacked-100pct", "status": "active", "canonId": "019de52c-ff14-71b8-8d88-860f8d7da84b", "version": 1, "description": null }, "framework": null }, "subkind": "bar-stacked-100pct", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 17:31:37.155+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "8eff70ae-2518-4d01-a5fb-ec41b9d3d859", "parentComponentId": null }, { "bbox": null, "kind": "metric", "text": "Percentage of AI solutions based on open-source: 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": "2026-04-25 12:20:05+00", "model": "or:google/gemini-3.1-flash-lite-preview", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "019dd952-5644-756a-a847-ff4dc740bdeb", "parentComponentId": null }, { "bbox": { "h": 0.05, "w": 0.5, "x": 0.05, "y": 0.93 }, "kind": "source-note", "text": "IBM10 What percentage of your company's current AI solutions or platforms are based on open-source? Sample Size: ITDMs = 2,413", "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 17:31:37.155+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "805c83f6-fb9e-4a22-ad9e-48eb17bb6d0a", "parentComponentId": null }, { "bbox": { "h": 0.08, "w": 0.9, "x": 0.05, "y": 0.12 }, "kind": "title", "text": "Over 80% of ITDMs report that at least a quarter of their company's AI solutions or platforms are based on open-source", "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 17:31:37.155+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "0a60453f-6e99-43b1-94f4-eb9f1698b296", "parentComponentId": null }, { "bbox": { "h": 0.03, "w": 0.4, "x": 0.05, "y": 0.07 }, "kind": "title", "text": "CURRENT LANDSCAPE OF AI: AI IMPLEMENTATION", "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 17:31:37.155+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "4c30dce3-534a-4aa8-bd20-02f318ef8797", "parentComponentId": null } ], "metrics": [], "tools": [], "frameworks": [], "arcBeats": [], "loops": [], "locked": true }, { "page": 16, "type": "analysis", "title": "The slide highlights that 58% of ITDMs transition in less than a year, with a specific callout for larger enterprises.", "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": "dense", "densityScore": 66, "componentCount": 7, "textChars": 763, "nDataPoints": 6, "notes": "The slide highlights that 58% of ITDMs transition in less than a year, with a specific callout for larger enterprises.", "elementsJson": [ "headline_text", "bar_chart_horizontal", "callout_box" ], "confidence": 1, "extraction": { "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "at": "2026-05-02 17:31:36.669+00", "seconds": 5.897, "promptVersion": "v2-canon-conditioned" } }, "links": { "slide": "/slides/019dd923-5e88-73ef-bd5d-e266bb5de1d1/16", "deck": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1", "deckAnchor": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1#slide-16", "deckJson": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1.json" }, "components": [ { "bbox": { "h": 0.35, "w": 0.3, "x": 0.65, "y": 0.029 }, "kind": "callout", "text": "Data Deep Dive: 1 in 5 ITDMs at companies with over 5,000 employees say their company typically transitions from pilot to full production in less than 6 months, compared to only about 10% of those at smaller businesses.", "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 17:31:36.669+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "2aea54fb-fcdf-499f-a457-3e4bff0ff375", "parentComponentId": null }, { "bbox": null, "kind": "callout", "text": "58% of ITDMs report that their company typically moves from pilot to full production in less than a year.", "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": "2026-04-25 12:20:05+00", "model": "or:google/gemini-3.1-flash-lite-preview", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "019dd952-5644-756a-a848-4aea71003617", "parentComponentId": null }, { "bbox": { "h": 0.55, "w": 0.35, "x": 0.15, "y": 0.28 }, "kind": "chart", "text": "Average Length of Time to Transition From Pilot to Full 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": "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 17:31:36.669+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "0c55df50-8f74-4fb1-b38d-8cbef5010b0a", "parentComponentId": null }, { "bbox": null, "kind": "metric", "text": "Transition time from pilot to production: 58%", "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": "2026-04-25 12:20:05+00", "model": "or:google/gemini-3.1-flash-lite-preview", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "019dd952-5644-756a-a848-4c2f24599180", "parentComponentId": null }, { "bbox": { "h": 0.05, "w": 0.6, "x": 0.05, "y": 0.93 }, "kind": "source-note", "text": "IBM4 On average, how long does it take your organization to transition from launching an AI pilot to full production? Sample Size: ITDMs = 2,413", "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 17:31:36.669+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "fb22bd43-238e-4f29-b89b-db87e2d48aed", "parentComponentId": null }, { "bbox": { "h": 0.08, "w": 0.9, "x": 0.05, "y": 0.12 }, "kind": "title", "text": "Most organizations are rapidly moving from AI pilots to full production, suggesting a need for processes that enable efficient project scaling", "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 17:31:36.669+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "2468450a-327f-4b91-bd8c-6dbfa26adaa8", "parentComponentId": null }, { "bbox": { "h": 0.03, "w": 0.4, "x": 0.05, "y": 0.07 }, "kind": "title", "text": "CURRENT LANDSCAPE OF AI: AI IMPLEMENTATION", "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 17:31:36.669+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "c3b2dbc2-b368-46d7-b477-ccb303590093", "parentComponentId": null } ], "metrics": [], "tools": [], "frameworks": [], "arcBeats": [], "loops": [], "locked": true }, { "page": 17, "type": "analysis", "title": "The chart highlights that the majority of companies are scaling AI pilots beyond the initial 1-10 range.", "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": "dense", "densityScore": 63, "componentCount": 7, "textChars": 621, "nDataPoints": 9, "notes": "The chart highlights that the majority of companies are scaling AI pilots beyond the initial 1-10 range.", "elementsJson": [ "headline_text", "bar_chart_horizontal", "callout_box" ], "confidence": 1, "extraction": { "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "at": "2026-05-02 17:31:33.95+00", "seconds": 2.966, "promptVersion": "v2-canon-conditioned" } }, "links": { "slide": "/slides/019dd923-5e88-73ef-bd5d-e266bb5de1d1/17", "deck": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1", "deckAnchor": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1#slide-17", "deckJson": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1.json" }, "components": [ { "bbox": { "h": 0.45, "w": 0.3, "x": 0.65, "y": 0.29 }, "kind": "callout", "text": "Data Deep Dive: A third or more of ITDMs in Brazil (33%), Indonesia (35%), and India (45%) will have started 21+ AI pilots in 2024. Large enterprises are starting AI pilots at a greater rate than smaller companies.", "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 17:31:33.95+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "e981888c-ac90-4795-962d-cfd22f1ea27d", "parentComponentId": null }, { "bbox": null, "kind": "callout", "text": "A third or more of ITDMs in Brazil (33%), Indonesia (35%), and India (45%) will have started 21+ AI pilots in 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": "2026-04-25 12:20:05+00", "model": "or:google/gemini-3.1-flash-lite-preview", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "019dd952-5644-756a-a848-329515c1266b", "parentComponentId": null }, { "bbox": { "h": 0.55, "w": 0.55, "x": 0.05, "y": 0.29 }, "kind": "chart", "text": "Number of AI Pilots Started in 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 17:31:33.95+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "1a31d242-b468-4795-81de-51a897c2fb8b", "parentComponentId": null }, { "bbox": null, "kind": "metric", "text": "Number of AI Pilots: 71%", "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": "2026-04-25 12:20:05+00", "model": "or:google/gemini-3.1-flash-lite-preview", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "019dd952-5644-756a-a848-35bcecce8e6e", "parentComponentId": null }, { "bbox": { "h": 0.05, "w": 0.4, "x": 0.05, "y": 0.93 }, "kind": "source-note", "text": "IBM2 By the end of the year, how many AI pilots will your company have started in 2024? Sample Size: ITDMs = 2,413", "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 17:31:33.95+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "d1f54340-b72a-4e99-8eb9-2468047db06d", "parentComponentId": null }, { "bbox": { "h": 0.04, "w": 0.8, "x": 0.05, "y": 0.12 }, "kind": "title", "text": "By the end of 2024, 71% of companies will have started more than 10 AI pilots", "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 17:31:33.95+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "3d916f59-d789-432b-81c8-bd0a78db1778", "parentComponentId": null }, { "bbox": { "h": 0.03, "w": 0.45, "x": 0.05, "y": 0.07 }, "kind": "title", "text": "CURRENT LANDSCAPE OF AI: AI IMPLEMENTATION", "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 17:31:33.95+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "841e7b61-ca63-4bf7-9aea-7965d2b8c325", "parentComponentId": null } ], "metrics": [], "tools": [], "frameworks": [], "arcBeats": [], "loops": [], "locked": true }, { "page": 18, "type": "analysis", "function": "summarize", "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": "summarize", "functionCanon": { "name": "Summarize", "slug": "summarize", "status": "active", "canonId": "019de52d-1541-704f-b86f-bf7b75056373", "version": 1, "description": null }, "density": "dense", "densityScore": 71, "componentCount": 7, "textChars": 921, "nDataPoints": 14, "notes": null, "elementsJson": [ "headline_text", "bar_chart_vertical", "callout_box" ], "confidence": 1, "extraction": { "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "at": "2026-05-02 17:31:34.76+00", "seconds": 3.687, "promptVersion": "v2-canon-conditioned" } }, "links": { "slide": "/slides/019dd923-5e88-73ef-bd5d-e266bb5de1d1/18", "deck": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1", "deckAnchor": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1#slide-18", "deckJson": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1.json" }, "components": [ { "bbox": { "h": 0.6, "w": 0.3, "x": 0.65, "y": 0.28 }, "kind": "callout", "text": "Data Deep Dive: 60% or more of ITDMs in Canada (61%), France (61%), Spain (63%), the UK (64%), South Korea (65%), Germany (67%), and Singapore (73%) say that half or less of their 2024 AI pilots will have fully launched by the end of the year.", "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 17:31:34.76+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "978f69dc-71f6-4a1a-8deb-53e2191cadec", "parentComponentId": null }, { "bbox": null, "kind": "callout", "text": "60% or more of ITDMs in Canada (61%), France (61%), Spain (63%), the UK (64%), South Korea (65%), Germany (67%), and Singapore (73%) say that half or less of their 2024 AI pilots will have fully launched by the end of the year.", "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": "2026-04-25 12:20:06+00", "model": "or:google/gemini-3.1-flash-lite-preview", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "019dd952-5644-756a-a848-c22d9ed7ab9e", "parentComponentId": null }, { "bbox": { "h": 0.6, "w": 0.6, "x": 0.05, "y": 0.28 }, "kind": "chart", "text": "Percentage of 2024 AI Pilots Fully Launched in 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": "Vertical bar chart", "slug": "bar-vertical", "status": "active", "canonId": "019de52c-fe9d-70f2-b3b7-a9ae294f5917", "version": 1, "description": null }, "framework": null }, "subkind": "bar-vertical", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 17:31:34.76+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "ca23dc04-dc92-4766-b4bc-3cd287383cfd", "parentComponentId": null }, { "bbox": null, "kind": "metric", "text": "Percentage of 2024 AI Pilots Fully Launched: 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": "2026-04-25 12:20:06+00", "model": "or:google/gemini-3.1-flash-lite-preview", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "019dd952-5644-756a-a848-c41cf9234732", "parentComponentId": null }, { "bbox": { "h": 0.03, "w": 0.5, "x": 0.05, "y": 0.94 }, "kind": "source-note", "text": "IBM3 What percentage of the AI pilots started in 2024 will have fully launched by the end of the year? Sample Size: ITDMs at companies that have started AI pilots in 2024 = 2,393", "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 17:31:34.76+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "6bfd652d-24d9-45a5-b008-0130845c9d2c", "parentComponentId": null }, { "bbox": { "h": 0.07, "w": 0.9, "x": 0.05, "y": 0.12 }, "kind": "title", "text": "However, over 50% of ITDMs report that half or less of the AI pilots started in 2024 will have fully launched by the end of the year", "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 17:31:34.76+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "4bdb6c00-5aac-40a4-a449-597067fdd725", "parentComponentId": null }, { "bbox": { "h": 0.03, "w": 0.4, "x": 0.05, "y": 0.07 }, "kind": "title", "text": "CURRENT LANDSCAPE OF AI: AI IMPLEMENTATION", "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 17:31:34.76+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "b39a117b-a75c-4de2-b35a-09d32c6d20f5", "parentComponentId": null } ], "metrics": [], "tools": [], "frameworks": [], "arcBeats": [], "loops": [], "locked": true }, { "page": 19, "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": 3, "componentCount": 2, "textChars": 40, "nDataPoints": 0, "notes": null, "elementsJson": [ "headline_text" ], "confidence": 1, "extraction": { "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "at": "2026-05-02 17:31:35.127+00", "seconds": 3.835, "promptVersion": "v2-canon-conditioned" } }, "links": { "slide": "/slides/019dd923-5e88-73ef-bd5d-e266bb5de1d1/19", "deck": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1", "deckAnchor": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1#slide-19", "deckJson": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1.json" }, "components": [ { "bbox": { "h": 0.06, "w": 0.45, "x": 0.08, "y": 0.42 }, "kind": "title", "text": "Challenges of AI Implementation", "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 17:31:35.127+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "9f0668cf-03b5-496b-804f-a21b70712fe6", "parentComponentId": null }, { "bbox": { "h": 0.03, "w": 0.08, "x": 0.08, "y": 0.34 }, "kind": "title", "text": "SECTION 2", "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 17:31:35.127+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "193ae9b1-360a-489d-9607-b12f3e639479", "parentComponentId": null } ], "metrics": [], "tools": [], "frameworks": [], "arcBeats": [], "loops": [], "locked": true }, { "page": 20, "type": "analysis", "title": "The slide uses a 'Data Deep Dive' callout box to provide granular insights based on company size, open-source usage, and management level.", "function": "diagnose", "rawType": "pain_points", "block": null, "metadata": { "slideType": "pain_points", "slideTypeCanon": { "name": "Pain points", "slug": "pain_points", "status": "active", "canonId": "019de52d-08a0-761d-a14f-1dbc5e447381", "version": 1, "description": null }, "function": "diagnose", "functionCanon": { "name": "Diagnose", "slug": "diagnose", "status": "active", "canonId": "019de52d-1657-7223-acc5-7437d878c850", "version": 1, "description": null }, "density": "dense", "densityScore": 64, "componentCount": 7, "textChars": 624, "nDataPoints": 13, "notes": "The slide uses a 'Data Deep Dive' callout box to provide granular insights based on company size, open-source usage, and management level.", "elementsJson": [ "bar_chart_horizontal", "callout_box" ], "confidence": 1, "extraction": { "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "at": "2026-05-02 17:31:33.696+00", "seconds": 2.393, "promptVersion": "v2-canon-conditioned" } }, "links": { "slide": "/slides/019dd923-5e88-73ef-bd5d-e266bb5de1d1/20", "deck": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1", "deckAnchor": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1#slide-20", "deckJson": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1.json" }, "components": [ { "bbox": { "h": 0.55, "w": 0.3, "x": 0.65, "y": 0.28 }, "kind": "callout", "text": "Data Deep Dive: Open-Source Insight, Employee adoption, Senior management perspectives", "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 17:31:33.696+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "5381a5ca-f89f-49a1-a368-308f38934140", "parentComponentId": null }, { "bbox": null, "kind": "callout", "text": "Open-Source Insight: Lack of AI governance is a more significant challenge at companies using open source (Using open-source = 25%, Not using open-source = 17%).", "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": "2026-04-25 12:20:05+00", "model": "or:google/gemini-3.1-flash-lite-preview", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "019dd952-5644-756a-a848-607c8cc0f298", "parentComponentId": null }, { "bbox": { "h": 0.55, "w": 0.45, "x": 0.05, "y": 0.28 }, "kind": "chart", "text": "Significant Challenges When Implementing AI", "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 17:31:33.696+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "e5e0947b-7656-484e-ab03-920e54a0ebb7", "parentComponentId": null }, { "bbox": { "h": 0.03, "w": 0.35, "x": 0.18, "y": 0.93 }, "kind": "disclaimer", "text": "IBM7 How challenging are the following obstacles for your company when implementing AI? Sample Size: ITDMs = 2,413", "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 17:31:33.696+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "162576be-fabd-4dc4-b841-c99b5bd26368", "parentComponentId": null }, { "bbox": null, "kind": "metric", "text": "Percentage of ITDMs selecting 'Very challenging': 23%", "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": "2026-04-25 12:20:05+00", "model": "or:google/gemini-3.1-flash-lite-preview", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "019dd952-5644-756a-a848-65cd5ffef075", "parentComponentId": null }, { "bbox": { "h": 0.06, "w": 0.85, "x": 0.05, "y": 0.12 }, "kind": "title", "text": "Companies face a broad range of significant challenges as they implement AI, highlighting the complexity of their operating environments", "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 17:31:33.696+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "fdf2a8a9-2d08-4ddc-a82f-d8f0d7980fd1", "parentComponentId": null }, { "bbox": { "h": 0.03, "w": 0.35, "x": 0.05, "y": 0.07 }, "kind": "title", "text": "Challenges of AI Implementation", "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 17:31:33.696+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "bfbba2c9-75da-42cf-b2ee-d91b42ca462b", "parentComponentId": null } ], "metrics": [], "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? 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": "f027a20b-f5a6-42d8-99a5-0c321ef2cfd5", "evidence": "The slide mentions 'ITDMs' and provides sample size, indicating the audience is IT Decision Makers.", "pageRefs": null, "priority": "Core", "whenToUse": null, "confidence": 0.7, "extraction": { "at": "2026-07-16 22:02:16.081352+00", "model": "or:meta-llama/llama-4-scout", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 20, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null } ], "frameworks": [], "arcBeats": [ { "to": 21, "arc": { "name": "The Sparkline", "slug": "sparkline", "status": "active", "bestFor": "Keynotes, TED-style talks", "canonId": "019dd956-606e-720c-905a-42607ac0bf50", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "What Is -> What Could Be -> What Is -> What Could Be -> New Bliss", "description": null, "familyLabel": null }, "from": 20, "name": "Complication", "beatId": "720f580e-8d58-4365-a3b1-f2b9161624b6", "matchId": "bf9fcf67-d39d-4c8d-8724-bdd9506a6c64", "beatType": { "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." }, "evidence": "The deck highlights the challenges of AI implementation, including data quality and availability issues.", "position": 2, "isPrimaryArc": true, "parentBeatType": null, "alignedBlockIds": null, "matchConfidence": 0.8 } ], "loops": [ { "to": 21, "from": 20, "loop": { "name": "27_cost_of_inaction", "slug": "27-cost-of-inaction", "status": "active", "bestFor": "Urgent budget requests, compliance, risk mitigation", "canonId": "019dd956-70d1-7395-a15b-857ba858b394", "version": 1, "bodyDocId": "019df22a-2420-77be-bc41-ded96d08cb21", "structure": "The Status Quo -> The Hidden Costs Accumulating -> The Future State of Inaction -> The Tipping Point", "description": "Quantify what happens if the audience does nothing", "familyLabel": null }, "matchId": "f4039535-f8b3-4195-8482-c0b0a421a4ab", "evidence": "The deck highlights the challenges of AI implementation and the need to address them.", "position": 0, "objective": "What are the consequences of not addressing AI implementation challenges?", "confidence": 0.7, "extraction": { "at": "2026-07-16 21:24:12.414721+00", "model": "or:meta-llama/llama-4-scout", "runId": null, "seconds": null, "promptVersion": "doc-narrative-v1" } } ], "locked": true }, { "page": 21, "type": "analysis", "title": "The slide highlights data-related issues as the primary barrier to AI scaling.", "function": "diagnose", "rawType": "pain_points", "block": null, "metadata": { "slideType": "pain_points", "slideTypeCanon": { "name": "Pain points", "slug": "pain_points", "status": "active", "canonId": "019de52d-08a0-761d-a14f-1dbc5e447381", "version": 1, "description": null }, "function": "diagnose", "functionCanon": { "name": "Diagnose", "slug": "diagnose", "status": "active", "canonId": "019de52d-1657-7223-acc5-7437d878c850", "version": 1, "description": null }, "density": "dense", "densityScore": 68, "componentCount": 7, "textChars": 820, "nDataPoints": 9, "notes": "The slide highlights data-related issues as the primary barrier to AI scaling.", "elementsJson": [ "headline_text", "action_title", "bar_chart_horizontal", "callout_box" ], "confidence": 1, "extraction": { "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "at": "2026-05-02 17:31:38.058+00", "seconds": 6.4, "promptVersion": "v2-canon-conditioned" } }, "links": { "slide": "/slides/019dd923-5e88-73ef-bd5d-e266bb5de1d1/21", "deck": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1", "deckAnchor": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1#slide-21", "deckJson": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1.json" }, "components": [ { "bbox": { "h": 0.3, "w": 0.3, "x": 0.65, "y": 0.29 }, "kind": "callout", "text": "Data Deep Dive: Data quality and availability is a more common issue at companies with 5,000 or fewer 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 17:31:38.058+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "3bffdc85-c8a1-4609-af97-c6ba0c3d76ee", "parentComponentId": null }, { "bbox": null, "kind": "callout", "text": "Data quality and availability is a more common issue at companies with 5,000 or fewer employees (101-1,000 employees = 51%, 1,001-5,000 employees = 51%, >5,000 employees = 44%).", "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": "2026-04-25 12:20:06+00", "model": "or:google/gemini-3.1-flash-lite-preview", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "019dd952-5644-756a-a848-908072dd59e7", "parentComponentId": null }, { "bbox": { "h": 0.6, "w": 0.55, "x": 0.05, "y": 0.295 }, "kind": "chart", "text": "Obstacles Faced When Implementing AI Pilot Projects", "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 17:31:38.058+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "16e93d7c-4d3b-43a2-9c71-3f921979c7ee", "parentComponentId": null }, { "bbox": { "h": 0.04, "w": 0.8, "x": 0.05, "y": 0.94 }, "kind": "disclaimer", "text": "IBM5 Which of the following obstacles, if any, has your company encountered when moving AI projects from pilot to full implementation? Please select all that apply. Sample Size: ITDMs at Companies that have Launched an AI Pilot = 2,409", "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 17:31:38.058+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "92f9875d-fb09-4e8b-8ae1-2abb9fb8a17c", "parentComponentId": null }, { "bbox": null, "kind": "metric", "text": "Percentage of ITDMs selecting obstacle: 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": "2026-04-25 12:20:06+00", "model": "or:google/gemini-3.1-flash-lite-preview", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "019dd952-5644-756a-a848-955f86fc3c83", "parentComponentId": null }, { "bbox": { "h": 0.08, "w": 0.85, "x": 0.05, "y": 0.12 }, "kind": "title", "text": "Data quality and availability and integration with existing systems are the most common challenges companies face as they move AI projects from pilot to full implementation", "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 17:31:38.058+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "bbc80dc1-405f-4a31-a830-412abac88947", "parentComponentId": null }, { "bbox": { "h": 0.03, "w": 0.35, "x": 0.05, "y": 0.07 }, "kind": "title", "text": "CHALLENGES OF AI IMPLEMENTATION", "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 17:31:38.058+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "5f320a09-c141-4af4-8405-88332f7390ae", "parentComponentId": null } ], "metrics": [], "tools": [ { "tool": { "name": "Problem Statement Canvas", "slug": "problem-statement-canvas", "status": "active", "bestFor": null, "canonId": "019dd956-839d-744b-ad11-9bf3e3642a18", "version": 1, "bodyDocId": null, "description": "Structured definition of the problem: What? Who? Where? When? Scale?", "familyLabel": null, "categoryName": "Block", "categorySlug": "block" }, "agent": "Architect", "layer": "slide", "agents": [ "Architect" ], "matchId": "02058c14-bbd0-4924-a990-920c4ee5ae8e", "evidence": "The slide highlights specific challenges companies face when moving AI projects from pilot to full implementation.", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 0.6, "extraction": { "at": "2026-07-16 22:02:16.163221+00", "model": "or:meta-llama/llama-4-scout", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 21, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null } ], "frameworks": [], "arcBeats": [ { "to": 21, "arc": { "name": "The Sparkline", "slug": "sparkline", "status": "active", "bestFor": "Keynotes, TED-style talks", "canonId": "019dd956-606e-720c-905a-42607ac0bf50", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "What Is -> What Could Be -> What Is -> What Could Be -> New Bliss", "description": null, "familyLabel": null }, "from": 20, "name": "Complication", "beatId": "720f580e-8d58-4365-a3b1-f2b9161624b6", "matchId": "bf9fcf67-d39d-4c8d-8724-bdd9506a6c64", "beatType": { "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." }, "evidence": "The deck highlights the challenges of AI implementation, including data quality and availability issues.", "position": 2, "isPrimaryArc": true, "parentBeatType": null, "alignedBlockIds": null, "matchConfidence": 0.8 } ], "loops": [ { "to": 21, "from": 20, "loop": { "name": "27_cost_of_inaction", "slug": "27-cost-of-inaction", "status": "active", "bestFor": "Urgent budget requests, compliance, risk mitigation", "canonId": "019dd956-70d1-7395-a15b-857ba858b394", "version": 1, "bodyDocId": "019df22a-2420-77be-bc41-ded96d08cb21", "structure": "The Status Quo -> The Hidden Costs Accumulating -> The Future State of Inaction -> The Tipping Point", "description": "Quantify what happens if the audience does nothing", "familyLabel": null }, "matchId": "f4039535-f8b3-4195-8482-c0b0a421a4ab", "evidence": "The deck highlights the challenges of AI implementation and the need to address them.", "position": 0, "objective": "What are the consequences of not addressing AI implementation challenges?", "confidence": 0.7, "extraction": { "at": "2026-07-16 21:24:12.414721+00", "model": "or:meta-llama/llama-4-scout", "runId": null, "seconds": null, "promptVersion": "doc-narrative-v1" } } ], "locked": true }, { "page": 22, "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": 2, "componentCount": 2, "textChars": 21, "nDataPoints": 0, "notes": null, "elementsJson": [ "headline_text" ], "confidence": 1, "extraction": { "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "at": "2026-05-02 17:31:35.654+00", "seconds": 3.565, "promptVersion": "v2-canon-conditioned" } }, "links": { "slide": "/slides/019dd923-5e88-73ef-bd5d-e266bb5de1d1/22", "deck": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1", "deckAnchor": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1#slide-22", "deckJson": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1.json" }, "components": [ { "bbox": { "h": 0.07, "w": 0.22, "x": 0.08, "y": 0.42 }, "kind": "title", "text": "Future of 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 17:31:35.654+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "832eac46-782c-4d1b-a2d7-a6af11a444b4", "parentComponentId": null }, { "bbox": { "h": 0.03, "w": 0.08, "x": 0.08, "y": 0.34 }, "kind": "title", "text": "SECTION 3", "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 17:31:35.654+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "21f8b2a3-542b-4be0-89f9-bf02df574670", "parentComponentId": null } ], "metrics": [], "tools": [], "frameworks": [], "arcBeats": [], "loops": [], "locked": true }, { "page": 23, "type": "analysis", "title": "The slide uses a grouped horizontal bar chart to compare two years of survey data, supplemented by a 'Data Deep Dive' callout box highlighting specific segments", "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": "dense", "densityScore": 63, "componentCount": 7, "textChars": 595, "nDataPoints": 12, "notes": "The slide uses a grouped horizontal bar chart to compare two years of survey data, supplemented by a 'Data Deep Dive' callout box highlighting specific segments (open-source users and geographic regions).", "elementsJson": [ "bar_chart_grouped", "callout_box" ], "confidence": 1, "extraction": { "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "at": "2026-05-02 17:31:34.871+00", "seconds": 2.73, "promptVersion": "v2-canon-conditioned" } }, "links": { "slide": "/slides/019dd923-5e88-73ef-bd5d-e266bb5de1d1/23", "deck": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1", "deckAnchor": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1#slide-23", "deckJson": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1.json" }, "components": [ { "bbox": { "h": 0.48, "w": 0.3, "x": 0.65, "y": 0.29 }, "kind": "callout", "text": "Data Deep Dive: Open-Source Insight and Geographic trends", "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 17:31:34.871+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "46c20c6f-de47-4231-bdd9-e312191f987b", "parentComponentId": null }, { "bbox": null, "kind": "callout", "text": "4 in 10 open-source users are planning to start more than 20 pilots in '25.", "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": "2026-04-25 12:20:05+00", "model": "or:google/gemini-3.1-flash-lite-preview", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "019dd952-5644-756a-a848-7aec97f2a18b", "parentComponentId": null }, { "bbox": { "h": 0.6, "w": 0.45, "x": 0.08, "y": 0.28 }, "kind": "chart", "text": "Number of AI Pilots Planned for 2024 vs. 2025", "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": "Grouped bar chart", "slug": "bar-grouped", "status": "active", "canonId": "019de52c-ff3b-751e-a8ff-f21ff11097b1", "version": 1, "description": null }, "framework": null }, "subkind": "bar-grouped", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 17:31:34.871+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "5f61d372-be6e-42ce-93b5-81acd188b2bb", "parentComponentId": null }, { "bbox": null, "kind": "metric", "text": "Percentage of ITDMs: 33%", "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": "2026-04-25 12:20:05+00", "model": "or:google/gemini-3.1-flash-lite-preview", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "019dd952-5644-756a-a848-7ca7442f8f9a", "parentComponentId": null }, { "bbox": { "h": 0.03, "w": 0.6, "x": 0.18, "y": 0.094 }, "kind": "source-note", "text": "IBM8 How many AI pilots does your company have planned for 2025? // IBM2 By the end of the year, how many AI pilots will yourcompany have started in 2024? Sample Size: ITDMs = 2,413", "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 17:31:34.871+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "ac6ef974-e290-4a76-8fe9-7ebb7f1a41bd", "parentComponentId": null }, { "bbox": { "h": 0.08, "w": 0.9, "x": 0.05, "y": 0.12 }, "kind": "title", "text": "ITDMs are more optimistic about the number of AI pilots their company will start in 2025; Around a third say their company has plans to start more than 20 AI pilots, compared to only around 20% in 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 17:31:34.871+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "9a97e778-8642-4031-ac6f-740e7097f16f", "parentComponentId": null }, { "bbox": { "h": 0.03, "w": 0.12, "x": 0.05, "y": 0.07 }, "kind": "title", "text": "FUTURE OF 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 17:31:34.871+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "87a8468b-cbd2-41e1-b991-936507d5530b", "parentComponentId": null } ], "metrics": [], "tools": [], "frameworks": [], "arcBeats": [ { "to": 26, "arc": { "name": "The Sparkline", "slug": "sparkline", "status": "active", "bestFor": "Keynotes, TED-style talks", "canonId": "019dd956-606e-720c-905a-42607ac0bf50", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "What Is -> What Could Be -> What Is -> What Could Be -> New Bliss", "description": null, "familyLabel": null }, "from": 23, "name": "Development", "beatId": "22874121-9055-4ce2-b5b1-e6a4c001108a", "matchId": "bf9fcf67-d39d-4c8d-8724-bdd9506a6c64", "beatType": { "name": "Development", "slug": "development", "status": "active", "canonId": "019dd9b8-0332-7008-b3aa-11b0840a57b1", "version": 1, "description": "The middle stretch in arcs that have one. Often where length problems creep in." }, "evidence": "The deck discusses the future of AI investments and plans for 2025.", "position": 3, "isPrimaryArc": true, "parentBeatType": null, "alignedBlockIds": null, "matchConfidence": 0.8 } ], "loops": [ { "to": 26, "from": 23, "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": "d7f608c3-cad7-441c-9fc4-3ef2dbe8a2c7", "evidence": "The deck discusses the future of AI investments and plans for 2025.", "position": 1, "objective": "Why is now the right time to invest in AI?", "confidence": 0.7, "extraction": { "at": "2026-07-16 21:24:12.45473+00", "model": "or:meta-llama/llama-4-scout", "runId": null, "seconds": null, "promptVersion": "doc-narrative-v1" } } ], "locked": true }, { "page": 24, "type": "analysis", "title": "The slide uses a flow-chart style layout to connect high-level budget decisions to granular percentage changes.", "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": "dense", "densityScore": 72, "componentCount": 8, "textChars": 660, "nDataPoints": 12, "notes": "The slide uses a flow-chart style layout to connect high-level budget decisions to granular percentage changes.", "elementsJson": [ "headline_text", "bar_chart_horizontal", "callout_box" ], "confidence": 1, "extraction": { "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "at": "2026-05-02 17:31:41.734+00", "seconds": 9.561, "promptVersion": "v2-canon-conditioned" } }, "links": { "slide": "/slides/019dd923-5e88-73ef-bd5d-e266bb5de1d1/24", "deck": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1", "deckAnchor": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1#slide-24", "deckJson": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1.json" }, "components": [ { "bbox": { "h": 0.4, "w": 0.3, "x": 0.65, "y": 0.3 }, "kind": "callout", "text": "Data Deep Dive: Open-Source Insight and regional investment trends.", "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 17:31:41.734+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "1ff67e39-3449-41c5-bf3e-6b534c37c31b", "parentComponentId": null }, { "bbox": null, "kind": "callout", "text": "Companies using open-source for AI tooling are even more likely to be increasing their AI investment in 2025 (Using open-source = 65%, Not using open-source = 58%).", "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": "2026-04-25 12:20:06+00", "model": "or:google/gemini-3.1-flash-lite-preview", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "019dd952-5644-756a-a848-a8230267b484", "parentComponentId": null }, { "bbox": { "h": 0.5, "w": 0.3, "x": 0.05, "y": 0.3 }, "kind": "chart", "text": "2025 AI Budget Allocation", "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 17:31:41.734+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "007347a9-f32f-4468-9a52-17807f85dd8b", "parentComponentId": null }, { "bbox": { "h": 0.2, "w": 0.25, "x": 0.37, "y": 0.32 }, "kind": "chart", "text": "Percent Increase in AI Investment", "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 17:31:41.734+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "689054e2-dca1-47e6-8940-30a50bb8139e", "parentComponentId": null }, { "bbox": { "h": 0.2, "w": 0.25, "x": 0.295, "y": 0.59 }, "kind": "chart", "text": "Percent Decrease in AI Investment", "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 17:31:41.734+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "b83afac5-3f18-4b94-8060-fe1b5e0f39a0", "parentComponentId": null }, { "bbox": null, "kind": "metric", "text": "AI investment intent: 62%", "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": "2026-04-25 12:20:06+00", "model": "or:google/gemini-3.1-flash-lite-preview", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "019dd952-5644-756a-a848-ae7babc2b9d1", "parentComponentId": null }, { "bbox": { "h": 0.05, "w": 0.9, "x": 0.05, "y": 0.93 }, "kind": "source-note", "text": "IBM17 How does your company plan to allocate its AI budget in 2025? // IBM17a How much does your companyplan to increase its AI investment? // IBM17b How much does your company plan to decrease its AI investment? Sample Size: ITDMs = 2,413", "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 17:31:41.734+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "b5f62751-87be-4ac2-a16d-dbeabb1cd075", "parentComponentId": null }, { "bbox": { "h": 0.05, "w": 0.7, "x": 0.05, "y": 0.12 }, "kind": "title", "text": "Companies are largely planning to increase their investments in AI in 2025", "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 17:31:41.734+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "25337756-d9e6-41c2-ac0d-3545f77fe007", "parentComponentId": null } ], "metrics": [], "tools": [], "frameworks": [], "arcBeats": [ { "to": 26, "arc": { "name": "The Sparkline", "slug": "sparkline", "status": "active", "bestFor": "Keynotes, TED-style talks", "canonId": "019dd956-606e-720c-905a-42607ac0bf50", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "What Is -> What Could Be -> What Is -> What Could Be -> New Bliss", "description": null, "familyLabel": null }, "from": 23, "name": "Development", "beatId": "22874121-9055-4ce2-b5b1-e6a4c001108a", "matchId": "bf9fcf67-d39d-4c8d-8724-bdd9506a6c64", "beatType": { "name": "Development", "slug": "development", "status": "active", "canonId": "019dd9b8-0332-7008-b3aa-11b0840a57b1", "version": 1, "description": "The middle stretch in arcs that have one. Often where length problems creep in." }, "evidence": "The deck discusses the future of AI investments and plans for 2025.", "position": 3, "isPrimaryArc": true, "parentBeatType": null, "alignedBlockIds": null, "matchConfidence": 0.8 } ], "loops": [ { "to": 26, "from": 23, "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": "d7f608c3-cad7-441c-9fc4-3ef2dbe8a2c7", "evidence": "The deck discusses the future of AI investments and plans for 2025.", "position": 1, "objective": "Why is now the right time to invest in AI?", "confidence": 0.7, "extraction": { "at": "2026-07-16 21:24:12.45473+00", "model": "or:meta-llama/llama-4-scout", "runId": null, "seconds": null, "promptVersion": "doc-narrative-v1" } } ], "locked": true }, { "page": 25, "type": "analysis", "title": "The chart highlights the top 4 categories with a purple box.", "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": "balanced", "densityScore": 39, "componentCount": 5, "textChars": 413, "nDataPoints": 9, "notes": "The chart highlights the top 4 categories with a purple box.", "elementsJson": [ "bar_chart_horizontal", "headline_text" ], "confidence": 1, "extraction": { "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "at": "2026-05-02 17:31:34.734+00", "seconds": 2.441, "promptVersion": "v2-canon-conditioned" } }, "links": { "slide": "/slides/019dd923-5e88-73ef-bd5d-e266bb5de1d1/25", "deck": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1", "deckAnchor": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1#slide-25", "deckJson": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1.json" }, "components": [ { "bbox": { "h": 0.5, "w": 0.8, "x": 0.05, "y": 0.295 }, "kind": "chart", "text": "Top Areas for Allocating AI Investments in 2025", "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 17:31:34.734+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "fe47f54a-4b1a-4c58-8758-71c75cf354ce", "parentComponentId": null }, { "bbox": null, "kind": "metric", "text": "Percentage of ITDMs: 63%", "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": "2026-04-25 12:20:06+00", "model": "or:google/gemini-3.1-flash-lite-preview", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "019dd952-5644-756a-a849-12bc0ddd00ba", "parentComponentId": null }, { "bbox": { "h": 0.03, "w": 0.5, "x": 0.18, "y": 0.93 }, "kind": "source-note", "text": "IBM18 In which areas is your company most interested in allocating its AI investments in 2025? Please select up to three options. Sample Size: ITDMs = 2,413", "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 17:31:34.734+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "e93433af-f336-4f74-ac20-99eb50863ba9", "parentComponentId": null }, { "bbox": { "h": 0.08, "w": 0.9, "x": 0.05, "y": 0.12 }, "kind": "title", "text": "Companies are most interested in allocating their AI investments in IT operations; Data quality, product innovation, and software coding are also popular areas for investment", "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 17:31:34.734+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "89bc7135-3c42-4f03-879a-73a075149121", "parentComponentId": null }, { "bbox": { "h": 0.02, "w": 0.1, "x": 0.05, "y": 0.07 }, "kind": "title", "text": "FUTURE OF 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": "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 17:31:34.734+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "6cb33d27-5a23-44c3-8291-ab095a303db3", "parentComponentId": null } ], "metrics": [], "tools": [ { "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": "c881801d-f481-4ef3-bbd7-27b75e80c969", "evidence": "The slide implies a matrix or list of areas for AI investment, but no clear 2x2 matrix is visible.", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 0.5, "extraction": { "at": "2026-07-16 22:02:16.359146+00", "model": "or:meta-llama/llama-4-scout", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 25, "whyItWorks": null, "antipattern": null, "cardinality": "common", "narrativePurpose": null } ], "frameworks": [], "arcBeats": [ { "to": 26, "arc": { "name": "The Sparkline", "slug": "sparkline", "status": "active", "bestFor": "Keynotes, TED-style talks", "canonId": "019dd956-606e-720c-905a-42607ac0bf50", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "What Is -> What Could Be -> What Is -> What Could Be -> New Bliss", "description": null, "familyLabel": null }, "from": 23, "name": "Development", "beatId": "22874121-9055-4ce2-b5b1-e6a4c001108a", "matchId": "bf9fcf67-d39d-4c8d-8724-bdd9506a6c64", "beatType": { "name": "Development", "slug": "development", "status": "active", "canonId": "019dd9b8-0332-7008-b3aa-11b0840a57b1", "version": 1, "description": "The middle stretch in arcs that have one. Often where length problems creep in." }, "evidence": "The deck discusses the future of AI investments and plans for 2025.", "position": 3, "isPrimaryArc": true, "parentBeatType": null, "alignedBlockIds": null, "matchConfidence": 0.8 } ], "loops": [ { "to": 26, "from": 23, "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": "d7f608c3-cad7-441c-9fc4-3ef2dbe8a2c7", "evidence": "The deck discusses the future of AI investments and plans for 2025.", "position": 1, "objective": "Why is now the right time to invest in AI?", "confidence": 0.7, "extraction": { "at": "2026-07-16 21:24:12.45473+00", "model": "or:meta-llama/llama-4-scout", "runId": null, "seconds": null, "promptVersion": "doc-narrative-v1" } } ], "locked": true }, { "page": 26, "type": "analysis", "title": "The chart shows a shift towards higher percentages of open-source usage in 2025 compared to 2024.", "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": "dense", "densityScore": 70, "componentCount": 7, "textChars": 894, "nDataPoints": 10, "notes": "The chart shows a shift towards higher percentages of open-source usage in 2025 compared to 2024.", "elementsJson": [ "headline_text", "bar_chart_grouped", "callout_box" ], "confidence": 1, "extraction": { "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "at": "2026-05-02 17:31:35.67+00", "seconds": 3.255, "promptVersion": "v2-canon-conditioned" } }, "links": { "slide": "/slides/019dd923-5e88-73ef-bd5d-e266bb5de1d1/26", "deck": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1", "deckAnchor": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1#slide-26", "deckJson": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1.json" }, "components": [ { "bbox": { "h": 0.5, "w": 0.3, "x": 0.65, "y": 0.029 }, "kind": "callout", "text": "Data Deep Dive: Over 40% of businesses that currently base less than a quarter of their AI solutions on open-source plan to increase this share in 2025. Indian companies are especially likely to increase open-source usage.", "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 17:31:35.67+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "def59666-aca3-4b07-9b29-bf11aebafe8a", "parentComponentId": null }, { "bbox": null, "kind": "callout", "text": "Over 40% of businesses that currently base less than a quarter (1-24%) of their AI solutions on open-source plan to increase this share in 2025 (42%).", "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": "2026-04-25 12:20:07+00", "model": "or:google/gemini-3.1-flash-lite-preview", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "019dd952-5644-756a-a849-566d41f8cc37", "parentComponentId": null }, { "bbox": { "h": 0.6, "w": 0.5, "x": 0.05, "y": 0.28 }, "kind": "chart", "text": "Percentage of AI Solutions Based on Open-Source in 2024 vs. 2025", "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": "Grouped bar chart", "slug": "bar-grouped", "status": "active", "canonId": "019de52c-ff3b-751e-a8ff-f21ff11097b1", "version": 1, "description": null }, "framework": null }, "subkind": "bar-grouped", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 17:31:35.67+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "246e8034-679f-4faf-ab4e-64bb8867be10", "parentComponentId": null }, { "bbox": { "h": 0.05, "w": 0.7, "x": 0.18, "y": 0.093 }, "kind": "disclaimer", "text": "IBM10 What percentage of your company's current AI solutions or platforms are based on open-source? // IBM20 In the next year, what percentage of your AI solutions or platforms will be based on open source? Sample Size: ITDMs = 2,413", "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 17:31:35.67+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "8a896fad-5352-4904-a949-ca7241102c83", "parentComponentId": null }, { "bbox": null, "kind": "metric", "text": "Percentage of AI solutions based on open-source: 41%", "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": "2026-04-25 12:20:07+00", "model": "or:google/gemini-3.1-flash-lite-preview", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "019dd952-5644-756a-a849-5aec1d6bbd70", "parentComponentId": null }, { "bbox": { "h": 0.08, "w": 0.9, "x": 0.05, "y": 0.12 }, "kind": "title", "text": "Investment in open-source solutions for AI continues into 2025; More AI solutions are expected to be based on open-source in the new year (37% 2024 vs. 41% 2025)", "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 17:31:35.67+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "7edb37e1-96d6-4afa-b313-83e9140658e3", "parentComponentId": null }, { "bbox": { "h": 0.03, "w": 0.15, "x": 0.05, "y": 0.07 }, "kind": "title", "text": "FUTURE OF 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 17:31:35.67+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "c043449f-b2d8-44d1-a014-fc89f97feb8d", "parentComponentId": null } ], "metrics": [], "tools": [], "frameworks": [], "arcBeats": [ { "to": 26, "arc": { "name": "The Sparkline", "slug": "sparkline", "status": "active", "bestFor": "Keynotes, TED-style talks", "canonId": "019dd956-606e-720c-905a-42607ac0bf50", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "What Is -> What Could Be -> What Is -> What Could Be -> New Bliss", "description": null, "familyLabel": null }, "from": 23, "name": "Development", "beatId": "22874121-9055-4ce2-b5b1-e6a4c001108a", "matchId": "bf9fcf67-d39d-4c8d-8724-bdd9506a6c64", "beatType": { "name": "Development", "slug": "development", "status": "active", "canonId": "019dd9b8-0332-7008-b3aa-11b0840a57b1", "version": 1, "description": "The middle stretch in arcs that have one. Often where length problems creep in." }, "evidence": "The deck discusses the future of AI investments and plans for 2025.", "position": 3, "isPrimaryArc": true, "parentBeatType": null, "alignedBlockIds": null, "matchConfidence": 0.8 } ], "loops": [ { "to": 26, "from": 23, "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": "d7f608c3-cad7-441c-9fc4-3ef2dbe8a2c7", "evidence": "The deck discusses the future of AI investments and plans for 2025.", "position": 1, "objective": "Why is now the right time to invest in AI?", "confidence": 0.7, "extraction": { "at": "2026-07-16 21:24:12.45473+00", "model": "or:meta-llama/llama-4-scout", "runId": null, "seconds": null, "promptVersion": "doc-narrative-v1" } } ], "locked": true }, { "page": 27, "type": "analysis", "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": "dense", "densityScore": 74, "componentCount": 7, "textChars": 1227, "nDataPoints": 11, "notes": null, "elementsJson": [ "headline_text", "bar_chart_horizontal", "callout_box" ], "confidence": 1, "extraction": { "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "at": "2026-05-02 17:31:38.974+00", "seconds": 6.555, "promptVersion": "v2-canon-conditioned" } }, "links": { "slide": "/slides/019dd923-5e88-73ef-bd5d-e266bb5de1d1/27", "deck": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1", "deckAnchor": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1#slide-27", "deckJson": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1.json" }, "components": [ { "bbox": null, "kind": "callout", "text": "Open-Source Insight: 2 in 5 non-open-source users plan to use open-source for AI implementation in 2025 (41%).", "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": "2026-04-25 12:20:06+00", "model": "or:google/gemini-3.1-flash-lite-preview", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "019dd952-5644-756a-a849-252d374b10a9", "parentComponentId": null }, { "bbox": { "h": 0.6, "w": 0.55, "x": 0.05, "y": 0.295 }, "kind": "chart", "text": "Strategic Changes to Optimize AI Implementation Planned for 2025", "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 17:31:38.974+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "0a23a4a3-050d-4826-8691-bb2f43209df7", "parentComponentId": null }, { "bbox": null, "kind": "metric", "text": "Percentage of ITDMs: 51%", "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": "2026-04-25 12:20:06+00", "model": "or:google/gemini-3.1-flash-lite-preview", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "019dd952-5644-756a-a849-2a194bb87a89", "parentComponentId": null }, { "bbox": { "h": 0.6, "w": 0.28, "x": 0.66, "y": 0.295 }, "kind": "paragraph", "text": "Data Deep Dive: Open-Source Insight: 2 in 5 non-open-source users plan to use open-source for AI implementation in 2025 (41%). Additionally, over half of open-source users (54%) will be using cloud managed services in 2025 to help optimize AI implementation (Non-Open-Source Users = 47%). 71% of ITDMs in India report that their company plans to utilize more open-source in the new year to help optimize their AI implementation. Middle management is more likely to report their company plans to be using cloud managed services (53%) and more open-source (49%) and than their senior-level colleagues (Senior Management = 47% using cloud managed services, 44% using more open-source).", "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 17:31:38.974+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "fc779d18-4bcd-43cc-9c5f-89d2ff692935", "parentComponentId": null }, { "bbox": { "h": 0.03, "w": 0.5, "x": 0.18, "y": 0.94 }, "kind": "source-note", "text": "IBM21 Which of the following strategic changes, if any, is your company planning for 2025 to optimize AI implementations? Please select all that apply. Sample Size: ITDMs = 2,413", "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 17:31:38.974+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "20877ac1-4cd8-445e-991d-9d8183f76023", "parentComponentId": null }, { "bbox": { "h": 0.03, "w": 0.12, "x": 0.05, "y": 0.07 }, "kind": "title", "text": "FUTURE OF 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 17:31:38.974+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "02c0b85e-8564-41b0-99d8-6e7c82769a52", "parentComponentId": null }, { "bbox": { "h": 0.08, "w": 0.9, "x": 0.05, "y": 0.12 }, "kind": "title", "text": "Increasing use of open-source and utilizing cloud managed services are among the most common ways businesses plan to optimize their AI implementation in 2025", "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 17:31:38.974+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "c413f782-10a1-4584-bdcc-30226ed4acc8", "parentComponentId": null } ], "metrics": [], "tools": [ { "tool": { "name": "List presentation", "slug": "list-presentation", "status": "active", "bestFor": null, "canonId": "019dd9e1-4ef7-777d-ba68-9074c2b3bcf1", "version": 1, "bodyDocId": null, "description": "Bulleted, numbered, or checklist enumerations.", "familyLabel": null, "categoryName": null, "categorySlug": null }, "agent": null, "layer": "slide", "agents": null, "matchId": "474da381-ebe6-40b0-8dcc-f91478c7e97f", "evidence": "The slide presents a list of strategic changes to optimize AI implementation.", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 0.6, "extraction": { "at": "2026-07-16 22:02:16.477904+00", "model": "or:meta-llama/llama-4-scout", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 27, "whyItWorks": null, "antipattern": null, "cardinality": "common", "narrativePurpose": null } ], "frameworks": [], "arcBeats": [], "loops": [], "locked": true }, { "page": 28, "type": "appendix", "function": "appendix", "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": "appendix", "functionCanon": { "name": "Appendix", "slug": "appendix", "status": "active", "canonId": "019de52d-138d-750b-83c3-49b4bc7a7a38", "version": 1, "description": null }, "density": "sparse", "densityScore": 0, "componentCount": 1, "textChars": 8, "nDataPoints": 0, "notes": null, "elementsJson": [ "headline_text" ], "confidence": 1, "extraction": { "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "at": "2026-05-02 17:31:34.784+00", "seconds": 2.177, "promptVersion": "v2-canon-conditioned" } }, "links": { "slide": "/slides/019dd923-5e88-73ef-bd5d-e266bb5de1d1/28", "deck": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1", "deckAnchor": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1#slide-28", "deckJson": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1.json" }, "components": [ { "bbox": { "h": 0.085, "w": 0.205, "x": 0.036, "y": 0.425 }, "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 17:31:34.784+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "0da9c690-d99a-4d65-a0f9-140cc5abb350", "parentComponentId": null } ], "metrics": [], "tools": [], "frameworks": [], "arcBeats": [], "loops": [], "locked": true }, { "page": 29, "type": "analysis", "title": "The slide displays three grouped bar charts representing different time periods for AI pilot launches.", "function": "analyze_data", "rawType": "appendix_data", "block": null, "metadata": { "slideType": "appendix_data", "slideTypeCanon": { "name": "Appendix data", "slug": "appendix_data", "status": "active", "canonId": "019de52d-078a-745b-9ee4-c15f2f539acd", "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": "balanced", "densityScore": 46, "componentCount": 5, "textChars": 516, "nDataPoints": 33, "notes": "The slide displays three grouped bar charts representing different time periods for AI pilot launches.", "elementsJson": [ "bar_chart_vertical", "data_table" ], "confidence": 1, "extraction": { "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "at": "2026-05-02 17:31:35.318+00", "seconds": 2.402, "promptVersion": "v2-canon-conditioned" } }, "links": { "slide": "/slides/019dd923-5e88-73ef-bd5d-e266bb5de1d1/29", "deck": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1", "deckAnchor": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1#slide-29", "deckJson": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1.json" }, "components": [ { "bbox": null, "kind": "callout", "text": "On average, ITDMs expect over 60% of their 2025 AI pilots to be fully launched by the end of the year.", "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": "2026-04-25 12:20:06+00", "model": "or:google/gemini-3.1-flash-lite-preview", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "019dd952-5644-756a-a848-f7e15073cab8", "parentComponentId": null }, { "bbox": { "h": 0.55, "w": 0.88, "x": 0.06, "y": 0.345 }, "kind": "chart", "text": "Projected 2025 AI Pilot Launch Timeline: H1, H2, & Beyond 2025", "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": "Vertical bar chart", "slug": "bar-vertical", "status": "active", "canonId": "019de52c-fe9d-70f2-b3b7-a9ae294f5917", "version": 1, "description": null }, "framework": null }, "subkind": "bar-vertical", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 17:31:35.318+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "bc28b551-837b-4640-b752-c5a220b7ebee", "parentComponentId": null }, { "bbox": null, "kind": "metric", "text": "Percentage of pilots fully launched: 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": "2026-04-25 12:20:06+00", "model": "or:google/gemini-3.1-flash-lite-preview", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "019dd952-5644-756a-a848-fac850599a3a", "parentComponentId": null }, { "bbox": { "h": 0.03, "w": 0.5, "x": 0.18, "y": 0.93 }, "kind": "source-note", "text": "IBM9 And what percentage of these AI pilots planned for 2025 do you think will be fully launched in the following time periods? Numeric Open End Sample Size: ITDMs at Companies Planning AI Pilots in 2025 = 2,396", "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 17:31:35.318+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "0e294062-3248-4ea7-a439-b88ad093e385", "parentComponentId": null }, { "bbox": { "h": 0.05, "w": 0.9, "x": 0.05, "y": 0.12 }, "kind": "title", "text": "On average, ITDMs expect over 60% of their 2025 AI pilots to be fully launched by the end of the year", "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 17:31:35.318+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "4b04b252-89bd-4400-8e8d-c33074ca37c9", "parentComponentId": null } ], "metrics": [], "tools": [ { "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": "2d3d8cdf-31f5-431b-9940-80ef520818c3", "evidence": "The slide uses a bar chart to show the projected AI pilot launch timeline.", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 0.7, "extraction": { "at": "2026-07-16 22:02:16.597912+00", "model": "or:meta-llama/llama-4-scout", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 29, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null } ], "frameworks": [], "arcBeats": [ { "to": 77, "arc": { "name": "The Sparkline", "slug": "sparkline", "status": "active", "bestFor": "Keynotes, TED-style talks", "canonId": "019dd956-606e-720c-905a-42607ac0bf50", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "What Is -> What Could Be -> What Is -> What Could Be -> New Bliss", "description": null, "familyLabel": null }, "from": 29, "name": "Evidence", "beatId": "5bb325e2-e460-48c2-ba3f-ded31b7b7818", "matchId": "bf9fcf67-d39d-4c8d-8724-bdd9506a6c64", "beatType": { "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." }, "evidence": "The deck provides extensive data and evidence to support its findings and recommendations.", "position": 4, "isPrimaryArc": true, "parentBeatType": null, "alignedBlockIds": null, "matchConfidence": 0.8 } ], "loops": [], "locked": true }, { "page": 30, "type": "analysis", "title": "Source: Morning Consult, Sample Size: ITDMs = 2,413", "function": "analyze_data", "rawType": "appendix_data", "block": null, "metadata": { "slideType": "appendix_data", "slideTypeCanon": { "name": "Appendix data", "slug": "appendix_data", "status": "active", "canonId": "019de52d-078a-745b-9ee4-c15f2f539acd", "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": "balanced", "densityScore": 36, "componentCount": 5, "textChars": 336, "nDataPoints": 9, "notes": "Source: Morning Consult, Sample Size: ITDMs = 2,413", "elementsJson": [ "bar_chart_horizontal", "footnote" ], "confidence": 1, "extraction": { "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "at": "2026-05-02 17:31:35.653+00", "seconds": 2.369, "promptVersion": "v2-canon-conditioned" } }, "links": { "slide": "/slides/019dd923-5e88-73ef-bd5d-e266bb5de1d1/30", "deck": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1", "deckAnchor": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1#slide-30", "deckJson": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1.json" }, "components": [ { "bbox": { "h": 0.55, "w": 0.45, "x": 0.22, "y": 0.295 }, "kind": "chart", "text": "Top Areas Likely to See AI Investments Reduced in 2025", "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 17:31:35.653+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "12a12e19-d33f-43fc-942e-cce8fe96c8c6", "parentComponentId": null }, { "bbox": null, "kind": "metric", "text": "Percentage of ITDMs: 34%", "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": "2026-04-25 12:20:09+00", "model": "or:google/gemini-3.1-flash-lite-preview", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "019dd952-5644-756a-a849-a67e280f097f", "parentComponentId": null }, { "bbox": { "h": 0.03, "w": 0.5, "x": 0.18, "y": 0.94 }, "kind": "source-note", "text": "IBM19 In which areas is your company most likely to consider reducing its AI investments in 2025? Please select up to three options. Sample Size: ITDMs = 2,413", "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 17:31:35.653+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "0b1e3856-2916-4aff-a1ef-9d1afd895293", "parentComponentId": null }, { "bbox": { "h": 0.05, "w": 0.8, "x": 0.05, "y": 0.11 }, "kind": "title", "text": "ITDMs are split on the areas their companies are likely to consider reducing 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 17:31:35.653+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "768e9d43-8f5c-4d58-aba2-117d42e19d2d", "parentComponentId": null }, { "bbox": { "h": 0.02, "w": 0.1, "x": 0.05, "y": 0.07 }, "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": "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 17:31:35.653+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "2af97162-e3b3-4c88-9789-f4590ecdcb96", "parentComponentId": null } ], "metrics": [], "tools": [ { "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": "6133c87f-63af-4fad-983f-2d2d461c62d1", "evidence": "The slide uses a bar chart to show areas likely to see AI investments reduced.", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 0.7, "extraction": { "at": "2026-07-16 22:02:16.676766+00", "model": "or:meta-llama/llama-4-scout", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 30, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null } ], "frameworks": [], "arcBeats": [ { "to": 77, "arc": { "name": "The Sparkline", "slug": "sparkline", "status": "active", "bestFor": "Keynotes, TED-style talks", "canonId": "019dd956-606e-720c-905a-42607ac0bf50", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "What Is -> What Could Be -> What Is -> What Could Be -> New Bliss", "description": null, "familyLabel": null }, "from": 29, "name": "Evidence", "beatId": "5bb325e2-e460-48c2-ba3f-ded31b7b7818", "matchId": "bf9fcf67-d39d-4c8d-8724-bdd9506a6c64", "beatType": { "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." }, "evidence": "The deck provides extensive data and evidence to support its findings and recommendations.", "position": 4, "isPrimaryArc": true, "parentBeatType": null, "alignedBlockIds": null, "matchConfidence": 0.8 } ], "loops": [], "locked": true }, { "page": 31, "type": "analysis", "title": "Source: Morning Consult. Sample size: 2,413 ITDMs.", "function": "analyze_data", "rawType": "appendix_data", "block": null, "metadata": { "slideType": "appendix_data", "slideTypeCanon": { "name": "Appendix data", "slug": "appendix_data", "status": "active", "canonId": "019de52d-078a-745b-9ee4-c15f2f539acd", "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": "balanced", "densityScore": 32, "componentCount": 4, "textChars": 423, "nDataPoints": 5, "notes": "Source: Morning Consult. Sample size: 2,413 ITDMs.", "elementsJson": [ "bar_chart_horizontal" ], "confidence": 1, "extraction": { "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "at": "2026-05-02 17:31:36.891+00", "seconds": 3.277, "promptVersion": "v2-canon-conditioned" } }, "links": { "slide": "/slides/019dd923-5e88-73ef-bd5d-e266bb5de1d1/31", "deck": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1", "deckAnchor": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1#slide-31", "deckJson": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1.json" }, "components": [ { "bbox": { "h": 0.5, "w": 0.7, "x": 0.15, "y": 0.3 }, "kind": "chart", "text": "Metrics Used to Measure ROI from AI Investments", "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 17:31:36.891+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "01ade10f-7dbb-4d85-9cbf-3a49b5daef55", "parentComponentId": null }, { "bbox": null, "kind": "metric", "text": "ROI measurement metrics: 62%", "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": "2026-04-25 12:20:06+00", "model": "or:google/gemini-3.1-flash-lite-preview", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "019dd952-5644-756a-a848-d9bc0b887728", "parentComponentId": null }, { "bbox": { "h": 0.05, "w": 0.45, "x": 0.18, "y": 0.93 }, "kind": "source-note", "text": "IBM12 How does your company calculate return on investment (ROI) from AI investments? Please select all that apply. Sample Size: ITDMs = 2,413", "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 17:31:36.891+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "71f27d83-5aed-4507-a956-acd8c41c4e18", "parentComponentId": null }, { "bbox": { "h": 0.15, "w": 0.9, "x": 0.05, "y": 0.12 }, "kind": "title", "text": "Organizations are most likely to be using faster software development, productivity time savings, and more rapid innovation to measure ROI of AI, while calculating quantifiable savings is a lot less popular", "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 17:31:36.891+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "a7d35d9a-d916-4e1c-b2b5-e9b87c9b99b6", "parentComponentId": null } ], "metrics": [], "tools": [ { "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": "5f8b8b03-82ff-4dc7-bac2-f59a83e6c643", "evidence": "The slide uses a bar chart to show metrics used to measure ROI from AI investments.", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 0.7, "extraction": { "at": "2026-07-16 22:02:16.754989+00", "model": "or:meta-llama/llama-4-scout", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 31, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null } ], "frameworks": [], "arcBeats": [ { "to": 77, "arc": { "name": "The Sparkline", "slug": "sparkline", "status": "active", "bestFor": "Keynotes, TED-style talks", "canonId": "019dd956-606e-720c-905a-42607ac0bf50", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "What Is -> What Could Be -> What Is -> What Could Be -> New Bliss", "description": null, "familyLabel": null }, "from": 29, "name": "Evidence", "beatId": "5bb325e2-e460-48c2-ba3f-ded31b7b7818", "matchId": "bf9fcf67-d39d-4c8d-8724-bdd9506a6c64", "beatType": { "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." }, "evidence": "The deck provides extensive data and evidence to support its findings and recommendations.", "position": 4, "isPrimaryArc": true, "parentBeatType": null, "alignedBlockIds": null, "matchConfidence": 0.8 } ], "loops": [], "locked": true }, { "page": 32, "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": 2, "componentCount": 1, "textChars": 52, "nDataPoints": 0, "notes": null, "elementsJson": [ "headline_text" ], "confidence": 1, "extraction": { "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "at": "2026-05-02 17:31:35.769+00", "seconds": 1.735, "promptVersion": "v2-canon-conditioned" } }, "links": { "slide": "/slides/019dd923-5e88-73ef-bd5d-e266bb5de1d1/32", "deck": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1", "deckAnchor": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1#slide-32", "deckJson": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1.json" }, "components": [ { "bbox": { "h": 0.15, "w": 0.6, "x": 0.07, "y": 0.42 }, "kind": "title", "text": "Appendix: Advanced vs. Emerging AI Ecosystem Markets", "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 17:31:35.769+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "e4d3b75a-a6a8-4a37-a47c-7e1e05f6ed82", "parentComponentId": null } ], "metrics": [], "tools": [], "frameworks": [], "arcBeats": [ { "to": 77, "arc": { "name": "The Sparkline", "slug": "sparkline", "status": "active", "bestFor": "Keynotes, TED-style talks", "canonId": "019dd956-606e-720c-905a-42607ac0bf50", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "What Is -> What Could Be -> What Is -> What Could Be -> New Bliss", "description": null, "familyLabel": null }, "from": 29, "name": "Evidence", "beatId": "5bb325e2-e460-48c2-ba3f-ded31b7b7818", "matchId": "bf9fcf67-d39d-4c8d-8724-bdd9506a6c64", "beatType": { "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." }, "evidence": "The deck provides extensive data and evidence to support its findings and recommendations.", "position": 4, "isPrimaryArc": true, "parentBeatType": null, "alignedBlockIds": null, "matchConfidence": 0.8 } ], "loops": [], "locked": true }, { "page": 33, "type": "appendix", "title": "Methodology slide explaining respondent segmentation.", "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": 54, "componentCount": 5, "textChars": 990, "nDataPoints": 4, "notes": "Methodology slide explaining respondent segmentation.", "elementsJson": [ "paragraph", "bullet_list" ], "confidence": 1, "extraction": { "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "at": "2026-05-02 17:31:40.605+00", "seconds": 6.566, "promptVersion": "v2-canon-conditioned" } }, "links": { "slide": "/slides/019dd923-5e88-73ef-bd5d-e266bb5de1d1/33", "deck": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1", "deckAnchor": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1#slide-33", "deckJson": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1.json" }, "components": [ { "bbox": { "h": 0.167, "w": 0.886, "x": 0.057, "y": 0.275 }, "kind": "list", "text": "Group 1: Advanced AI Ecosystems: Respondents from the US, Canada, the UK, France, Germany, Singapore, and South Korea displayed similar response patterns across multiple key questions. These markets have higher adjusted per capita income and are likely to have been working with AI for a longer time, and, therefore, are categorized as 'advanced'. The sample size of this group is 1,407 and the results have a margin of error of +/- 3 percentage points.", "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 17:31:40.605+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "35523e12-6832-4da8-9fd3-57ace94fdc3a", "parentComponentId": null }, { "bbox": { "h": 0.125, "w": 0.886, "x": 0.057, "y": 0.467 }, "kind": "list", "text": "Group 2: Emerging AI Ecosystems: Respondents from Mexico, Spain, Brazil, India, and Indonesia also had distinct response patterns. These markets are likely to be newer to AI exploration and tend to be making rapid progress in AI development. The sample size of this group is 1,006 and the results have a margin of error of +/- 3 percentage points.", "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 17:31:40.605+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "d4a4a9ca-047f-4cd9-b23b-efa47f6be024", "parentComponentId": null }, { "bbox": { "h": 0.042, "w": 0.886, "x": 0.057, "y": 0.208 }, "kind": "paragraph", "text": "When analyzing the data, Morning Consult identified patterns in the responses from respondents of two sets of markets:", "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 17:31:40.605+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "bccf10a0-d502-447b-b736-53ba9754baef", "parentComponentId": null }, { "bbox": { "h": 0.022, "w": 0.435, "x": 0.057, "y": 0.078 }, "kind": "title", "text": "APPENDIX: ADVANCED VS. EMERGING AI ECOSYSTEM MARKETS", "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 17:31:40.605+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "25e04908-5673-4cff-8d9f-f3c599d0900e", "parentComponentId": null }, { "bbox": { "h": 0.038, "w": 0.235, "x": 0.057, "y": 0.125 }, "kind": "title", "text": "Audience Description", "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 17:31:40.605+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "7ba8cb31-802c-4696-871a-9a3fdd4ceb23", "parentComponentId": null } ], "metrics": [], "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? 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": "c8304500-b1a7-471d-adc7-140b5dc5caa3", "evidence": "Group 1: Advanced AI Ecosystems: Respondents from the US, Canada, the UK, France, Germany, Singapore, and South Korea displayed similar response patterns across multiple key questions.", "pageRefs": null, "priority": "Core", "whenToUse": null, "confidence": 0.7, "extraction": { "at": "2026-07-16 22:02:09.418528+00", "model": "or:meta-llama/llama-4-scout", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 33, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "Audience Segmentation", "slug": "audience-segmentation", "status": "active", "bestFor": null, "canonId": "019dd956-8079-7046-8e6b-ecdf1bf15590", "version": 1, "bodyDocId": null, "description": "Grouping audience by attitude toward your message: Champions, Neutrals, Skeptics", "familyLabel": null, "categoryName": "Block", "categorySlug": "block" }, "agent": "Storyteller", "layer": "slide", "agents": [ "Storyteller" ], "matchId": "8f18e8ab-a4ae-45ae-86ca-9052e33ac41f", "evidence": "Group 1: Advanced AI Ecosystems: Respondents from the US, Canada, the UK, France, Germany, Singapore, and South Korea displayed similar response patterns across multiple key questions. Group 2: Emerging AI Ecosystems: Respondents from Mexico, Spain, Brazil, India, and Indonesia also had distinct response patterns.", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 0.7, "extraction": { "at": "2026-07-16 22:02:09.452709+00", "model": "or:meta-llama/llama-4-scout", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 33, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null } ], "frameworks": [ { "matchId": "50397989-f813-4278-87f9-fd7e4b88ecc5", "evidence": "The slide explicitly defines two distinct groups of markets based on response patterns and economic characteristics.", "framework": null, "confidence": 1, "extraction": { "at": "2026-05-02 17:31:40.605+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 33, "frameworkName": "audience-segmentation" } ], "arcBeats": [ { "to": 77, "arc": { "name": "The Sparkline", "slug": "sparkline", "status": "active", "bestFor": "Keynotes, TED-style talks", "canonId": "019dd956-606e-720c-905a-42607ac0bf50", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "What Is -> What Could Be -> What Is -> What Could Be -> New Bliss", "description": null, "familyLabel": null }, "from": 29, "name": "Evidence", "beatId": "5bb325e2-e460-48c2-ba3f-ded31b7b7818", "matchId": "bf9fcf67-d39d-4c8d-8724-bdd9506a6c64", "beatType": { "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." }, "evidence": "The deck provides extensive data and evidence to support its findings and recommendations.", "position": 4, "isPrimaryArc": true, "parentBeatType": null, "alignedBlockIds": null, "matchConfidence": 0.8 } ], "loops": [], "locked": true }, { "page": 34, "type": "analysis", "title": "Data source: Morning Consult. Sample sizes: Advanced (1,407), Emerging (1,006).", "function": "analyze_data", "rawType": "appendix_data", "block": null, "metadata": { "slideType": "appendix_data", "slideTypeCanon": { "name": "Appendix data", "slug": "appendix_data", "status": "active", "canonId": "019de52d-078a-745b-9ee4-c15f2f539acd", "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": "dense", "densityScore": 53, "componentCount": 6, "textChars": 541, "nDataPoints": 10, "notes": "Data source: Morning Consult. Sample sizes: Advanced (1,407), Emerging (1,006).", "elementsJson": [ "bar_chart_grouped" ], "confidence": 1, "extraction": { "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "at": "2026-05-02 17:31:36.695+00", "seconds": 2.656, "promptVersion": "v2-canon-conditioned" } }, "links": { "slide": "/slides/019dd923-5e88-73ef-bd5d-e266bb5de1d1/34", "deck": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1", "deckAnchor": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1#slide-34", "deckJson": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1.json" }, "components": [ { "bbox": { "h": 0.5, "w": 0.6, "x": 0.08, "y": 0.35 }, "kind": "chart", "text": "Grouped bar chart showing AI strategy progress levels", "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": "Grouped bar chart", "slug": "bar-grouped", "status": "active", "canonId": "019de52c-ff3b-751e-a8ff-f21ff11097b1", "version": 1, "description": null }, "framework": null }, "subkind": "bar-grouped", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 17:31:36.695+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "a79522c4-7d1d-4ff7-aa7a-7bb50d2b704e", "parentComponentId": null }, { "bbox": { "h": 0.05, "w": 0.7, "x": 0.18, "y": 0.93 }, "kind": "disclaimer", "text": "IBM1 Which of the following statements best describes your organization's AI strategy today?\nSample Size: Advanced AI Ecosystem (US, Canada, UK, France, Germany, Singapore, South Korea) = 1,407, Emerging AI Ecosystems(Mexico, Spain, Brazil, India, Indonesia) = 1,006", "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 17:31:36.695+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "40afcb55-4b70-4dfe-9083-b6b777ed6c36", "parentComponentId": null }, { "bbox": { "h": 0.05, "w": 0.15, "x": 0.78, "y": 0.595 }, "kind": "legend", "text": "Advanced AI Ecosystems\nEmerging AI Ecosystems", "attrs": null, "canon": { "kind": { "name": "Legend", "slug": "legend", "status": "active", "canonId": "31361933-3d22-4c70-bbad-0801e9fffc0c", "version": 1, "description": "Color/symbol decoder placed adjacent to a chart or diagram." }, "tool": null, "subkind": null, "framework": null }, "subkind": null, "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 17:31:36.695+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "1b5f321d-4753-43a1-bfe8-ec0b92fb2286", "parentComponentId": null }, { "bbox": null, "kind": "metric", "text": "Percentage of ITDMs: 54%", "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": "2026-04-25 12:20:08+00", "model": "or:google/gemini-3.1-flash-lite-preview", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "019dd952-5644-756a-a849-939227b0f00a", "parentComponentId": null }, { "bbox": { "h": 0.03, "w": 0.5, "x": 0.05, "y": 0.07 }, "kind": "title", "text": "APPENDIX: ADVANCED VS. EMERGING AI ECOSYSTEM MARKETS", "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 17:31:36.695+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "d19cdda1-0e3b-4fd7-832a-e79fd2b72323", "parentComponentId": null }, { "bbox": { "h": 0.05, "w": 0.4, "x": 0.3, "y": 0.28 }, "kind": "title", "text": "Progress of AI Strategy\nAmong ITDMs in Advanced vs. Emerging AI Ecosystem Markets, Showing % Selected", "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 17:31:36.695+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "45955ee8-8e25-44dd-aa16-141ef3070366", "parentComponentId": null } ], "metrics": [], "tools": [ { "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": "f61f84e6-8128-4745-905c-8bf234ece954", "evidence": "chart/bar-grouped: Grouped bar chart showing AI strategy progress levels", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 0.5, "extraction": { "at": "2026-07-16 22:02:09.520581+00", "model": "or:meta-llama/llama-4-scout", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 34, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null } ], "frameworks": [], "arcBeats": [ { "to": 77, "arc": { "name": "The Sparkline", "slug": "sparkline", "status": "active", "bestFor": "Keynotes, TED-style talks", "canonId": "019dd956-606e-720c-905a-42607ac0bf50", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "What Is -> What Could Be -> What Is -> What Could Be -> New Bliss", "description": null, "familyLabel": null }, "from": 29, "name": "Evidence", "beatId": "5bb325e2-e460-48c2-ba3f-ded31b7b7818", "matchId": "bf9fcf67-d39d-4c8d-8724-bdd9506a6c64", "beatType": { "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." }, "evidence": "The deck provides extensive data and evidence to support its findings and recommendations.", "position": 4, "isPrimaryArc": true, "parentBeatType": null, "alignedBlockIds": null, "matchConfidence": 0.8 } ], "loops": [], "locked": true }, { "page": 35, "type": "analysis", "title": "Data source: Morning Consult. Sample sizes provided in footer.", "function": "analyze_data", "rawType": "appendix_data", "block": null, "metadata": { "slideType": "appendix_data", "slideTypeCanon": { "name": "Appendix data", "slug": "appendix_data", "status": "active", "canonId": "019de52d-078a-745b-9ee4-c15f2f539acd", "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": "dense", "densityScore": 55, "componentCount": 6, "textChars": 621, "nDataPoints": 10, "notes": "Data source: Morning Consult. Sample sizes provided in footer.", "elementsJson": [ "bar_chart_grouped" ], "confidence": 1, "extraction": { "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "at": "2026-05-02 17:31:36.569+00", "seconds": 2.475, "promptVersion": "v2-canon-conditioned" } }, "links": { "slide": "/slides/019dd923-5e88-73ef-bd5d-e266bb5de1d1/35", "deck": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1", "deckAnchor": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1#slide-35", "deckJson": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1.json" }, "components": [ { "bbox": { "h": 0.5, "w": 0.4, "x": 0.3, "y": 0.37 }, "kind": "chart", "text": "Grouped bar chart showing distribution of AI pilots (None, 1-10, 11-20, 21-30, More than 30) for Advanced vs Emerging markets.", "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": "Grouped bar chart", "slug": "bar-grouped", "status": "active", "canonId": "019de52c-ff3b-751e-a8ff-f21ff11097b1", "version": 1, "description": null }, "framework": null }, "subkind": "bar-grouped", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 17:31:36.569+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "95a50a9f-cbc1-4a4b-a14b-e8574d8ed6ff", "parentComponentId": null }, { "bbox": { "h": 0.04, "w": 0.7, "x": 0.18, "y": 0.94 }, "kind": "disclaimer", "text": "IBM2 By the end of the year, how many AI pilots will your company have started in 2024? Sample Size: Advanced AI Ecosystem (US, Canada, UK, France, Germany, Singapore, South Korea) = 1,407, Emerging AI Ecosystems(Mexico, Spain, Brazil, India, Indonesia) = 1,006", "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 17:31:36.569+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "d05e3234-3dff-4803-b33a-b6b2131619ef", "parentComponentId": null }, { "bbox": { "h": 0.05, "w": 0.15, "x": 0.78, "y": 0.6 }, "kind": "legend", "text": "Advanced AI Ecosystems\nEmerging AI Ecosystems", "attrs": null, "canon": { "kind": { "name": "Legend", "slug": "legend", "status": "active", "canonId": "31361933-3d22-4c70-bbad-0801e9fffc0c", "version": 1, "description": "Color/symbol decoder placed adjacent to a chart or diagram." }, "tool": null, "subkind": null, "framework": null }, "subkind": null, "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 17:31:36.569+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "9743cc4a-ad14-424a-9a71-95c319f580f5", "parentComponentId": null }, { "bbox": null, "kind": "metric", "text": "Number of AI Pilots: 55%", "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": "2026-04-25 12:20:07+00", "model": "or:google/gemini-3.1-flash-lite-preview", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "019dd952-5644-756a-a849-696666b4bcfb", "parentComponentId": null }, { "bbox": { "h": 0.03, "w": 0.5, "x": 0.05, "y": 0.08 }, "kind": "title", "text": "APPENDIX: ADVANCED VS. EMERGING AI ECOSYSTEM MARKETS", "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 17:31:36.569+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "37d40ac3-3428-4d6c-8f8f-7b8fedddd251", "parentComponentId": null }, { "bbox": { "h": 0.05, "w": 0.4, "x": 0.3, "y": 0.29 }, "kind": "title", "text": "Number of AI Pilots Started in 2024\nAmong ITDMs in Advanced vs. Emerging AI Ecosystem Markets, Showing % Selected", "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 17:31:36.569+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "1fa207a7-2183-458b-9ca4-c3f2e781d346", "parentComponentId": null } ], "metrics": [], "tools": [ { "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": "2bc78946-dad3-43be-b1d5-c88df9c9d185", "evidence": "chart/bar-grouped: Grouped bar chart showing distribution of AI pilots (None, 1-10, 11-20, 21-30, More than 30) for Advanced vs Emerging markets.", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 0.5, "extraction": { "at": "2026-07-16 22:02:09.58867+00", "model": "or:meta-llama/llama-4-scout", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 35, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null } ], "frameworks": [], "arcBeats": [ { "to": 77, "arc": { "name": "The Sparkline", "slug": "sparkline", "status": "active", "bestFor": "Keynotes, TED-style talks", "canonId": "019dd956-606e-720c-905a-42607ac0bf50", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "What Is -> What Could Be -> What Is -> What Could Be -> New Bliss", "description": null, "familyLabel": null }, "from": 29, "name": "Evidence", "beatId": "5bb325e2-e460-48c2-ba3f-ded31b7b7818", "matchId": "bf9fcf67-d39d-4c8d-8724-bdd9506a6c64", "beatType": { "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." }, "evidence": "The deck provides extensive data and evidence to support its findings and recommendations.", "position": 4, "isPrimaryArc": true, "parentBeatType": null, "alignedBlockIds": null, "matchConfidence": 0.8 } ], "loops": [], "locked": true }, { "page": 36, "type": "analysis", "title": "Data source: Morning Consult. Sample sizes: Advanced (1,396), Emerging (997).", "function": "analyze_data", "rawType": "appendix_data", "block": null, "metadata": { "slideType": "appendix_data", "slideTypeCanon": { "name": "Appendix data", "slug": "appendix_data", "status": "active", "canonId": "019de52d-078a-745b-9ee4-c15f2f539acd", "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": "dense", "densityScore": 64, "componentCount": 7, "textChars": 593, "nDataPoints": 22, "notes": "Data source: Morning Consult. Sample sizes: Advanced (1,396), Emerging (997).", "elementsJson": [ "bar_chart_grouped" ], "confidence": 1, "extraction": { "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "at": "2026-05-02 17:31:37.503+00", "seconds": 3.23, "promptVersion": "v2-canon-conditioned" } }, "links": { "slide": "/slides/019dd923-5e88-73ef-bd5d-e266bb5de1d1/36", "deck": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1", "deckAnchor": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1#slide-36", "deckJson": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1.json" }, "components": [ { "bbox": { "h": 0.45, "w": 0.84, "x": 0.08, "y": 0.4 }, "kind": "chart", "text": null, "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": "Grouped bar chart", "slug": "bar-grouped", "status": "active", "canonId": "019de52c-ff3b-751e-a8ff-f21ff11097b1", "version": 1, "description": null }, "framework": null }, "subkind": "bar-grouped", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 17:31:37.503+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "4e315f2a-1fbf-4127-a6cf-3f4c2f356cbb", "parentComponentId": null }, { "bbox": { "h": 0.02, "w": 0.3, "x": 0.35, "y": 0.36 }, "kind": "legend", "text": "Advanced AI Ecosystems | Emerging AI Ecosystems", "attrs": null, "canon": { "kind": { "name": "Legend", "slug": "legend", "status": "active", "canonId": "31361933-3d22-4c70-bbad-0801e9fffc0c", "version": 1, "description": "Color/symbol decoder placed adjacent to a chart or diagram." }, "tool": null, "subkind": null, "framework": null }, "subkind": null, "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 17:31:37.503+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "ddaab22a-9936-4995-870c-57129ccfbdc9", "parentComponentId": null }, { "bbox": null, "kind": "metric", "text": "Percentage of 2024 AI Pilots Fully Launched", "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": "2026-04-25 12:20:07+00", "model": "or:google/gemini-3.1-flash-lite-preview", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "019dd952-5644-756a-a849-803bcc1ff0b3", "parentComponentId": null }, { "bbox": { "h": 0.04, "w": 0.9, "x": 0.05, "y": 0.94 }, "kind": "source-note", "text": "IBM3 What percentage of the AI pilots started in 2024 will have fully launched by the end of the year? Sample Size: Advanced AI Ecosystem (US, Canada, UK, France, Germany, Singapore, South Korea) = 1,396, Emerging AI Ecosystems(Mexico, Spain, Brazil, India, Indonesia) = 997", "attrs": { "numbered": true }, "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 17:31:37.503+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "827901cd-a483-4cdb-bbbe-03fdbcfcdb43", "parentComponentId": null }, { "bbox": { "h": 0.03, "w": 0.6, "x": 0.2, "y": 0.32 }, "kind": "subtitle", "text": "Among ITDMs at Companies that have started AI Pilots in 2024 in Advanced vs. Emerging AI Ecosystem Markets, Showing % Selected", "attrs": null, "canon": { "kind": { "name": "Subtitle", "slug": "subtitle", "status": "active", "canonId": "82d821ee-2793-42e7-8f16-c6131385a3ce", "version": 1, "description": "Header-zone supporting text near the title (= ex body.description with bbox)." }, "tool": null, "subkind": null, "framework": null }, "subkind": null, "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 17:31:37.503+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "237d21cd-846b-4fd8-9bce-debfcef21d72", "parentComponentId": null }, { "bbox": { "h": 0.03, "w": 0.5, "x": 0.05, "y": 0.07 }, "kind": "title", "text": "APPENDIX: ADVANCED VS. EMERGING AI ECOSYSTEM MARKETS", "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 17:31:37.503+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "30586c9f-f328-4a00-ab55-62cd15f54c0d", "parentComponentId": null }, { "bbox": { "h": 0.03, "w": 0.4, "x": 0.3, "y": 0.29 }, "kind": "title", "text": "Percentage of 2024 AI Pilots Fully Launched in 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": "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 17:31:37.503+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "f54cbccc-0450-473d-a532-88232c3b9bce", "parentComponentId": null } ], "metrics": [], "tools": [ { "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": "5831e3dd-f241-4d66-b006-832938fa2a63", "evidence": "chart/bar-grouped: Grouped bar chart showing distribution of open-source usage percentages (0%, 1-24%, 25-49%, 50-74%, 75-100%) for Advanced vs Emerging markets.", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 0.5, "extraction": { "at": "2026-07-16 22:02:09.658035+00", "model": "or:meta-llama/llama-4-scout", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 36, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null } ], "frameworks": [], "arcBeats": [ { "to": 77, "arc": { "name": "The Sparkline", "slug": "sparkline", "status": "active", "bestFor": "Keynotes, TED-style talks", "canonId": "019dd956-606e-720c-905a-42607ac0bf50", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "What Is -> What Could Be -> What Is -> What Could Be -> New Bliss", "description": null, "familyLabel": null }, "from": 29, "name": "Evidence", "beatId": "5bb325e2-e460-48c2-ba3f-ded31b7b7818", "matchId": "bf9fcf67-d39d-4c8d-8724-bdd9506a6c64", "beatType": { "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." }, "evidence": "The deck provides extensive data and evidence to support its findings and recommendations.", "position": 4, "isPrimaryArc": true, "parentBeatType": null, "alignedBlockIds": null, "matchConfidence": 0.8 } ], "loops": [], "locked": true }, { "page": 37, "type": "analysis", "title": "The chart shows that transition times are relatively similar across both market types, with the majority of organizations taking between 6 months and 2 years.", "function": "analyze_data", "rawType": "appendix_data", "block": null, "metadata": { "slideType": "appendix_data", "slideTypeCanon": { "name": "Appendix data", "slug": "appendix_data", "status": "active", "canonId": "019de52d-078a-745b-9ee4-c15f2f539acd", "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": "dense", "densityScore": 53, "componentCount": 6, "textChars": 555, "nDataPoints": 10, "notes": "The chart shows that transition times are relatively similar across both market types, with the majority of organizations taking between 6 months and 2 years.", "elementsJson": [ "bar_chart_grouped" ], "confidence": 1, "extraction": { "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "at": "2026-05-02 17:31:42.491+00", "seconds": 8.005, "promptVersion": "v2-canon-conditioned" } }, "links": { "slide": "/slides/019dd923-5e88-73ef-bd5d-e266bb5de1d1/37", "deck": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1", "deckAnchor": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1#slide-37", "deckJson": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1.json" }, "components": [ { "bbox": { "h": 0.5, "w": 0.35, "x": 0.25, "y": 0.35 }, "kind": "chart", "text": null, "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": "Grouped bar chart", "slug": "bar-grouped", "status": "active", "canonId": "019de52c-ff3b-751e-a8ff-f21ff11097b1", "version": 1, "description": null }, "framework": null }, "subkind": "bar-grouped", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 17:31:42.491+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "517a24d3-30c3-47fb-836a-25dca5a537d2", "parentComponentId": null }, { "bbox": { "h": 0.05, "w": 0.7, "x": 0.18, "y": 0.93 }, "kind": "disclaimer", "text": "IBM4 On average, how long does it take your organization to transition from launching an AI pilot to full production?\nSample Size: Advanced AI Ecosystem (US, Canada, UK, France, Germany, Singapore, South Korea) = 1,407, Emerging AI Ecosystems(Mexico, Spain, Brazil, India, Indonesia) = 1,006", "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 17:31:42.491+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "2526a1ae-1ad9-45a7-a4f2-af4f0dcbe356", "parentComponentId": null }, { "bbox": { "h": 0.05, "w": 0.15, "x": 0.79, "y": 0.595 }, "kind": "legend", "text": "Advanced AI Ecosystems\nEmerging AI Ecosystems", "attrs": null, "canon": { "kind": { "name": "Legend", "slug": "legend", "status": "active", "canonId": "31361933-3d22-4c70-bbad-0801e9fffc0c", "version": 1, "description": "Color/symbol decoder placed adjacent to a chart or diagram." }, "tool": null, "subkind": null, "framework": null }, "subkind": null, "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 17:31:42.491+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "11b5584b-0288-4032-bdcb-eb44fed65634", "parentComponentId": null }, { "bbox": null, "kind": "metric", "text": "Time to transition: 51%", "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": "2026-04-25 12:20:11+00", "model": "or:google/gemini-3.1-flash-lite-preview", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "019dd952-5644-756a-a849-e80f5c63ffc6", "parentComponentId": null }, { "bbox": { "h": 0.03, "w": 0.5, "x": 0.05, "y": 0.07 }, "kind": "title", "text": "APPENDIX: ADVANCED VS. EMERGING AI ECOSYSTEM MARKETS", "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 17:31:42.491+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "a21b82e4-b4d3-4ab6-9e7b-832383b8ae94", "parentComponentId": null }, { "bbox": { "h": 0.05, "w": 0.4, "x": 0.3, "y": 0.29 }, "kind": "title", "text": "Average Length of Time to Transition From Pilot to Full Production\nAmong ITDMs in Advanced vs. Emerging AI Ecosystem Markets, Showing % Selected", "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 17:31:42.491+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "665cee80-4f5c-4af4-9a1a-912b2c822580", "parentComponentId": null } ], "metrics": [], "tools": [ { "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": "6b6ece98-1afd-4224-ad0a-6a56e44e8f8f", "evidence": "Grouped bar chart showing 9 categories of obstacles with percentages for two market types.", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 0.5, "extraction": { "at": "2026-07-16 22:02:09.728587+00", "model": "or:meta-llama/llama-4-scout", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 37, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null } ], "frameworks": [], "arcBeats": [ { "to": 77, "arc": { "name": "The Sparkline", "slug": "sparkline", "status": "active", "bestFor": "Keynotes, TED-style talks", "canonId": "019dd956-606e-720c-905a-42607ac0bf50", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "What Is -> What Could Be -> What Is -> What Could Be -> New Bliss", "description": null, "familyLabel": null }, "from": 29, "name": "Evidence", "beatId": "5bb325e2-e460-48c2-ba3f-ded31b7b7818", "matchId": "bf9fcf67-d39d-4c8d-8724-bdd9506a6c64", "beatType": { "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." }, "evidence": "The deck provides extensive data and evidence to support its findings and recommendations.", "position": 4, "isPrimaryArc": true, "parentBeatType": null, "alignedBlockIds": null, "matchConfidence": 0.8 } ], "loops": [], "locked": true }, { "page": 38, "type": "analysis", "title": "Data source: IBM. Sample sizes: Advanced (1,404), Emerging (1,005).", "function": "analyze_data", "rawType": "appendix_data", "block": null, "metadata": { "slideType": "appendix_data", "slideTypeCanon": { "name": "Appendix data", "slug": "appendix_data", "status": "active", "canonId": "019de52d-078a-745b-9ee4-c15f2f539acd", "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": "dense", "densityScore": 56, "componentCount": 6, "textChars": 600, "nDataPoints": 18, "notes": "Data source: IBM. Sample sizes: Advanced (1,404), Emerging (1,005).", "elementsJson": [ "bar_chart_grouped" ], "confidence": 1, "extraction": { "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "at": "2026-05-02 17:31:37.405+00", "seconds": 2.719, "promptVersion": "v2-canon-conditioned" } }, "links": { "slide": "/slides/019dd923-5e88-73ef-bd5d-e266bb5de1d1/38", "deck": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1", "deckAnchor": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1#slide-38", "deckJson": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1.json" }, "components": [ { "bbox": { "h": 0.5, "w": 0.4, "x": 0.2, "y": 0.35 }, "kind": "chart", "text": "Grouped bar chart showing 9 categories of obstacles with percentages for two market types.", "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": "Grouped bar chart", "slug": "bar-grouped", "status": "active", "canonId": "019de52c-ff3b-751e-a8ff-f21ff11097b1", "version": 1, "description": null }, "framework": null }, "subkind": "bar-grouped", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 17:31:37.405+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "f611ba14-5716-499d-97c1-a9b58b9ce63a", "parentComponentId": null }, { "bbox": { "h": 0.06, "w": 0.15, "x": 0.78, "y": 0.59 }, "kind": "legend", "text": "Advanced AI Ecosystems; Emerging AI Ecosystems", "attrs": null, "canon": { "kind": { "name": "Legend", "slug": "legend", "status": "active", "canonId": "31361933-3d22-4c70-bbad-0801e9fffc0c", "version": 1, "description": "Color/symbol decoder placed adjacent to a chart or diagram." }, "tool": null, "subkind": null, "framework": null }, "subkind": null, "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 17:31:37.405+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "07dfe722-5b38-4387-94c3-8618bfe2ae80", "parentComponentId": null }, { "bbox": null, "kind": "metric", "text": "Percentage of ITDMs: 51%", "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": "2026-04-25 12:20:11+00", "model": "or:google/gemini-3.1-flash-lite-preview", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "019dd952-5644-756a-a84a-c2d4ccfe3e79", "parentComponentId": null }, { "bbox": { "h": 0.05, "w": 0.7, "x": 0.18, "y": 0.93 }, "kind": "paragraph", "text": "IBM Which of the following obstacles, if any, has your company encountered when moving AI projects from pilot to full implementation? Please select all that apply. Sample Size: Advanced AI Ecosystem (US, Canada, UK, France, Germany, Singapore, South Korea) = 1,404, Emerging AI Ecosystems(Mexico, Spain, Brazil, India, Indonesia) = 1,005", "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": null, "framework": null }, "subkind": "source-note", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 17:31:37.405+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "e4db27fa-1eb3-4a35-8976-41cf300efb04", "parentComponentId": null }, { "bbox": { "h": 0.03, "w": 0.5, "x": 0.05, "y": 0.07 }, "kind": "title", "text": "APPENDIX: ADVANCED VS. EMERGING AI ECOSYSTEM MARKETS", "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 17:31:37.405+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "3259b374-bca1-4451-b93a-5191eed51c6b", "parentComponentId": null }, { "bbox": { "h": 0.02, "w": 0.33, "x": 0.33, "y": 0.295 }, "kind": "title", "text": "Obstacles Faced When Implementing AI Pilot Projects", "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 17:31:37.405+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "bd7ed694-1c60-44d1-9483-872b275456c2", "parentComponentId": null } ], "metrics": [], "tools": [ { "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": "f3c025ae-5985-4947-bab8-f7ba49d19210", "evidence": "chart/bar-grouped: Grouped bar chart showing 7 categories of AI implementation challenges", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 0.5, "extraction": { "at": "2026-07-16 22:02:09.795049+00", "model": "or:meta-llama/llama-4-scout", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 38, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null } ], "frameworks": [], "arcBeats": [ { "to": 77, "arc": { "name": "The Sparkline", "slug": "sparkline", "status": "active", "bestFor": "Keynotes, TED-style talks", "canonId": "019dd956-606e-720c-905a-42607ac0bf50", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "What Is -> What Could Be -> What Is -> What Could Be -> New Bliss", "description": null, "familyLabel": null }, "from": 29, "name": "Evidence", "beatId": "5bb325e2-e460-48c2-ba3f-ded31b7b7818", "matchId": "bf9fcf67-d39d-4c8d-8724-bdd9506a6c64", "beatType": { "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." }, "evidence": "The deck provides extensive data and evidence to support its findings and recommendations.", "position": 4, "isPrimaryArc": true, "parentBeatType": null, "alignedBlockIds": null, "matchConfidence": 0.8 } ], "loops": [], "locked": true }, { "page": 39, "type": "analysis", "title": "Data source: Morning Consult. Sample sizes: Advanced (1,407), Emerging (1,006).", "function": "analyze_data", "rawType": "appendix_data", "block": null, "metadata": { "slideType": "appendix_data", "slideTypeCanon": { "name": "Appendix data", "slug": "appendix_data", "status": "active", "canonId": "019de52d-078a-745b-9ee4-c15f2f539acd", "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": "balanced", "densityScore": 48, "componentCount": 6, "textChars": 458, "nDataPoints": 6, "notes": "Data source: Morning Consult. Sample sizes: Advanced (1,407), Emerging (1,006).", "elementsJson": [ "bar_chart_grouped" ], "confidence": 1, "extraction": { "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "at": "2026-05-02 17:31:37.976+00", "seconds": 3.128, "promptVersion": "v2-canon-conditioned" } }, "links": { "slide": "/slides/019dd923-5e88-73ef-bd5d-e266bb5de1d1/39", "deck": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1", "deckAnchor": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1#slide-39", "deckJson": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1.json" }, "components": [ { "bbox": { "h": 0.45, "w": 0.45, "x": 0.215, "y": 0.38 }, "kind": "chart", "text": null, "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": "Grouped bar chart", "slug": "bar-grouped", "status": "active", "canonId": "019de52c-ff3b-751e-a8ff-f21ff11097b1", "version": 1, "description": null }, "framework": null }, "subkind": "bar-grouped", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 17:31:37.976+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "b9f9d900-bb1c-4dfb-a5ca-95894ca557a9", "parentComponentId": null }, { "bbox": { "h": 0.03, "w": 0.69, "x": 0.18, "y": 0.935 }, "kind": "disclaimer", "text": "IBM6 Where does your company source your AI tools?\nSample Size: Advanced AI Ecosystem (US, Canada, UK, France, Germany, Singapore, South Korea) = 1,407, Emerging AI Ecosystems(Mexico, Spain, Brazil, India, Indonesia) = 1,006", "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 17:31:37.976+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "7586c7c9-2bf1-45c4-bd9b-76b8d5335669", "parentComponentId": null }, { "bbox": { "h": 0.04, "w": 0.15, "x": 0.79, "y": 0.6 }, "kind": "legend", "text": "Advanced AI Ecosystems\nEmerging AI Ecosystems", "attrs": null, "canon": { "kind": { "name": "Legend", "slug": "legend", "status": "active", "canonId": "31361933-3d22-4c70-bbad-0801e9fffc0c", "version": 1, "description": "Color/symbol decoder placed adjacent to a chart or diagram." }, "tool": null, "subkind": null, "framework": null }, "subkind": null, "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 17:31:37.976+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "4143214e-6f5f-45a1-b1ca-87ff4f013e8d", "parentComponentId": null }, { "bbox": null, "kind": "metric", "text": "Percentage of ITDMs selecting source: 67%", "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": "2026-04-25 12:20:11+00", "model": "or:google/gemini-3.1-flash-lite-preview", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "019dd952-5644-756a-a849-bb1150a3173a", "parentComponentId": null }, { "bbox": { "h": 0.022, "w": 0.536, "x": 0.056, "y": 0.078 }, "kind": "title", "text": "APPENDIX: ADVANCED VS. EMERGING AI ECOSYSTEM MARKETS", "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 17:31:37.976+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "99e33703-9580-4fc8-a6c7-725bd7aad7c6", "parentComponentId": null }, { "bbox": { "h": 0.035, "w": 0.36, "x": 0.32, "y": 0.295 }, "kind": "title", "text": "Source of AI Tools\nAmong ITDMs in Advanced vs. Emerging AI Ecosystem Markets, Showing % Selected", "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 17:31:37.976+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "090c0eb6-ef48-4d5c-8daf-fc92caa6dca2", "parentComponentId": null } ], "metrics": [], "tools": [ { "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": "3a469373-c229-4320-aff9-8dfc158803fa", "evidence": "chart/bar-grouped: Grouped bar chart showing distribution of AI pilots (None, 1-10, 11-20, 21-30, More than 30) for Advanced vs Emerging markets.", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 0.5, "extraction": { "at": "2026-07-16 22:02:09.861503+00", "model": "or:meta-llama/llama-4-scout", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 39, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null } ], "frameworks": [], "arcBeats": [ { "to": 77, "arc": { "name": "The Sparkline", "slug": "sparkline", "status": "active", "bestFor": "Keynotes, TED-style talks", "canonId": "019dd956-606e-720c-905a-42607ac0bf50", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "What Is -> What Could Be -> What Is -> What Could Be -> New Bliss", "description": null, "familyLabel": null }, "from": 29, "name": "Evidence", "beatId": "5bb325e2-e460-48c2-ba3f-ded31b7b7818", "matchId": "bf9fcf67-d39d-4c8d-8724-bdd9506a6c64", "beatType": { "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." }, "evidence": "The deck provides extensive data and evidence to support its findings and recommendations.", "position": 4, "isPrimaryArc": true, "parentBeatType": null, "alignedBlockIds": null, "matchConfidence": 0.8 } ], "loops": [], "locked": true }, { "page": 40, "type": "analysis", "title": "Data source: Morning Consult. Sample sizes provided in footer.", "function": "analyze_data", "rawType": "appendix_data", "block": null, "metadata": { "slideType": "appendix_data", "slideTypeCanon": { "name": "Appendix data", "slug": "appendix_data", "status": "active", "canonId": "019de52d-078a-745b-9ee4-c15f2f539acd", "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": "dense", "densityScore": 53, "componentCount": 6, "textChars": 525, "nDataPoints": 14, "notes": "Data source: Morning Consult. Sample sizes provided in footer.", "elementsJson": [ "bar_chart_grouped", "footnote" ], "confidence": 1, "extraction": { "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "at": "2026-05-02 17:31:41.19+00", "seconds": 6.257, "promptVersion": "v2-canon-conditioned" } }, "links": { "slide": "/slides/019dd923-5e88-73ef-bd5d-e266bb5de1d1/40", "deck": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1", "deckAnchor": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1#slide-40", "deckJson": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1.json" }, "components": [ { "bbox": { "h": 0.5, "w": 0.3, "x": 0.2, "y": 0.35 }, "kind": "chart", "text": "Grouped bar chart showing 7 categories of AI implementation challenges", "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": "Grouped bar chart", "slug": "bar-grouped", "status": "active", "canonId": "019de52c-ff3b-751e-a8ff-f21ff11097b1", "version": 1, "description": null }, "framework": null }, "subkind": "bar-grouped", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 17:31:41.19+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "dcf186c7-7cf1-40ff-84e2-7241c142df0f", "parentComponentId": null }, { "bbox": { "h": 0.05, "w": 0.7, "x": 0.18, "y": 0.93 }, "kind": "disclaimer", "text": "IBM7 How challenging are the following obstacles for your company when implementing AI? Sample Size: Advanced AI Ecosystem (US, Canada, UK, France, Germany, Singapore, South Korea) = 1,407, Emerging AI Ecosystems(Mexico, Spain, Brazil, India, Indonesia) = 1,006", "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 17:31:41.19+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "4a6b5535-9d58-40a8-86e4-c43f1d882cd8", "parentComponentId": null }, { "bbox": { "h": 0.06, "w": 0.15, "x": 0.78, "y": 0.59 }, "kind": "legend", "text": "Advanced AI Ecosystems; Emerging AI Ecosystems", "attrs": null, "canon": { "kind": { "name": "Legend", "slug": "legend", "status": "active", "canonId": "31361933-3d22-4c70-bbad-0801e9fffc0c", "version": 1, "description": "Color/symbol decoder placed adjacent to a chart or diagram." }, "tool": null, "subkind": null, "framework": null }, "subkind": null, "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 17:31:41.19+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "aa4b0806-21dc-4a45-88f9-70e0fe7ba9fe", "parentComponentId": null }, { "bbox": null, "kind": "metric", "text": "Percentage of ITDMs selecting 'Very challenging': 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": "2026-04-25 12:20:11+00", "model": "or:google/gemini-3.1-flash-lite-preview", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "019dd952-5644-756a-a84a-518bd89ee6b9", "parentComponentId": null }, { "bbox": { "h": 0.03, "w": 0.5, "x": 0.05, "y": 0.07 }, "kind": "title", "text": "APPENDIX: ADVANCED VS. EMERGING AI ECOSYSTEM MARKETS", "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 17:31:41.19+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "0a2c5892-e4c9-482d-bb1d-df2d194f7272", "parentComponentId": null }, { "bbox": { "h": 0.03, "w": 0.3, "x": 0.35, "y": 0.295 }, "kind": "title", "text": "Significant Challenges When Implementing 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 17:31:41.19+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "58a7e1f8-fc61-4119-87f6-b2e3f9bf8319", "parentComponentId": null } ], "metrics": [], "tools": [ { "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": "8a327cd1-7790-4592-90ca-9b1d95721d7a", "evidence": "chart/bar-stacked-100pct: Stacked bar chart comparing motivations for Advanced vs Emerging AI Ecosystems", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 0.5, "extraction": { "at": "2026-07-16 22:02:09.930567+00", "model": "or:meta-llama/llama-4-scout", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 40, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null } ], "frameworks": [], "arcBeats": [ { "to": 77, "arc": { "name": "The Sparkline", "slug": "sparkline", "status": "active", "bestFor": "Keynotes, TED-style talks", "canonId": "019dd956-606e-720c-905a-42607ac0bf50", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "What Is -> What Could Be -> What Is -> What Could Be -> New Bliss", "description": null, "familyLabel": null }, "from": 29, "name": "Evidence", "beatId": "5bb325e2-e460-48c2-ba3f-ded31b7b7818", "matchId": "bf9fcf67-d39d-4c8d-8724-bdd9506a6c64", "beatType": { "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." }, "evidence": "The deck provides extensive data and evidence to support its findings and recommendations.", "position": 4, "isPrimaryArc": true, "parentBeatType": null, "alignedBlockIds": null, "matchConfidence": 0.8 } ], "loops": [], "locked": true }, { "page": 41, "type": "analysis", "title": "Data source: Morning Consult. Sample sizes provided in footer.", "function": "analyze_data", "rawType": "appendix_data", "block": null, "metadata": { "slideType": "appendix_data", "slideTypeCanon": { "name": "Appendix data", "slug": "appendix_data", "status": "active", "canonId": "019de52d-078a-745b-9ee4-c15f2f539acd", "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": "dense", "densityScore": 55, "componentCount": 6, "textChars": 599, "nDataPoints": 10, "notes": "Data source: Morning Consult. Sample sizes provided in footer.", "elementsJson": [ "bar_chart_grouped" ], "confidence": 1, "extraction": { "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "at": "2026-05-02 17:31:42.956+00", "seconds": 7.917, "promptVersion": "v2-canon-conditioned" } }, "links": { "slide": "/slides/019dd923-5e88-73ef-bd5d-e266bb5de1d1/41", "deck": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1", "deckAnchor": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1#slide-41", "deckJson": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1.json" }, "components": [ { "bbox": { "h": 0.5, "w": 0.25, "x": 0.3, "y": 0.37 }, "kind": "chart", "text": "Grouped bar chart showing distribution of AI pilots (None, 1-10, 11-20, 21-30, More than 30) for Advanced vs Emerging markets.", "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": "Grouped bar chart", "slug": "bar-grouped", "status": "active", "canonId": "019de52c-ff3b-751e-a8ff-f21ff11097b1", "version": 1, "description": null }, "framework": null }, "subkind": "bar-grouped", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 17:31:42.956+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "49bd8a3b-865b-40d8-88f9-1b79fd2f1d4f", "parentComponentId": null }, { "bbox": { "h": 0.05, "w": 0.7, "x": 0.18, "y": 0.93 }, "kind": "disclaimer", "text": "IBM8 How many AI pilots does your company have planned for 2025?\nSample Size: Advanced AI Ecosystem (US, Canada, UK, France, Germany, Singapore, South Korea) = 1,407, Emerging AI Ecosystems(Mexico, Spain, Brazil, India, Indonesia) = 1,006", "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 17:31:42.956+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "e03bad4d-dd72-4f86-934c-955e33dd2268", "parentComponentId": null }, { "bbox": { "h": 0.05, "w": 0.15, "x": 0.78, "y": 0.595 }, "kind": "legend", "text": "Advanced AI Ecosystems\nEmerging AI Ecosystems", "attrs": null, "canon": { "kind": { "name": "Legend", "slug": "legend", "status": "active", "canonId": "31361933-3d22-4c70-bbad-0801e9fffc0c", "version": 1, "description": "Color/symbol decoder placed adjacent to a chart or diagram." }, "tool": null, "subkind": null, "framework": null }, "subkind": null, "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 17:31:42.956+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "858062af-8505-4cd3-905a-b0bd2fbc3849", "parentComponentId": null }, { "bbox": null, "kind": "metric", "text": "Number of AI pilots: 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": "2026-04-25 12:20:11+00", "model": "or:google/gemini-3.1-flash-lite-preview", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "019dd952-5644-756a-a849-d96ab7d7910f", "parentComponentId": null }, { "bbox": { "h": 0.03, "w": 0.5, "x": 0.05, "y": 0.07 }, "kind": "title", "text": "APPENDIX: ADVANCED VS. EMERGING AI ECOSYSTEM MARKETS", "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 17:31:42.956+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "66faaf03-72c8-4ae1-86f1-95fbce9eef2a", "parentComponentId": null }, { "bbox": { "h": 0.05, "w": 0.4, "x": 0.3, "y": 0.29 }, "kind": "title", "text": "Number of AI Pilots Planned for 2025\nAmong ITDMs in Advanced vs. Emerging AI Ecosystem Markets, Showing % Selected", "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 17:31:42.956+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "dcebec3a-f039-4cda-9936-be7c37276fa6", "parentComponentId": null } ], "metrics": [], "tools": [ { "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": "6a62a76b-0c8b-4f67-976b-ac0fde6699cd", "evidence": "chart/bar-grouped: Grouped bar chart showing distribution of AI pilots planned for 2025", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 0.5, "extraction": { "at": "2026-07-16 22:02:09.997827+00", "model": "or:meta-llama/llama-4-scout", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 41, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null } ], "frameworks": [], "arcBeats": [ { "to": 77, "arc": { "name": "The Sparkline", "slug": "sparkline", "status": "active", "bestFor": "Keynotes, TED-style talks", "canonId": "019dd956-606e-720c-905a-42607ac0bf50", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "What Is -> What Could Be -> What Is -> What Could Be -> New Bliss", "description": null, "familyLabel": null }, "from": 29, "name": "Evidence", "beatId": "5bb325e2-e460-48c2-ba3f-ded31b7b7818", "matchId": "bf9fcf67-d39d-4c8d-8724-bdd9506a6c64", "beatType": { "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." }, "evidence": "The deck provides extensive data and evidence to support its findings and recommendations.", "position": 4, "isPrimaryArc": true, "parentBeatType": null, "alignedBlockIds": null, "matchConfidence": 0.8 } ], "loops": [], "locked": true }, { "page": 42, "type": "analysis", "title": "Data source: Morning Consult. Sample sizes provided in footer.", "function": "analyze_data", "rawType": "appendix_data", "block": null, "metadata": { "slideType": "appendix_data", "slideTypeCanon": { "name": "Appendix data", "slug": "appendix_data", "status": "active", "canonId": "019de52d-078a-745b-9ee4-c15f2f539acd", "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": "dense", "densityScore": 57, "componentCount": 6, "textChars": 688, "nDataPoints": 10, "notes": "Data source: Morning Consult. Sample sizes provided in footer.", "elementsJson": [ "headline_text", "bar_chart_grouped", "footnote" ], "confidence": 1, "extraction": { "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "at": "2026-05-02 17:31:37.898+00", "seconds": 2.774, "promptVersion": "v2-canon-conditioned" } }, "links": { "slide": "/slides/019dd923-5e88-73ef-bd5d-e266bb5de1d1/42", "deck": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1", "deckAnchor": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1#slide-42", "deckJson": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1.json" }, "components": [ { "bbox": { "h": 0.5, "w": 0.3, "x": 0.3, "y": 0.35 }, "kind": "chart", "text": "Grouped bar chart showing distribution of open-source usage percentages (0%, 1-24%, 25-49%, 50-74%, 75-100%) for Advanced vs Emerging markets.", "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": "Grouped bar chart", "slug": "bar-grouped", "status": "active", "canonId": "019de52c-ff3b-751e-a8ff-f21ff11097b1", "version": 1, "description": null }, "framework": null }, "subkind": "bar-grouped", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 17:31:37.898+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "885f7a46-0cff-42c0-a140-b2b7e01aa40f", "parentComponentId": null }, { "bbox": { "h": 0.05, "w": 0.7, "x": 0.18, "y": 0.93 }, "kind": "disclaimer", "text": "IBM10 What percentage of your company's current AI solutions or platforms are based on opensource?\nSample Size: Advanced AI Ecosystem (US, Canada, UK, France, Germany, Singapore, South Korea) = 1,407, Emerging AI Ecosystems(Mexico, Spain, Brazil, India, Indonesia) = 1,006", "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 17:31:37.898+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "ecc3e331-8334-4fb5-8fe5-f037071aa1d5", "parentComponentId": null }, { "bbox": { "h": 0.05, "w": 0.15, "x": 0.78, "y": 0.595 }, "kind": "legend", "text": "Advanced AI Ecosystems\nEmerging AI Ecosystems", "attrs": null, "canon": { "kind": { "name": "Legend", "slug": "legend", "status": "active", "canonId": "31361933-3d22-4c70-bbad-0801e9fffc0c", "version": 1, "description": "Color/symbol decoder placed adjacent to a chart or diagram." }, "tool": null, "subkind": null, "framework": null }, "subkind": null, "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 17:31:37.898+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "5d9aae0f-c34b-40dc-ac7e-394be7e5b2b6", "parentComponentId": null }, { "bbox": null, "kind": "metric", "text": "Percentage of AI solutions based on open-source: 49%", "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": "2026-04-25 12:20:11+00", "model": "or:google/gemini-3.1-flash-lite-preview", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "019dd952-5644-756a-a84a-9e8d65f48d8e", "parentComponentId": null }, { "bbox": { "h": 0.03, "w": 0.5, "x": 0.05, "y": 0.07 }, "kind": "title", "text": "APPENDIX: ADVANCED VS. EMERGING AI ECOSYSTEM MARKETS", "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 17:31:37.898+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "60e3b69f-99c9-453a-8e10-8bc529a449d7", "parentComponentId": null }, { "bbox": { "h": 0.05, "w": 0.4, "x": 0.3, "y": 0.29 }, "kind": "title", "text": "Percentage of AI Solutions Based on Open-Source\nAmong ITDMs in Advanced vs. Emerging AI Ecosystem Markets, Showing % Selected", "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 17:31:37.898+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "59e8237b-d019-43e3-9928-ef7ccca5ac6b", "parentComponentId": null } ], "metrics": [], "tools": [ { "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": "ec7e1308-705a-498b-a0b5-3822e09d7937", "evidence": "chart/bar-grouped: Grouped bar chart showing distribution of open-source usage percentages", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 0.5, "extraction": { "at": "2026-07-16 22:02:10.064766+00", "model": "or:meta-llama/llama-4-scout", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 42, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null } ], "frameworks": [], "arcBeats": [ { "to": 77, "arc": { "name": "The Sparkline", "slug": "sparkline", "status": "active", "bestFor": "Keynotes, TED-style talks", "canonId": "019dd956-606e-720c-905a-42607ac0bf50", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "What Is -> What Could Be -> What Is -> What Could Be -> New Bliss", "description": null, "familyLabel": null }, "from": 29, "name": "Evidence", "beatId": "5bb325e2-e460-48c2-ba3f-ded31b7b7818", "matchId": "bf9fcf67-d39d-4c8d-8724-bdd9506a6c64", "beatType": { "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." }, "evidence": "The deck provides extensive data and evidence to support its findings and recommendations.", "position": 4, "isPrimaryArc": true, "parentBeatType": null, "alignedBlockIds": null, "matchConfidence": 0.8 } ], "loops": [], "locked": true }, { "page": 43, "type": "analysis", "title": "Data source: Morning Consult, IBM11 survey.", "function": "analyze_data", "rawType": "appendix_data", "block": null, "metadata": { "slideType": "appendix_data", "slideTypeCanon": { "name": "Appendix data", "slug": "appendix_data", "status": "active", "canonId": "019de52d-078a-745b-9ee4-c15f2f539acd", "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": "dense", "densityScore": 56, "componentCount": 6, "textChars": 649, "nDataPoints": 10, "notes": "Data source: Morning Consult, IBM11 survey.", "elementsJson": [ "bar_chart_stacked" ], "confidence": 1, "extraction": { "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "at": "2026-05-02 17:31:38.4+00", "seconds": 3.157, "promptVersion": "v2-canon-conditioned" } }, "links": { "slide": "/slides/019dd923-5e88-73ef-bd5d-e266bb5de1d1/43", "deck": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1", "deckAnchor": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1#slide-43", "deckJson": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1.json" }, "components": [ { "bbox": { "h": 0.45, "w": 0.75, "x": 0.22, "y": 0.4 }, "kind": "chart", "text": "Stacked bar chart comparing motivations for Advanced vs Emerging AI Ecosystems", "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": "Stacked bar chart (100%)", "slug": "bar-stacked-100pct", "status": "active", "canonId": "019de52c-ff14-71b8-8d88-860f8d7da84b", "version": 1, "description": null }, "framework": null }, "subkind": "bar-stacked-100pct", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 17:31:38.4+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "8577214f-4f9d-4fd1-8a13-9c6ff5b73229", "parentComponentId": null }, { "bbox": { "h": 0.05, "w": 0.7, "x": 0.18, "y": 0.93 }, "kind": "disclaimer", "text": "IBM11 What is the primary motivation driving AI implementation at your company? Sample Size: Advanced AI Ecosystem (US, Canada, UK, France, Germany, Singapore, South Korea) = 1,407, Emerging AI Ecosystems (Mexico, Spain, Brazil, India, Indonesia) = 1,006", "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 17:31:38.4+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "a7dbc81a-d755-4f1d-a862-192f06e4345f", "parentComponentId": null }, { "bbox": { "h": 0.03, "w": 0.8, "x": 0.11, "y": 0.35 }, "kind": "legend", "text": "Completely innovation-driven, Mostly innovation-driven, Equally innovation-driven and ROI-driven, Mostly ROI-driven, Completely ROI-driven", "attrs": null, "canon": { "kind": { "name": "Legend", "slug": "legend", "status": "active", "canonId": "31361933-3d22-4c70-bbad-0801e9fffc0c", "version": 1, "description": "Color/symbol decoder placed adjacent to a chart or diagram." }, "tool": null, "subkind": null, "framework": null }, "subkind": null, "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 17:31:38.4+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "b8c16ae6-971d-4801-8323-4d363972a53a", "parentComponentId": null }, { "bbox": null, "kind": "metric", "text": "Motivation for AI implementation", "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": "2026-04-25 12:20:11+00", "model": "or:google/gemini-3.1-flash-lite-preview", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "019dd952-5644-756a-a849-fb819713bf6d", "parentComponentId": null }, { "bbox": { "h": 0.03, "w": 0.5, "x": 0.05, "y": 0.07 }, "kind": "title", "text": "APPENDIX: ADVANCED VS. EMERGING AI ECOSYSTEM MARKETS", "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 17:31:38.4+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "6728c799-0445-43ee-8f70-50b05ee7dfb0", "parentComponentId": null }, { "bbox": { "h": 0.05, "w": 0.4, "x": 0.3, "y": 0.28 }, "kind": "title", "text": "Motivations Driving AI Implementation\nAmong ITDMs in Advanced vs. Emerging AI Ecosystem Markets", "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 17:31:38.4+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "483e07ec-0825-41e4-81b3-901bb1bb73d7", "parentComponentId": null } ], "metrics": [], "tools": [ { "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": "f9e5fbbc-8fc7-4183-b984-06e4f4f0c560", "evidence": "legend: Completely innovation-driven, Mostly innovation-driven, Equally innovation-driven and ROI-driven, Mostly ROI-driven, Completely ROI-driven", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 0.5, "extraction": { "at": "2026-07-16 22:02:10.134398+00", "model": "or:meta-llama/llama-4-scout", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 43, "whyItWorks": null, "antipattern": null, "cardinality": "common", "narrativePurpose": null } ], "frameworks": [], "arcBeats": [ { "to": 77, "arc": { "name": "The Sparkline", "slug": "sparkline", "status": "active", "bestFor": "Keynotes, TED-style talks", "canonId": "019dd956-606e-720c-905a-42607ac0bf50", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "What Is -> What Could Be -> What Is -> What Could Be -> New Bliss", "description": null, "familyLabel": null }, "from": 29, "name": "Evidence", "beatId": "5bb325e2-e460-48c2-ba3f-ded31b7b7818", "matchId": "bf9fcf67-d39d-4c8d-8724-bdd9506a6c64", "beatType": { "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." }, "evidence": "The deck provides extensive data and evidence to support its findings and recommendations.", "position": 4, "isPrimaryArc": true, "parentBeatType": null, "alignedBlockIds": null, "matchConfidence": 0.8 } ], "loops": [], "locked": true }, { "page": 44, "type": "analysis", "title": "The chart shows that Emerging AI Ecosystem markets generally report higher percentages for most ROI metrics compared to Advanced AI Ecosystem markets, except fo", "function": "analyze_data", "rawType": "appendix_data", "block": null, "metadata": { "slideType": "appendix_data", "slideTypeCanon": { "name": "Appendix data", "slug": "appendix_data", "status": "active", "canonId": "019de52d-078a-745b-9ee4-c15f2f539acd", "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": "dense", "densityScore": 53, "componentCount": 6, "textChars": 539, "nDataPoints": 10, "notes": "The chart shows that Emerging AI Ecosystem markets generally report higher percentages for most ROI metrics compared to Advanced AI Ecosystem markets, except for hard dollar savings which are equal.", "elementsJson": [ "bar_chart_grouped", "footnote" ], "confidence": 1, "extraction": { "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "at": "2026-05-02 17:31:38.335+00", "seconds": 3.08, "promptVersion": "v2-canon-conditioned" } }, "links": { "slide": "/slides/019dd923-5e88-73ef-bd5d-e266bb5de1d1/44", "deck": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1", "deckAnchor": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1#slide-44", "deckJson": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1.json" }, "components": [ { "bbox": { "h": 0.55, "w": 0.6, "x": 0.2, "y": 0.35 }, "kind": "chart", "text": null, "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": "Grouped bar chart", "slug": "bar-grouped", "status": "active", "canonId": "019de52c-ff3b-751e-a8ff-f21ff11097b1", "version": 1, "description": null }, "framework": null }, "subkind": "bar-grouped", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 17:31:38.335+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "a0da8c49-d634-402b-b277-64ac2125e132", "parentComponentId": null }, { "bbox": { "h": 0.05, "w": 0.7, "x": 0.18, "y": 0.93 }, "kind": "disclaimer", "text": "IBM12 How does your company calculate return on investment (ROI) from AI investments? Please select all that apply.\nSample Size: Advanced AI Ecosystem (US, Canada, UK, France, Germany, Singapore, South Korea) = 1,407, Emerging AI Ecosystems(Mexico, Spain, Brazil, India, Indonesia) = 1,006", "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 17:31:38.335+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "0a6c78e0-ab3d-460b-8a00-6c9f5c62317d", "parentComponentId": null }, { "bbox": { "h": 0.05, "w": 0.15, "x": 0.78, "y": 0.595 }, "kind": "legend", "text": "Advanced AI Ecosystems\nEmerging AI Ecosystems", "attrs": null, "canon": { "kind": { "name": "Legend", "slug": "legend", "status": "active", "canonId": "31361933-3d22-4c70-bbad-0801e9fffc0c", "version": 1, "description": "Color/symbol decoder placed adjacent to a chart or diagram." }, "tool": null, "subkind": null, "framework": null }, "subkind": null, "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 17:31:38.335+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "66ec7994-6bcb-4158-b716-6376bc2ac702", "parentComponentId": null }, { "bbox": null, "kind": "metric", "text": "ROI measurement metrics: 67%", "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": "2026-04-25 12:20:11+00", "model": "or:google/gemini-3.1-flash-lite-preview", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "019dd952-5644-756a-a84a-89856f82c1ba", "parentComponentId": null }, { "bbox": { "h": 0.03, "w": 0.5, "x": 0.05, "y": 0.07 }, "kind": "title", "text": "APPENDIX: ADVANCED VS. EMERGING AI ECOSYSTEM MARKETS", "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 17:31:38.335+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "3e9e3c5a-90bf-4054-b93e-f4b6ad6e9a73", "parentComponentId": null }, { "bbox": { "h": 0.05, "w": 0.4, "x": 0.3, "y": 0.29 }, "kind": "title", "text": "Metrics Used to Measure ROI from AI Investments\nAmong ITDMs in Advanced vs. Emerging AI Ecosystem Markets, Showing % Selected", "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 17:31:38.335+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "520cd992-79ab-4bf3-be65-adf2052a8d78", "parentComponentId": null } ], "metrics": [], "tools": [ { "tool": { "name": "Chartjunk Elimination", "slug": "chartjunk-elimination", "status": "active", "bestFor": null, "canonId": "019dd956-b49e-7453-ab01-b60f338eeda1", "version": 1, "bodyDocId": null, "description": "Remove decorative elements that don't convey data: 3D effects, shadows, unnecessary gridlines", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Designer", "layer": "slide", "agents": [ "Designer" ], "matchId": "a2b5de1a-99c0-4f60-aef1-0947c56842cf", "evidence": "The slide contains a grouped bar chart with clear labels and a legend, showing a simple and effective visualization of data.", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 0.7, "extraction": { "at": "2026-07-16 22:02:11.148935+00", "model": "or:meta-llama/llama-4-scout", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 44, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "Data-Ink Ratio", "slug": "data-ink-ratio", "status": "active", "bestFor": null, "canonId": "019dd956-afc8-70da-b378-92834d36fde6", "version": 1, "bodyDocId": null, "description": "Maximize data, minimize non-data ink - remove chartjunk and decoration", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Designer", "layer": "slide", "agents": [ "Designer" ], "matchId": "787461ba-993c-4b74-ba0a-f0a3d6253c2e", "evidence": "The chart appears to have a high data-ink ratio, with a clear focus on presenting the data.", "pageRefs": null, "priority": "Core", "whenToUse": null, "confidence": 0.7, "extraction": { "at": "2026-07-16 22:02:11.18878+00", "model": "or:meta-llama/llama-4-scout", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 44, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null } ], "frameworks": [], "arcBeats": [ { "to": 77, "arc": { "name": "The Sparkline", "slug": "sparkline", "status": "active", "bestFor": "Keynotes, TED-style talks", "canonId": "019dd956-606e-720c-905a-42607ac0bf50", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "What Is -> What Could Be -> What Is -> What Could Be -> New Bliss", "description": null, "familyLabel": null }, "from": 29, "name": "Evidence", "beatId": "5bb325e2-e460-48c2-ba3f-ded31b7b7818", "matchId": "bf9fcf67-d39d-4c8d-8724-bdd9506a6c64", "beatType": { "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." }, "evidence": "The deck provides extensive data and evidence to support its findings and recommendations.", "position": 4, "isPrimaryArc": true, "parentBeatType": null, "alignedBlockIds": null, "matchConfidence": 0.8 } ], "loops": [], "locked": true }, { "page": 45, "type": "analysis", "title": "Data source: Morning Consult / IBM12a. Sample sizes: Advanced (1,407), Emerging (1,006).", "function": "analyze_data", "rawType": "appendix_data", "block": null, "metadata": { "slideType": "appendix_data", "slideTypeCanon": { "name": "Appendix data", "slug": "appendix_data", "status": "active", "canonId": "019de52d-078a-745b-9ee4-c15f2f539acd", "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": "dense", "densityScore": 55, "componentCount": 6, "textChars": 620, "nDataPoints": 10, "notes": "Data source: Morning Consult / IBM12a. Sample sizes: Advanced (1,407), Emerging (1,006).", "elementsJson": [ "bar_chart_grouped" ], "confidence": 1, "extraction": { "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "at": "2026-05-02 17:31:42.265+00", "seconds": 6.932, "promptVersion": "v2-canon-conditioned" } }, "links": { "slide": "/slides/019dd923-5e88-73ef-bd5d-e266bb5de1d1/45", "deck": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1", "deckAnchor": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1#slide-45", "deckJson": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1.json" }, "components": [ { "bbox": { "h": 0.5, "w": 0.35, "x": 0.18, "y": 0.37 }, "kind": "chart", "text": "Grouped bar chart showing 5 categories of ROI metrics across two market types.", "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": "Grouped bar chart", "slug": "bar-grouped", "status": "active", "canonId": "019de52c-ff3b-751e-a8ff-f21ff11097b1", "version": 1, "description": null }, "framework": null }, "subkind": "bar-grouped", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 17:31:42.265+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "abea427f-e399-408f-899f-badd963e4de9", "parentComponentId": null }, { "bbox": { "h": 0.05, "w": 0.7, "x": 0.18, "y": 0.93 }, "kind": "disclaimer", "text": "IBM12a Which of these metrics is most important to your company when measuring ROI from AI investments?\nSample Size: Advanced AI Ecosystem (US, Canada, UK, France, Germany, Singapore, South Korea) = 1,407, Emerging AI Ecosystems(Mexico, Spain, Brazil, India, Indonesia) = 1,006", "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 17:31:42.265+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "09014f85-fa56-4d78-a107-a2b5e620231b", "parentComponentId": null }, { "bbox": { "h": 0.05, "w": 0.15, "x": 0.79, "y": 0.6 }, "kind": "legend", "text": "Advanced AI Ecosystems\nEmerging AI Ecosystems", "attrs": null, "canon": { "kind": { "name": "Legend", "slug": "legend", "status": "active", "canonId": "31361933-3d22-4c70-bbad-0801e9fffc0c", "version": 1, "description": "Color/symbol decoder placed adjacent to a chart or diagram." }, "tool": null, "subkind": null, "framework": null }, "subkind": null, "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 17:31:42.265+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "777e331b-002c-47b6-8abc-2b8f7f46ff67", "parentComponentId": null }, { "bbox": null, "kind": "metric", "text": "ROI calculation metrics: 28%", "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": "2026-04-25 12:20:12+00", "model": "or:google/gemini-3.1-flash-lite-preview", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "019dd952-5644-756a-a84a-d1cdc788e41a", "parentComponentId": null }, { "bbox": { "h": 0.03, "w": 0.5, "x": 0.05, "y": 0.07 }, "kind": "title", "text": "APPENDIX: ADVANCED VS. EMERGING AI ECOSYSTEM MARKETS", "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 17:31:42.265+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "22901bcd-5303-4468-bec6-c8f6cd902b6d", "parentComponentId": null }, { "bbox": { "h": 0.05, "w": 0.4, "x": 0.3, "y": 0.29 }, "kind": "title", "text": "Most Important Metric When Calculating ROI from AI Investments\nAmong ITDMs in Advanced vs. Emerging AI Ecosystem Markets, Showing % Selected", "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 17:31:42.265+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "8d86ddd6-6a90-4c80-9d4f-2e259b79d447", "parentComponentId": null } ], "metrics": [], "tools": [ { "tool": { "name": "Chartjunk Elimination", "slug": "chartjunk-elimination", "status": "active", "bestFor": null, "canonId": "019dd956-b49e-7453-ab01-b60f338eeda1", "version": 1, "bodyDocId": null, "description": "Remove decorative elements that don't convey data: 3D effects, shadows, unnecessary gridlines", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Designer", "layer": "slide", "agents": [ "Designer" ], "matchId": "91ad31c8-2247-40e1-a1a6-99be5ecb3b1b", "evidence": "The slide contains a grouped bar chart with clear labels and a legend, showing a simple and effective visualization of data.", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 0.7, "extraction": { "at": "2026-07-16 22:02:11.267604+00", "model": "or:meta-llama/llama-4-scout", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 45, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "Data-Ink Ratio", "slug": "data-ink-ratio", "status": "active", "bestFor": null, "canonId": "019dd956-afc8-70da-b378-92834d36fde6", "version": 1, "bodyDocId": null, "description": "Maximize data, minimize non-data ink - remove chartjunk and decoration", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Designer", "layer": "slide", "agents": [ "Designer" ], "matchId": "09f11c63-1972-4385-9272-d52534582715", "evidence": "The chart appears to have a high data-ink ratio, with a clear focus on presenting the data.", "pageRefs": null, "priority": "Core", "whenToUse": null, "confidence": 0.7, "extraction": { "at": "2026-07-16 22:02:11.309017+00", "model": "or:meta-llama/llama-4-scout", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 45, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null } ], "frameworks": [], "arcBeats": [ { "to": 77, "arc": { "name": "The Sparkline", "slug": "sparkline", "status": "active", "bestFor": "Keynotes, TED-style talks", "canonId": "019dd956-606e-720c-905a-42607ac0bf50", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "What Is -> What Could Be -> What Is -> What Could Be -> New Bliss", "description": null, "familyLabel": null }, "from": 29, "name": "Evidence", "beatId": "5bb325e2-e460-48c2-ba3f-ded31b7b7818", "matchId": "bf9fcf67-d39d-4c8d-8724-bdd9506a6c64", "beatType": { "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." }, "evidence": "The deck provides extensive data and evidence to support its findings and recommendations.", "position": 4, "isPrimaryArc": true, "parentBeatType": null, "alignedBlockIds": null, "matchConfidence": 0.8 } ], "loops": [], "locked": true }, { "page": 46, "type": "analysis", "title": "Data source: Morning Consult, IBM13 survey.", "function": "analyze_data", "rawType": "appendix_data", "block": null, "metadata": { "slideType": "appendix_data", "slideTypeCanon": { "name": "Appendix data", "slug": "appendix_data", "status": "active", "canonId": "019de52d-078a-745b-9ee4-c15f2f539acd", "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": "dense", "densityScore": 56, "componentCount": 6, "textChars": 653, "nDataPoints": 10, "notes": "Data source: Morning Consult, IBM13 survey.", "elementsJson": [ "bar_chart_grouped" ], "confidence": 1, "extraction": { "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "at": "2026-05-02 17:31:38.302+00", "seconds": 2.749, "promptVersion": "v2-canon-conditioned" } }, "links": { "slide": "/slides/019dd923-5e88-73ef-bd5d-e266bb5de1d1/46", "deck": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1", "deckAnchor": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1#slide-46", "deckJson": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1.json" }, "components": [ { "bbox": { "h": 0.5, "w": 0.4, "x": 0.12, "y": 0.37 }, "kind": "chart", "text": "Grouped bar chart showing 5 categories of AI strategy success indicators comparing Advanced vs Emerging markets.", "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": "Grouped bar chart", "slug": "bar-grouped", "status": "active", "canonId": "019de52c-ff3b-751e-a8ff-f21ff11097b1", "version": 1, "description": null }, "framework": null }, "subkind": "bar-grouped", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 17:31:38.302+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "305fb0f8-b9c8-4096-a829-83f77cefa56e", "parentComponentId": null }, { "bbox": { "h": 0.05, "w": 0.15, "x": 0.79, "y": 0.6 }, "kind": "legend", "text": "Advanced AI Ecosystems\nEmerging AI Ecosystems", "attrs": null, "canon": { "kind": { "name": "Legend", "slug": "legend", "status": "active", "canonId": "31361933-3d22-4c70-bbad-0801e9fffc0c", "version": 1, "description": "Color/symbol decoder placed adjacent to a chart or diagram." }, "tool": null, "subkind": null, "framework": null }, "subkind": null, "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 17:31:38.302+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "6149636a-6fed-4c1a-9cee-7d473229ab8b", "parentComponentId": null }, { "bbox": null, "kind": "metric", "text": "Percentage of ITDMs selecting indicator: 34%", "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": "2026-04-25 12:20:11+00", "model": "or:google/gemini-3.1-flash-lite-preview", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "019dd952-5644-756a-a84a-1a4caf5600c5", "parentComponentId": null }, { "bbox": { "h": 0.04, "w": 0.7, "x": 0.18, "y": 0.935 }, "kind": "paragraph", "text": "IBM13 Which outcome is most important to demonstrate the success of your company's AI strategy?\nSample Size: Advanced AI Ecosystem (US, Canada, UK, France, Germany, Singapore, South Korea) = 1,407, Emerging AI Ecosystems(Mexico, Spain, Brazil, India, Indonesia) = 1,006", "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": null, "framework": null }, "subkind": "source-note", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 17:31:38.302+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "67402803-8f90-4337-a4fb-bb89d9a2aeca", "parentComponentId": null }, { "bbox": { "h": 0.03, "w": 0.5, "x": 0.05, "y": 0.07 }, "kind": "title", "text": "APPENDIX: ADVANCED VS. EMERGING AI ECOSYSTEM MARKETS", "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 17:31:38.302+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "ddcd421a-091d-49dc-ac3f-49fe626ff083", "parentComponentId": null }, { "bbox": { "h": 0.05, "w": 0.4, "x": 0.3, "y": 0.29 }, "kind": "title", "text": "Most Important Indicators of a Successful AI Strategy\nAmong ITDMs in Advanced vs. Emerging AI Ecosystem Markets, Showing % Selected", "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 17:31:38.302+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "4969d74e-0e06-4258-b124-0d86eea8929c", "parentComponentId": null } ], "metrics": [], "tools": [ { "tool": { "name": "Chartjunk Elimination", "slug": "chartjunk-elimination", "status": "active", "bestFor": null, "canonId": "019dd956-b49e-7453-ab01-b60f338eeda1", "version": 1, "bodyDocId": null, "description": "Remove decorative elements that don't convey data: 3D effects, shadows, unnecessary gridlines", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Designer", "layer": "slide", "agents": [ "Designer" ], "matchId": "11fa36a3-1334-4e91-9b5a-ef94c717d562", "evidence": "The slide contains a grouped bar chart with clear labels and a legend, showing a simple and effective visualization of data.", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 0.7, "extraction": { "at": "2026-07-16 22:02:11.390655+00", "model": "or:meta-llama/llama-4-scout", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 46, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "Data-Ink Ratio", "slug": "data-ink-ratio", "status": "active", "bestFor": null, "canonId": "019dd956-afc8-70da-b378-92834d36fde6", "version": 1, "bodyDocId": null, "description": "Maximize data, minimize non-data ink - remove chartjunk and decoration", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Designer", "layer": "slide", "agents": [ "Designer" ], "matchId": "168634ce-84dd-463b-b781-f7304d3b5a61", "evidence": "The chart appears to have a high data-ink ratio, with a clear focus on presenting the data.", "pageRefs": null, "priority": "Core", "whenToUse": null, "confidence": 0.7, "extraction": { "at": "2026-07-16 22:02:11.430524+00", "model": "or:meta-llama/llama-4-scout", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 46, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null } ], "frameworks": [], "arcBeats": [ { "to": 77, "arc": { "name": "The Sparkline", "slug": "sparkline", "status": "active", "bestFor": "Keynotes, TED-style talks", "canonId": "019dd956-606e-720c-905a-42607ac0bf50", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "What Is -> What Could Be -> What Is -> What Could Be -> New Bliss", "description": null, "familyLabel": null }, "from": 29, "name": "Evidence", "beatId": "5bb325e2-e460-48c2-ba3f-ded31b7b7818", "matchId": "bf9fcf67-d39d-4c8d-8724-bdd9506a6c64", "beatType": { "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." }, "evidence": "The deck provides extensive data and evidence to support its findings and recommendations.", "position": 4, "isPrimaryArc": true, "parentBeatType": null, "alignedBlockIds": null, "matchConfidence": 0.8 } ], "loops": [], "locked": true }, { "page": 47, "type": "analysis", "title": "Data source: Morning Consult, IBM14 survey.", "function": "analyze_data", "rawType": "appendix_data", "block": null, "metadata": { "slideType": "appendix_data", "slideTypeCanon": { "name": "Appendix data", "slug": "appendix_data", "status": "active", "canonId": "019de52d-078a-745b-9ee4-c15f2f539acd", "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": "dense", "densityScore": 54, "componentCount": 6, "textChars": 602, "nDataPoints": 8, "notes": "Data source: Morning Consult, IBM14 survey.", "elementsJson": [ "bar_chart_grouped" ], "confidence": 1, "extraction": { "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "at": "2026-05-02 17:31:39.167+00", "seconds": 3.308, "promptVersion": "v2-canon-conditioned" } }, "links": { "slide": "/slides/019dd923-5e88-73ef-bd5d-e266bb5de1d1/47", "deck": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1", "deckAnchor": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1#slide-47", "deckJson": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1.json" }, "components": [ { "bbox": { "h": 0.45, "w": 0.3, "x": 0.35, "y": 0.37 }, "kind": "chart", "text": "Grouped bar chart showing ROI status (Positive, Break-even, Negative, Difficult to measure) for Advanced vs Emerging markets.", "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": "Grouped bar chart", "slug": "bar-grouped", "status": "active", "canonId": "019de52c-ff3b-751e-a8ff-f21ff11097b1", "version": 1, "description": null }, "framework": null }, "subkind": "bar-grouped", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 17:31:39.167+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "d622a5c6-9839-4ff8-92f4-6738f4678ffa", "parentComponentId": null }, { "bbox": { "h": 0.04, "w": 0.7, "x": 0.18, "y": 0.935 }, "kind": "disclaimer", "text": "IBM14 How would you rate ROI from your company's AI investments in 2024? Sample Size: Advanced AI Ecosystem (US, Canada, UK, France, Germany, Singapore, South Korea) = 1,407, Emerging AI Ecosystems(Mexico, Spain, Brazil, India, Indonesia) = 1,006", "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 17:31:39.167+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "3c6d3284-716b-4481-8167-5eaea8fc614e", "parentComponentId": null }, { "bbox": { "h": 0.06, "w": 0.15, "x": 0.79, "y": 0.595 }, "kind": "legend", "text": "Advanced AI Ecosystems\nEmerging AI Ecosystems", "attrs": null, "canon": { "kind": { "name": "Legend", "slug": "legend", "status": "active", "canonId": "31361933-3d22-4c70-bbad-0801e9fffc0c", "version": 1, "description": "Color/symbol decoder placed adjacent to a chart or diagram." }, "tool": null, "subkind": null, "framework": null }, "subkind": null, "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 17:31:39.167+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "f33abcdf-8bc1-4cb0-9e9b-523e83eee5fd", "parentComponentId": null }, { "bbox": null, "kind": "metric", "text": "ROI from AI investments: 54%", "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": "2026-04-25 12:20:11+00", "model": "or:google/gemini-3.1-flash-lite-preview", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "019dd952-5644-756a-a84a-79d344b7b10a", "parentComponentId": null }, { "bbox": { "h": 0.03, "w": 0.5, "x": 0.05, "y": 0.07 }, "kind": "title", "text": "APPENDIX: ADVANCED VS. EMERGING AI ECOSYSTEM MARKETS", "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 17:31:39.167+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "fc911c10-27cc-407a-85fe-50bd0674ec19", "parentComponentId": null }, { "bbox": { "h": 0.05, "w": 0.4, "x": 0.3, "y": 0.29 }, "kind": "title", "text": "ROI From 2024 AI Investments\nAmong ITDMs in Advanced vs. Emerging AI Ecosystem Markets, Showing % Selected", "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 17:31:39.167+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "48dd6c05-92ee-4a6c-96bc-5d3fea6096fa", "parentComponentId": null } ], "metrics": [], "tools": [ { "tool": { "name": "Chartjunk Elimination", "slug": "chartjunk-elimination", "status": "active", "bestFor": null, "canonId": "019dd956-b49e-7453-ab01-b60f338eeda1", "version": 1, "bodyDocId": null, "description": "Remove decorative elements that don't convey data: 3D effects, shadows, unnecessary gridlines", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Designer", "layer": "slide", "agents": [ "Designer" ], "matchId": "bed76c6f-3964-4bfb-a21d-8361f306b00d", "evidence": "The slide contains a grouped bar chart with clear labels and a legend, showing a simple and effective visualization of data.", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 0.7, "extraction": { "at": "2026-07-16 22:02:11.509383+00", "model": "or:meta-llama/llama-4-scout", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 47, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "Data-Ink Ratio", "slug": "data-ink-ratio", "status": "active", "bestFor": null, "canonId": "019dd956-afc8-70da-b378-92834d36fde6", "version": 1, "bodyDocId": null, "description": "Maximize data, minimize non-data ink - remove chartjunk and decoration", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Designer", "layer": "slide", "agents": [ "Designer" ], "matchId": "6a027ac1-dceb-46d7-84ed-253f8c51cdc7", "evidence": "The chart appears to have a high data-ink ratio, with a clear focus on presenting the data.", "pageRefs": null, "priority": "Core", "whenToUse": null, "confidence": 0.7, "extraction": { "at": "2026-07-16 22:02:11.548477+00", "model": "or:meta-llama/llama-4-scout", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 47, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null } ], "frameworks": [], "arcBeats": [ { "to": 77, "arc": { "name": "The Sparkline", "slug": "sparkline", "status": "active", "bestFor": "Keynotes, TED-style talks", "canonId": "019dd956-606e-720c-905a-42607ac0bf50", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "What Is -> What Could Be -> What Is -> What Could Be -> New Bliss", "description": null, "familyLabel": null }, "from": 29, "name": "Evidence", "beatId": "5bb325e2-e460-48c2-ba3f-ded31b7b7818", "matchId": "bf9fcf67-d39d-4c8d-8724-bdd9506a6c64", "beatType": { "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." }, "evidence": "The deck provides extensive data and evidence to support its findings and recommendations.", "position": 4, "isPrimaryArc": true, "parentBeatType": null, "alignedBlockIds": null, "matchConfidence": 0.8 } ], "loops": [], "locked": true }, { "page": 48, "type": "analysis", "title": "Data source: Morning Consult, IBM15 survey.", "function": "analyze_data", "rawType": "appendix_data", "block": null, "metadata": { "slideType": "appendix_data", "slideTypeCanon": { "name": "Appendix data", "slug": "appendix_data", "status": "active", "canonId": "019de52d-078a-745b-9ee4-c15f2f539acd", "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": "dense", "densityScore": 63, "componentCount": 7, "textChars": 598, "nDataPoints": 12, "notes": "Data source: Morning Consult, IBM15 survey.", "elementsJson": [ "headline_text", "bar_chart_grouped", "footnote" ], "confidence": 1, "extraction": { "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "at": "2026-05-02 17:31:38.425+00", "seconds": 2.509, "promptVersion": "v2-canon-conditioned" } }, "links": { "slide": "/slides/019dd923-5e88-73ef-bd5d-e266bb5de1d1/48", "deck": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1", "deckAnchor": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1#slide-48", "deckJson": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1.json" }, "components": [ { "bbox": { "h": 0.45, "w": 0.35, "x": 0.2, "y": 0.38 }, "kind": "chart", "text": "Grouped bar chart showing ROI timelines", "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": "Grouped bar chart", "slug": "bar-grouped", "status": "active", "canonId": "019de52c-ff3b-751e-a8ff-f21ff11097b1", "version": 1, "description": null }, "framework": null }, "subkind": "bar-grouped", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 17:31:38.425+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "459e0c33-c1a1-47a9-b465-b7a7006441d9", "parentComponentId": null }, { "bbox": { "h": 0.05, "w": 0.15, "x": 0.78, "y": 0.6 }, "kind": "legend", "text": "Advanced AI Ecosystems; Emerging AI Ecosystems", "attrs": null, "canon": { "kind": { "name": "Legend", "slug": "legend", "status": "active", "canonId": "31361933-3d22-4c70-bbad-0801e9fffc0c", "version": 1, "description": "Color/symbol decoder placed adjacent to a chart or diagram." }, "tool": null, "subkind": null, "framework": null }, "subkind": null, "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 17:31:38.425+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "118c9b66-bde9-402c-8bc6-864f01513c10", "parentComponentId": null }, { "bbox": null, "kind": "metric", "text": "Expected timeline for positive ROI: 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": "2026-04-25 12:20:11+00", "model": "or:google/gemini-3.1-flash-lite-preview", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "019dd952-5644-756a-a84a-2942fa137e81", "parentComponentId": null }, { "bbox": { "h": 0.03, "w": 0.6, "x": 0.2, "y": 0.32 }, "kind": "paragraph", "text": "Among ITDMs at Companies Not Currently Seeing Positive ROI in Advanced vs. Emerging AI Ecosystem Markets, Showing % Selected", "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 17:31:38.425+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "ef6dfec3-a1ce-491d-9625-c4b36503f1ad", "parentComponentId": null }, { "bbox": { "h": 0.04, "w": 0.9, "x": 0.05, "y": 0.94 }, "kind": "source-note", "text": "IBM15 When do you expect your company will see positive ROI from its AI investments? Sample Size: Advanced AI Ecosystem (US, Canada, UK, France, Germany, Singapore, South Korea) = 704, Emerging AI Ecosystems(Mexico, Spain, Brazil, India, Indonesia) = 428", "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 17:31:38.425+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "7dc4966a-a0e3-4ea8-93ff-6c4177a55bcf", "parentComponentId": null }, { "bbox": { "h": 0.03, "w": 0.5, "x": 0.05, "y": 0.08 }, "kind": "title", "text": "APPENDIX: ADVANCED VS. EMERGING AI ECOSYSTEM MARKETS", "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 17:31:38.425+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "536ac12c-fc93-49c5-aa5a-4acefc4fd95f", "parentComponentId": null }, { "bbox": { "h": 0.03, "w": 0.3, "x": 0.35, "y": 0.29 }, "kind": "title", "text": "Expected Timeline for Achieving Positive ROI", "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 17:31:38.425+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "743f88db-c068-4048-8132-c6369250f379", "parentComponentId": null } ], "metrics": [], "tools": [ { "tool": { "name": "Chartjunk Elimination", "slug": "chartjunk-elimination", "status": "active", "bestFor": null, "canonId": "019dd956-b49e-7453-ab01-b60f338eeda1", "version": 1, "bodyDocId": null, "description": "Remove decorative elements that don't convey data: 3D effects, shadows, unnecessary gridlines", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Designer", "layer": "slide", "agents": [ "Designer" ], "matchId": "22ff21de-b09a-4cfd-81be-7601144b3bc4", "evidence": "The slide contains a grouped bar chart with clear labels and a legend, showing a simple and effective visualization of data.", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 0.7, "extraction": { "at": "2026-07-16 22:02:11.626623+00", "model": "or:meta-llama/llama-4-scout", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 48, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "Data-Ink Ratio", "slug": "data-ink-ratio", "status": "active", "bestFor": null, "canonId": "019dd956-afc8-70da-b378-92834d36fde6", "version": 1, "bodyDocId": null, "description": "Maximize data, minimize non-data ink - remove chartjunk and decoration", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Designer", "layer": "slide", "agents": [ "Designer" ], "matchId": "4841a190-35ee-4d1a-b9c5-5acbf68ad87c", "evidence": "The chart appears to have a high data-ink ratio, with a clear focus on presenting the data.", "pageRefs": null, "priority": "Core", "whenToUse": null, "confidence": 0.7, "extraction": { "at": "2026-07-16 22:02:11.666406+00", "model": "or:meta-llama/llama-4-scout", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 48, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null } ], "frameworks": [], "arcBeats": [ { "to": 77, "arc": { "name": "The Sparkline", "slug": "sparkline", "status": "active", "bestFor": "Keynotes, TED-style talks", "canonId": "019dd956-606e-720c-905a-42607ac0bf50", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "What Is -> What Could Be -> What Is -> What Could Be -> New Bliss", "description": null, "familyLabel": null }, "from": 29, "name": "Evidence", "beatId": "5bb325e2-e460-48c2-ba3f-ded31b7b7818", "matchId": "bf9fcf67-d39d-4c8d-8724-bdd9506a6c64", "beatType": { "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." }, "evidence": "The deck provides extensive data and evidence to support its findings and recommendations.", "position": 4, "isPrimaryArc": true, "parentBeatType": null, "alignedBlockIds": null, "matchConfidence": 0.8 } ], "loops": [], "locked": true }, { "page": 49, "type": "analysis", "title": "Data source: Morning Consult. Sample sizes: Advanced (1,407), Emerging (1,006).", "function": "analyze_data", "rawType": "appendix_data", "block": null, "metadata": { "slideType": "appendix_data", "slideTypeCanon": { "name": "Appendix data", "slug": "appendix_data", "status": "active", "canonId": "019de52d-078a-745b-9ee4-c15f2f539acd", "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": "dense", "densityScore": 58, "componentCount": 6, "textChars": 755, "nDataPoints": 8, "notes": "Data source: Morning Consult. Sample sizes: Advanced (1,407), Emerging (1,006).", "elementsJson": [ "headline_text", "bar_chart_grouped", "footnote" ], "confidence": 1, "extraction": { "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "at": "2026-05-02 17:31:39.477+00", "seconds": 3.56, "promptVersion": "v2-canon-conditioned" } }, "links": { "slide": "/slides/019dd923-5e88-73ef-bd5d-e266bb5de1d1/49", "deck": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1", "deckAnchor": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1#slide-49", "deckJson": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1.json" }, "components": [ { "bbox": { "h": 0.45, "w": 0.35, "x": 0.18, "y": 0.38 }, "kind": "chart", "text": "Grouped bar chart showing factors: Business value/vision, Computing costs, User experience, Employee adoption.", "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": "Grouped bar chart", "slug": "bar-grouped", "status": "active", "canonId": "019de52c-ff3b-751e-a8ff-f21ff11097b1", "version": 1, "description": null }, "framework": null }, "subkind": "bar-grouped", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 17:31:39.477+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "c18db35f-678a-4a53-8fba-6911e871cfc9", "parentComponentId": null }, { "bbox": { "h": 0.05, "w": 0.7, "x": 0.18, "y": 0.93 }, "kind": "disclaimer", "text": "IBM16 What factors do you think most impact the ROI of your company's AI investments? Please rank the top 4 options, with 1 being the most impactful and 4 being the fourth most impactful. Sample Size: Advanced AI Ecosystem (US, Canada, UK, France, Germany, Singapore, South Korea) = 1,407, Emerging AI Ecosystem (Mexico, Spain, Brazil, India, Indonesia) = 1,006", "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 17:31:39.477+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "340c4a65-446c-4cb9-adf8-85852a90a325", "parentComponentId": null }, { "bbox": { "h": 0.06, "w": 0.15, "x": 0.78, "y": 0.6 }, "kind": "legend", "text": "Advanced AI Ecosystems\nEmerging AI Ecosystems", "attrs": null, "canon": { "kind": { "name": "Legend", "slug": "legend", "status": "active", "canonId": "31361933-3d22-4c70-bbad-0801e9fffc0c", "version": 1, "description": "Color/symbol decoder placed adjacent to a chart or diagram." }, "tool": null, "subkind": null, "framework": null }, "subkind": null, "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 17:31:39.477+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "442f2ce6-ae23-435e-9a80-1b78f36e9430", "parentComponentId": null }, { "bbox": null, "kind": "metric", "text": "Most influential factor impacting ROI: 34%", "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": "2026-04-25 12:20:13+00", "model": "or:google/gemini-3.1-flash-lite-preview", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "019dd952-5644-756a-a84a-fa0e3da6235a", "parentComponentId": null }, { "bbox": { "h": 0.03, "w": 0.5, "x": 0.05, "y": 0.07 }, "kind": "title", "text": "APPENDIX: ADVANCED VS. EMERGING AI ECOSYSTEM MARKETS", "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 17:31:39.477+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "970dabbe-ebd3-45c1-95f2-fb515d014a13", "parentComponentId": null }, { "bbox": { "h": 0.05, "w": 0.5, "x": 0.25, "y": 0.29 }, "kind": "title", "text": "Most Influential Factor Impacting the ROI of AI Investments: Rank 1\nAmong ITDMs in Advanced vs. Emerging AI Ecosystem Markets, Showing % Ranked 1", "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 17:31:39.477+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "e3aba79e-99ae-4595-9865-9aa49d04825e", "parentComponentId": null } ], "metrics": [], "tools": [ { "tool": { "name": "Chartjunk Elimination", "slug": "chartjunk-elimination", "status": "active", "bestFor": null, "canonId": "019dd956-b49e-7453-ab01-b60f338eeda1", "version": 1, "bodyDocId": null, "description": "Remove decorative elements that don't convey data: 3D effects, shadows, unnecessary gridlines", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Designer", "layer": "slide", "agents": [ "Designer" ], "matchId": "03d4edd9-984d-4bc9-9746-cc796ab25973", "evidence": "The slide contains a grouped bar chart with clear labels and a legend, showing a simple and effective visualization of data.", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 0.7, "extraction": { "at": "2026-07-16 22:02:11.74549+00", "model": "or:meta-llama/llama-4-scout", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 49, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "Data-Ink Ratio", "slug": "data-ink-ratio", "status": "active", "bestFor": null, "canonId": "019dd956-afc8-70da-b378-92834d36fde6", "version": 1, "bodyDocId": null, "description": "Maximize data, minimize non-data ink - remove chartjunk and decoration", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Designer", "layer": "slide", "agents": [ "Designer" ], "matchId": "bd2607e8-a869-45ea-837a-30712538c6cc", "evidence": "The chart appears to have a high data-ink ratio, with a clear focus on presenting the data.", "pageRefs": null, "priority": "Core", "whenToUse": null, "confidence": 0.7, "extraction": { "at": "2026-07-16 22:02:11.790318+00", "model": "or:meta-llama/llama-4-scout", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 49, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null } ], "frameworks": [], "arcBeats": [ { "to": 77, "arc": { "name": "The Sparkline", "slug": "sparkline", "status": "active", "bestFor": "Keynotes, TED-style talks", "canonId": "019dd956-606e-720c-905a-42607ac0bf50", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "What Is -> What Could Be -> What Is -> What Could Be -> New Bliss", "description": null, "familyLabel": null }, "from": 29, "name": "Evidence", "beatId": "5bb325e2-e460-48c2-ba3f-ded31b7b7818", "matchId": "bf9fcf67-d39d-4c8d-8724-bdd9506a6c64", "beatType": { "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." }, "evidence": "The deck provides extensive data and evidence to support its findings and recommendations.", "position": 4, "isPrimaryArc": true, "parentBeatType": null, "alignedBlockIds": null, "matchConfidence": 0.8 } ], "loops": [], "locked": true }, { "page": 50, "type": "analysis", "title": "Source: Morning Consult. Sample sizes: Advanced (1,407), Emerging (1,006).", "function": "analyze_data", "rawType": "appendix_data", "block": null, "metadata": { "slideType": "appendix_data", "slideTypeCanon": { "name": "Appendix data", "slug": "appendix_data", "status": "active", "canonId": "019de52d-078a-745b-9ee4-c15f2f539acd", "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": "dense", "densityScore": 54, "componentCount": 6, "textChars": 608, "nDataPoints": 8, "notes": "Source: Morning Consult. Sample sizes: Advanced (1,407), Emerging (1,006).", "elementsJson": [ "bar_chart_grouped", "footnote" ], "confidence": 1, "extraction": { "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "at": "2026-05-02 17:31:38.616+00", "seconds": 2.58, "promptVersion": "v2-canon-conditioned" } }, "links": { "slide": "/slides/019dd923-5e88-73ef-bd5d-e266bb5de1d1/50", "deck": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1", "deckAnchor": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1#slide-50", "deckJson": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1.json" }, "components": [ { "bbox": { "h": 0.5, "w": 0.6, "x": 0.15, "y": 0.35 }, "kind": "chart", "text": "Grouped bar chart showing investment plans (Increase, Maintain, Decrease, Reallocate) for Advanced vs Emerging markets.", "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": "Grouped bar chart", "slug": "bar-grouped", "status": "active", "canonId": "019de52c-ff3b-751e-a8ff-f21ff11097b1", "version": 1, "description": null }, "framework": null }, "subkind": "bar-grouped", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 17:31:38.616+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "4fb9b94d-469f-402d-9110-00f5e4b5e0ea", "parentComponentId": null }, { "bbox": { "h": 0.04, "w": 0.7, "x": 0.18, "y": 0.935 }, "kind": "disclaimer", "text": "IBM17 How does your company plan to allocate its AI budget in 2025? My company plans to...\nSample Size: Advanced AI Ecosystem (US, Canada, UK, France, Germany, Singapore, South Korea) = 1,407, Emerging AI Ecosystems(Mexico, Spain, Brazil, India, Indonesia) = 1,006", "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 17:31:38.616+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "fda6260b-4cec-41eb-a75f-edd994a54224", "parentComponentId": null }, { "bbox": { "h": 0.06, "w": 0.15, "x": 0.78, "y": 0.595 }, "kind": "legend", "text": "Advanced AI Ecosystems\nEmerging AI Ecosystems", "attrs": null, "canon": { "kind": { "name": "Legend", "slug": "legend", "status": "active", "canonId": "31361933-3d22-4c70-bbad-0801e9fffc0c", "version": 1, "description": "Color/symbol decoder placed adjacent to a chart or diagram." }, "tool": null, "subkind": null, "framework": null }, "subkind": null, "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 17:31:38.616+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "cee2011a-0a8e-4429-a602-7fbbdf551b7b", "parentComponentId": null }, { "bbox": null, "kind": "metric", "text": "AI budget allocation: 72%", "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": "2026-04-25 12:20:11+00", "model": "or:google/gemini-3.1-flash-lite-preview", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "019dd952-5644-756a-a84a-3f3ed77bfc8b", "parentComponentId": null }, { "bbox": { "h": 0.03, "w": 0.5, "x": 0.05, "y": 0.07 }, "kind": "title", "text": "APPENDIX: ADVANCED VS. EMERGING AI ECOSYSTEM MARKETS", "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 17:31:38.616+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "cae684ea-a0b8-4cb0-b273-012b4805f641", "parentComponentId": null }, { "bbox": { "h": 0.05, "w": 0.4, "x": 0.3, "y": 0.29 }, "kind": "title", "text": "2025 AI Budget Allocation\nAmong ITDMs in Advanced vs. Emerging AI Ecosystem Markets, Showing % Selected", "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 17:31:38.616+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "bdfab6b0-cf60-4a25-bf3e-1a70acb67194", "parentComponentId": null } ], "metrics": [], "tools": [ { "tool": { "name": "Chartjunk Elimination", "slug": "chartjunk-elimination", "status": "active", "bestFor": null, "canonId": "019dd956-b49e-7453-ab01-b60f338eeda1", "version": 1, "bodyDocId": null, "description": "Remove decorative elements that don't convey data: 3D effects, shadows, unnecessary gridlines", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Designer", "layer": "slide", "agents": [ "Designer" ], "matchId": "72ab6d04-a0aa-4f5f-93f8-de1977cefdcf", "evidence": "The slide contains a grouped bar chart with clear labels and a legend, showing a simple and effective visualization of data.", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 0.7, "extraction": { "at": "2026-07-16 22:02:11.901332+00", "model": "or:meta-llama/llama-4-scout", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 50, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "Data-Ink Ratio", "slug": "data-ink-ratio", "status": "active", "bestFor": null, "canonId": "019dd956-afc8-70da-b378-92834d36fde6", "version": 1, "bodyDocId": null, "description": "Maximize data, minimize non-data ink - remove chartjunk and decoration", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Designer", "layer": "slide", "agents": [ "Designer" ], "matchId": "395fb11a-15d4-404b-b7de-bce833b28ddb", "evidence": "The chart appears to have a high data-ink ratio, with a clear focus on presenting the data.", "pageRefs": null, "priority": "Core", "whenToUse": null, "confidence": 0.7, "extraction": { "at": "2026-07-16 22:02:11.941509+00", "model": "or:meta-llama/llama-4-scout", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 50, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null } ], "frameworks": [], "arcBeats": [ { "to": 77, "arc": { "name": "The Sparkline", "slug": "sparkline", "status": "active", "bestFor": "Keynotes, TED-style talks", "canonId": "019dd956-606e-720c-905a-42607ac0bf50", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "What Is -> What Could Be -> What Is -> What Could Be -> New Bliss", "description": null, "familyLabel": null }, "from": 29, "name": "Evidence", "beatId": "5bb325e2-e460-48c2-ba3f-ded31b7b7818", "matchId": "bf9fcf67-d39d-4c8d-8724-bdd9506a6c64", "beatType": { "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." }, "evidence": "The deck provides extensive data and evidence to support its findings and recommendations.", "position": 4, "isPrimaryArc": true, "parentBeatType": null, "alignedBlockIds": null, "matchConfidence": 0.8 } ], "loops": [], "locked": true }, { "page": 51, "type": "analysis", "title": "Data source: Morning Consult. Sample sizes provided in footer.", "function": "analyze_data", "rawType": "appendix_data", "block": null, "metadata": { "slideType": "appendix_data", "slideTypeCanon": { "name": "Appendix data", "slug": "appendix_data", "status": "active", "canonId": "019de52d-078a-745b-9ee4-c15f2f539acd", "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": "dense", "densityScore": 57, "componentCount": 6, "textChars": 632, "nDataPoints": 16, "notes": "Data source: Morning Consult. Sample sizes provided in footer.", "elementsJson": [ "bar_chart_grouped" ], "confidence": 1, "extraction": { "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "at": "2026-05-02 17:31:40.359+00", "seconds": 3.462, "promptVersion": "v2-canon-conditioned" } }, "links": { "slide": "/slides/019dd923-5e88-73ef-bd5d-e266bb5de1d1/51", "deck": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1", "deckAnchor": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1#slide-51", "deckJson": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1.json" }, "components": [ { "bbox": { "h": 0.5, "w": 0.5, "x": 0.2, "y": 0.35 }, "kind": "chart", "text": "Grouped bar chart showing investment areas by market type", "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": "Grouped bar chart", "slug": "bar-grouped", "status": "active", "canonId": "019de52c-ff3b-751e-a8ff-f21ff11097b1", "version": 1, "description": null }, "framework": null }, "subkind": "bar-grouped", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 17:31:40.359+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "b70efc3a-59d1-4301-b344-0d1aad563f0f", "parentComponentId": null }, { "bbox": { "h": 0.05, "w": 0.7, "x": 0.18, "y": 0.93 }, "kind": "disclaimer", "text": "IBM18 In which areas is your company most interested in allocating its AI investments in 2025? Please select up to three options.\nSample Size: Advanced AI Ecosystem (US, Canada, UK, France, Germany, Singapore, South Korea) = 1,407, Emerging AI Ecosystems(Mexico, Spain, Brazil, India, Indonesia) = 1,006", "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 17:31:40.359+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "0d2de09c-51cb-4622-8c48-7919afd326e6", "parentComponentId": null }, { "bbox": { "h": 0.05, "w": 0.15, "x": 0.78, "y": 0.595 }, "kind": "legend", "text": "Advanced AI Ecosystems\nEmerging AI Ecosystems", "attrs": null, "canon": { "kind": { "name": "Legend", "slug": "legend", "status": "active", "canonId": "31361933-3d22-4c70-bbad-0801e9fffc0c", "version": 1, "description": "Color/symbol decoder placed adjacent to a chart or diagram." }, "tool": null, "subkind": null, "framework": null }, "subkind": null, "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 17:31:40.359+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "4f3793c0-2966-4c28-a2a4-5c01ac33e55d", "parentComponentId": null }, { "bbox": null, "kind": "metric", "text": "Percentage of ITDMs selecting investment area: 68%", "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": "2026-04-25 12:20:13+00", "model": "or:google/gemini-3.1-flash-lite-preview", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "019dd952-5644-756a-a84b-1d39312c9969", "parentComponentId": null }, { "bbox": { "h": 0.03, "w": 0.5, "x": 0.05, "y": 0.07 }, "kind": "title", "text": "APPENDIX: ADVANCED VS. EMERGING AI ECOSYSTEM MARKETS", "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 17:31:40.359+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "e68c108f-ac08-4822-b414-b72fc19c5ffc", "parentComponentId": null }, { "bbox": { "h": 0.05, "w": 0.4, "x": 0.3, "y": 0.28 }, "kind": "title", "text": "Top Areas for Allocating AI Investments in 2025\nAmong ITDMs in Advanced vs. Emerging AI Ecosystem Markets, Showing % Selected", "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 17:31:40.359+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "6f3098b6-fa4e-4164-bcbe-f8a48b077637", "parentComponentId": null } ], "metrics": [], "tools": [ { "tool": { "name": "Chartjunk Elimination", "slug": "chartjunk-elimination", "status": "active", "bestFor": null, "canonId": "019dd956-b49e-7453-ab01-b60f338eeda1", "version": 1, "bodyDocId": null, "description": "Remove decorative elements that don't convey data: 3D effects, shadows, unnecessary gridlines", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Designer", "layer": "slide", "agents": [ "Designer" ], "matchId": "df7dba5e-7cd8-49e1-85c2-a5dd6ec03247", "evidence": "The slide contains a grouped bar chart with clear labels and a legend, showing a simple and effective visualization of data.", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 0.7, "extraction": { "at": "2026-07-16 22:02:12.020396+00", "model": "or:meta-llama/llama-4-scout", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 51, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "Data-Ink Ratio", "slug": "data-ink-ratio", "status": "active", "bestFor": null, "canonId": "019dd956-afc8-70da-b378-92834d36fde6", "version": 1, "bodyDocId": null, "description": "Maximize data, minimize non-data ink - remove chartjunk and decoration", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Designer", "layer": "slide", "agents": [ "Designer" ], "matchId": "dd8dba90-21ba-438d-b703-8bfc0d40afe2", "evidence": "The chart appears to have a high data-ink ratio, with a clear focus on presenting the data.", "pageRefs": null, "priority": "Core", "whenToUse": null, "confidence": 0.7, "extraction": { "at": "2026-07-16 22:02:12.060077+00", "model": "or:meta-llama/llama-4-scout", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 51, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null } ], "frameworks": [], "arcBeats": [ { "to": 77, "arc": { "name": "The Sparkline", "slug": "sparkline", "status": "active", "bestFor": "Keynotes, TED-style talks", "canonId": "019dd956-606e-720c-905a-42607ac0bf50", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "What Is -> What Could Be -> What Is -> What Could Be -> New Bliss", "description": null, "familyLabel": null }, "from": 29, "name": "Evidence", "beatId": "5bb325e2-e460-48c2-ba3f-ded31b7b7818", "matchId": "bf9fcf67-d39d-4c8d-8724-bdd9506a6c64", "beatType": { "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." }, "evidence": "The deck provides extensive data and evidence to support its findings and recommendations.", "position": 4, "isPrimaryArc": true, "parentBeatType": null, "alignedBlockIds": null, "matchConfidence": 0.8 } ], "loops": [], "locked": true }, { "page": 52, "type": "analysis", "title": "Data source: Morning Consult. Sample sizes provided in footer.", "function": "analyze_data", "rawType": "appendix_data", "block": null, "metadata": { "slideType": "appendix_data", "slideTypeCanon": { "name": "Appendix data", "slug": "appendix_data", "status": "active", "canonId": "019de52d-078a-745b-9ee4-c15f2f539acd", "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": "dense", "densityScore": 57, "componentCount": 6, "textChars": 642, "nDataPoints": 18, "notes": "Data source: Morning Consult. Sample sizes provided in footer.", "elementsJson": [ "bar_chart_grouped" ], "confidence": 1, "extraction": { "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "at": "2026-05-02 17:31:44.618+00", "seconds": 7.622, "promptVersion": "v2-canon-conditioned" } }, "links": { "slide": "/slides/019dd923-5e88-73ef-bd5d-e266bb5de1d1/52", "deck": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1", "deckAnchor": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1#slide-52", "deckJson": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1.json" }, "components": [ { "bbox": { "h": 0.5, "w": 0.3, "x": 0.25, "y": 0.36 }, "kind": "chart", "text": "Grouped bar chart showing investment reduction areas", "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": "Grouped bar chart", "slug": "bar-grouped", "status": "active", "canonId": "019de52c-ff3b-751e-a8ff-f21ff11097b1", "version": 1, "description": null }, "framework": null }, "subkind": "bar-grouped", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 17:31:44.618+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "ba22e36c-9465-43c9-90c8-08a473f6073a", "parentComponentId": null }, { "bbox": { "h": 0.05, "w": 0.7, "x": 0.18, "y": 0.93 }, "kind": "disclaimer", "text": "IBM19 In which areas is your company most likely to consider reducing its AI investments in 2025? Please select up to three options.\nSample Size: Advanced AI Ecosystem (US, Canada, UK, France, Germany, Singapore, South Korea) = 1,407, Emerging AI Ecosystems(Mexico, Spain, Brazil, India, Indonesia) = 1,006", "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 17:31:44.618+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "e4eccd07-5524-43e9-8ce4-2eeb4fcee0fb", "parentComponentId": null }, { "bbox": { "h": 0.06, "w": 0.15, "x": 0.78, "y": 0.6 }, "kind": "legend", "text": "Advanced AI Ecosystems\nEmerging AI Ecosystems", "attrs": null, "canon": { "kind": { "name": "Legend", "slug": "legend", "status": "active", "canonId": "31361933-3d22-4c70-bbad-0801e9fffc0c", "version": 1, "description": "Color/symbol decoder placed adjacent to a chart or diagram." }, "tool": null, "subkind": null, "framework": null }, "subkind": null, "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 17:31:44.618+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "a29792ea-3d8b-4469-a9b5-63074aaaa0eb", "parentComponentId": null }, { "bbox": null, "kind": "metric", "text": "Percentage of ITDMs likely to reduce AI investment: 37%", "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": "2026-04-25 12:20:11+00", "model": "or:google/gemini-3.1-flash-lite-preview", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "019dd952-5644-756a-a849-ca2236edf9b6", "parentComponentId": null }, { "bbox": { "h": 0.03, "w": 0.5, "x": 0.05, "y": 0.07 }, "kind": "title", "text": "APPENDIX: ADVANCED VS. EMERGING AI ECOSYSTEM MARKETS", "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 17:31:44.618+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "0c6deb24-f795-4561-8ca1-a47c5071c942", "parentComponentId": null }, { "bbox": { "h": 0.05, "w": 0.4, "x": 0.3, "y": 0.29 }, "kind": "title", "text": "Top Areas Likely to See AI Investments Reduced in 2025\nAmong ITDMs in Advanced vs. Emerging AI Ecosystem Markets, Showing % Selected", "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 17:31:44.618+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "934342bb-8347-4dbe-8efa-e315e11c5fe6", "parentComponentId": null } ], "metrics": [], "tools": [ { "tool": { "name": "Chartjunk Elimination", "slug": "chartjunk-elimination", "status": "active", "bestFor": null, "canonId": "019dd956-b49e-7453-ab01-b60f338eeda1", "version": 1, "bodyDocId": null, "description": "Remove decorative elements that don't convey data: 3D effects, shadows, unnecessary gridlines", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Designer", "layer": "slide", "agents": [ "Designer" ], "matchId": "6276ca88-478a-44d2-bee8-86257b7a225d", "evidence": "The slide contains a grouped bar chart with clear labels and a legend, showing a simple and effective visualization of data.", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 0.7, "extraction": { "at": "2026-07-16 22:02:12.139561+00", "model": "or:meta-llama/llama-4-scout", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 52, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "Data-Ink Ratio", "slug": "data-ink-ratio", "status": "active", "bestFor": null, "canonId": "019dd956-afc8-70da-b378-92834d36fde6", "version": 1, "bodyDocId": null, "description": "Maximize data, minimize non-data ink - remove chartjunk and decoration", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Designer", "layer": "slide", "agents": [ "Designer" ], "matchId": "70266368-d518-409b-895b-04e93376f0b4", "evidence": "The chart appears to have a high data-ink ratio, with a clear focus on presenting the data.", "pageRefs": null, "priority": "Core", "whenToUse": null, "confidence": 0.7, "extraction": { "at": "2026-07-16 22:02:12.179674+00", "model": "or:meta-llama/llama-4-scout", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 52, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null } ], "frameworks": [], "arcBeats": [ { "to": 77, "arc": { "name": "The Sparkline", "slug": "sparkline", "status": "active", "bestFor": "Keynotes, TED-style talks", "canonId": "019dd956-606e-720c-905a-42607ac0bf50", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "What Is -> What Could Be -> What Is -> What Could Be -> New Bliss", "description": null, "familyLabel": null }, "from": 29, "name": "Evidence", "beatId": "5bb325e2-e460-48c2-ba3f-ded31b7b7818", "matchId": "bf9fcf67-d39d-4c8d-8724-bdd9506a6c64", "beatType": { "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." }, "evidence": "The deck provides extensive data and evidence to support its findings and recommendations.", "position": 4, "isPrimaryArc": true, "parentBeatType": null, "alignedBlockIds": null, "matchConfidence": 0.8 } ], "loops": [], "locked": true }, { "page": 53, "type": "analysis", "title": "Data source: Morning Consult, IBM20 survey.", "function": "analyze_data", "rawType": "appendix_data", "block": null, "metadata": { "slideType": "appendix_data", "slideTypeCanon": { "name": "Appendix data", "slug": "appendix_data", "status": "active", "canonId": "019de52d-078a-745b-9ee4-c15f2f539acd", "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": "dense", "densityScore": 56, "componentCount": 6, "textChars": 630, "nDataPoints": 10, "notes": "Data source: Morning Consult, IBM20 survey.", "elementsJson": [ "bar_chart_grouped" ], "confidence": 1, "extraction": { "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "at": "2026-05-02 17:31:40.548+00", "seconds": 3.531, "promptVersion": "v2-canon-conditioned" } }, "links": { "slide": "/slides/019dd923-5e88-73ef-bd5d-e266bb5de1d1/53", "deck": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1", "deckAnchor": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1#slide-53", "deckJson": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1.json" }, "components": [ { "bbox": { "h": 0.45, "w": 0.2, "x": 0.35, "y": 0.375 }, "kind": "chart", "text": "Grouped bar chart showing distribution of open-source usage percentages", "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": "Grouped bar chart", "slug": "bar-grouped", "status": "active", "canonId": "019de52c-ff3b-751e-a8ff-f21ff11097b1", "version": 1, "description": null }, "framework": null }, "subkind": "bar-grouped", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 17:31:40.548+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "697ef3b8-9305-4859-bd20-86177111180f", "parentComponentId": null }, { "bbox": { "h": 0.028, "w": 0.695, "x": 0.182, "y": 0.938 }, "kind": "disclaimer", "text": "IBM20 In the next year, what percentage of your AI solutions or platforms will be based on open source?\nSample Size: Advanced AI Ecosystem (US, Canada, UK, France, Germany, Singapore, South Korea) = 1,407, Emerging AI Ecosystems(Mexico, Spain, Brazil, India, Indonesia) = 1,006", "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 17:31:40.548+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "fb80c8bf-5f68-4721-8434-a2ad26247f0b", "parentComponentId": null }, { "bbox": { "h": 0.04, "w": 0.135, "x": 0.795, "y": 0.6 }, "kind": "legend", "text": "Advanced AI Ecosystems\nEmerging AI Ecosystems", "attrs": null, "canon": { "kind": { "name": "Legend", "slug": "legend", "status": "active", "canonId": "31361933-3d22-4c70-bbad-0801e9fffc0c", "version": 1, "description": "Color/symbol decoder placed adjacent to a chart or diagram." }, "tool": null, "subkind": null, "framework": null }, "subkind": null, "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 17:31:40.548+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "69ce2496-b32c-43e5-b966-2918cc1cbe5b", "parentComponentId": null }, { "bbox": null, "kind": "metric", "text": "Percentage of AI solutions based on open-source: 49%", "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": "2026-04-25 12:20:11+00", "model": "or:google/gemini-3.1-flash-lite-preview", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "019dd952-5644-756a-a84a-b3d1a898b47d", "parentComponentId": null }, { "bbox": { "h": 0.022, "w": 0.536, "x": 0.056, "y": 0.078 }, "kind": "title", "text": "APPENDIX: ADVANCED VS. EMERGING AI ECOSYSTEM MARKETS", "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 17:31:40.548+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "a917a3f2-3232-4308-bb39-d256aada25ea", "parentComponentId": null }, { "bbox": { "h": 0.035, "w": 0.35, "x": 0.325, "y": 0.296 }, "kind": "title", "text": "Percentage of AI Solutions Based on Open-Source in 2025\nAmong ITDMs in Advanced vs. Emerging AI Ecosystem Markets, Showing % Selected", "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 17:31:40.548+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "b698bbe2-2b5b-444b-8e94-05519723f0f2", "parentComponentId": null } ], "metrics": [], "tools": [ { "tool": { "name": "Chartjunk Elimination", "slug": "chartjunk-elimination", "status": "active", "bestFor": null, "canonId": "019dd956-b49e-7453-ab01-b60f338eeda1", "version": 1, "bodyDocId": null, "description": "Remove decorative elements that don't convey data: 3D effects, shadows, unnecessary gridlines", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Designer", "layer": "slide", "agents": [ "Designer" ], "matchId": "7241c8cb-e73a-47b1-b6a4-6bb36e74334c", "evidence": "The slide contains a grouped bar chart with clear labels and a legend, showing a simple and effective visualization of data.", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 0.7, "extraction": { "at": "2026-07-16 22:02:12.259275+00", "model": "or:meta-llama/llama-4-scout", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 53, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "Data-Ink Ratio", "slug": "data-ink-ratio", "status": "active", "bestFor": null, "canonId": "019dd956-afc8-70da-b378-92834d36fde6", "version": 1, "bodyDocId": null, "description": "Maximize data, minimize non-data ink - remove chartjunk and decoration", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Designer", "layer": "slide", "agents": [ "Designer" ], "matchId": "e8dcbcdb-b7d8-4fab-bed4-7a425ad133b7", "evidence": "The chart appears to have a high data-ink ratio, with a clear focus on presenting the data.", "pageRefs": null, "priority": "Core", "whenToUse": null, "confidence": 0.7, "extraction": { "at": "2026-07-16 22:02:12.299346+00", "model": "or:meta-llama/llama-4-scout", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 53, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null } ], "frameworks": [], "arcBeats": [ { "to": 77, "arc": { "name": "The Sparkline", "slug": "sparkline", "status": "active", "bestFor": "Keynotes, TED-style talks", "canonId": "019dd956-606e-720c-905a-42607ac0bf50", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "What Is -> What Could Be -> What Is -> What Could Be -> New Bliss", "description": null, "familyLabel": null }, "from": 29, "name": "Evidence", "beatId": "5bb325e2-e460-48c2-ba3f-ded31b7b7818", "matchId": "bf9fcf67-d39d-4c8d-8724-bdd9506a6c64", "beatType": { "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." }, "evidence": "The deck provides extensive data and evidence to support its findings and recommendations.", "position": 4, "isPrimaryArc": true, "parentBeatType": null, "alignedBlockIds": null, "matchConfidence": 0.8 } ], "loops": [], "locked": true }, { "page": 54, "type": "analysis", "title": "Data source: Morning Consult / IBM. Sample sizes provided in footer.", "function": "analyze_data", "rawType": "appendix_data", "block": null, "metadata": { "slideType": "appendix_data", "slideTypeCanon": { "name": "Appendix data", "slug": "appendix_data", "status": "active", "canonId": "019de52d-078a-745b-9ee4-c15f2f539acd", "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": "dense", "densityScore": 54, "componentCount": 6, "textChars": 560, "nDataPoints": 18, "notes": "Data source: Morning Consult / IBM. Sample sizes provided in footer.", "elementsJson": [ "bar_chart_grouped", "footnote" ], "confidence": 1, "extraction": { "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "at": "2026-05-02 17:31:42.654+00", "seconds": 5.5, "promptVersion": "v2-canon-conditioned" } }, "links": { "slide": "/slides/019dd923-5e88-73ef-bd5d-e266bb5de1d1/54", "deck": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1", "deckAnchor": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1#slide-54", "deckJson": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1.json" }, "components": [ { "bbox": { "h": 0.55, "w": 0.6, "x": 0.2, "y": 0.35 }, "kind": "chart", "text": "Strategic changes planned for 2025 by market type", "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": "Grouped bar chart", "slug": "bar-grouped", "status": "active", "canonId": "019de52c-ff3b-751e-a8ff-f21ff11097b1", "version": 1, "description": null }, "framework": null }, "subkind": "bar-grouped", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 17:31:42.654+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "4d597be4-de5d-4146-bc93-ccb85d34c2aa", "parentComponentId": null }, { "bbox": { "h": 0.05, "w": 0.7, "x": 0.18, "y": 0.93 }, "kind": "disclaimer", "text": "IBM21 Which of the following strategic changes, if any, is your company planning for 2025 to optimize AI implementations? Please select all that apply. Sample Size: Advanced AI Ecosystem (US, Canada, UK, France, Germany, Singapore, South Korea) = 1,407, Emerging AI Ecosystems(Mexico, Spain, Brazil, India, Indonesia) = 1,006", "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 17:31:42.654+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "39ae257f-730d-4462-bf33-c6d513290109", "parentComponentId": null }, { "bbox": { "h": 0.05, "w": 0.15, "x": 0.78, "y": 0.595 }, "kind": "legend", "text": "Advanced AI Ecosystems; Emerging AI Ecosystems", "attrs": null, "canon": { "kind": { "name": "Legend", "slug": "legend", "status": "active", "canonId": "31361933-3d22-4c70-bbad-0801e9fffc0c", "version": 1, "description": "Color/symbol decoder placed adjacent to a chart or diagram." }, "tool": null, "subkind": null, "framework": null }, "subkind": null, "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 17:31:42.654+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "92bf01f1-db37-4132-8460-ed4a102ced31", "parentComponentId": null }, { "bbox": null, "kind": "metric", "text": "Percentage of ITDMs: 55%", "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": "2026-04-25 12:20:11+00", "model": "or:google/gemini-3.1-flash-lite-preview", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "019dd952-5644-756a-a84a-645ceeefc7e6", "parentComponentId": null }, { "bbox": { "h": 0.03, "w": 0.5, "x": 0.05, "y": 0.07 }, "kind": "title", "text": "APPENDIX: ADVANCED VS. EMERGING AI ECOSYSTEM MARKETS", "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 17:31:42.654+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "3fb68fed-0f2d-4ebe-8220-31a976d2733d", "parentComponentId": null }, { "bbox": { "h": 0.03, "w": 0.4, "x": 0.3, "y": 0.29 }, "kind": "title", "text": "Strategic Changes to Optimize AI Implementation Planned for 2025", "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 17:31:42.654+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "77af519a-d0ae-4085-a706-d9f3c36da1d6", "parentComponentId": null } ], "metrics": [], "tools": [ { "tool": { "name": "Chartjunk Elimination", "slug": "chartjunk-elimination", "status": "active", "bestFor": null, "canonId": "019dd956-b49e-7453-ab01-b60f338eeda1", "version": 1, "bodyDocId": null, "description": "Remove decorative elements that don't convey data: 3D effects, shadows, unnecessary gridlines", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Designer", "layer": "slide", "agents": [ "Designer" ], "matchId": "a1be1005-2821-4229-9ab7-c8854cacb46d", "evidence": "The slide contains a grouped bar chart with clear labels and a legend, showing a simple and effective visualization of data.", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 0.7, "extraction": { "at": "2026-07-16 22:02:12.379781+00", "model": "or:meta-llama/llama-4-scout", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 54, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "Data-Ink Ratio", "slug": "data-ink-ratio", "status": "active", "bestFor": null, "canonId": "019dd956-afc8-70da-b378-92834d36fde6", "version": 1, "bodyDocId": null, "description": "Maximize data, minimize non-data ink - remove chartjunk and decoration", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Designer", "layer": "slide", "agents": [ "Designer" ], "matchId": "51cbe3e8-fe15-4f37-83af-48464d34e4d8", "evidence": "The chart appears to have a high data-ink ratio, with a clear focus on presenting the data.", "pageRefs": null, "priority": "Core", "whenToUse": null, "confidence": 0.7, "extraction": { "at": "2026-07-16 22:02:12.419511+00", "model": "or:meta-llama/llama-4-scout", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 54, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null } ], "frameworks": [], "arcBeats": [ { "to": 77, "arc": { "name": "The Sparkline", "slug": "sparkline", "status": "active", "bestFor": "Keynotes, TED-style talks", "canonId": "019dd956-606e-720c-905a-42607ac0bf50", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "What Is -> What Could Be -> What Is -> What Could Be -> New Bliss", "description": null, "familyLabel": null }, "from": 29, "name": "Evidence", "beatId": "5bb325e2-e460-48c2-ba3f-ded31b7b7818", "matchId": "bf9fcf67-d39d-4c8d-8724-bdd9506a6c64", "beatType": { "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." }, "evidence": "The deck provides extensive data and evidence to support its findings and recommendations.", "position": 4, "isPrimaryArc": true, "parentBeatType": null, "alignedBlockIds": null, "matchConfidence": 0.8 } ], "loops": [], "locked": true }, { "page": 55, "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": 1, "componentCount": 1, "textChars": 25, "nDataPoints": 0, "notes": null, "elementsJson": [ "headline_text" ], "confidence": 1, "extraction": { "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "at": "2026-05-02 17:31:39.375+00", "seconds": 1.879, "promptVersion": "v2-canon-conditioned" } }, "links": { "slide": "/slides/019dd923-5e88-73ef-bd5d-e266bb5de1d1/55", "deck": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1", "deckAnchor": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1#slide-55", "deckJson": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1.json" }, "components": [ { "bbox": { "h": 0.06, "w": 0.45, "x": 0.07, "y": 0.43 }, "kind": "title", "text": "Appendix: ITDMs by Market", "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 17:31:39.375+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "341ef153-8036-49ba-b1f2-74231eec6f27", "parentComponentId": null } ], "metrics": [], "tools": [], "frameworks": [], "arcBeats": [ { "to": 77, "arc": { "name": "The Sparkline", "slug": "sparkline", "status": "active", "bestFor": "Keynotes, TED-style talks", "canonId": "019dd956-606e-720c-905a-42607ac0bf50", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "What Is -> What Could Be -> What Is -> What Could Be -> New Bliss", "description": null, "familyLabel": null }, "from": 29, "name": "Evidence", "beatId": "5bb325e2-e460-48c2-ba3f-ded31b7b7818", "matchId": "bf9fcf67-d39d-4c8d-8724-bdd9506a6c64", "beatType": { "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." }, "evidence": "The deck provides extensive data and evidence to support its findings and recommendations.", "position": 4, "isPrimaryArc": true, "parentBeatType": null, "alignedBlockIds": null, "matchConfidence": 0.8 } ], "loops": [], "locked": true }, { "page": 56, "type": "analysis", "title": "The table segments ITDMs by their self-reported progress in AI strategy execution across 12 countries/regions.", "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": "balanced", "densityScore": 34, "componentCount": 5, "textChars": 248, "nDataPoints": 60, "notes": "The table segments ITDMs by their self-reported progress in AI strategy execution across 12 countries/regions.", "elementsJson": [ "data_table" ], "confidence": 1, "extraction": { "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "at": "2026-05-02 17:31:43.103+00", "seconds": 5.395, "promptVersion": "v2-canon-conditioned" } }, "links": { "slide": "/slides/019dd923-5e88-73ef-bd5d-e266bb5de1d1/56", "deck": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1", "deckAnchor": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1#slide-56", "deckJson": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1.json" }, "components": [ { "bbox": { "h": 0.02, "w": 0.4, "x": 0.18, "y": 0.93 }, "kind": "disclaimer", "text": "IBM1 Which of the following statements best describes your organization's AI strategy today?", "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 17:31:43.103+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "cae985a6-6585-4c4d-a727-e917a5bfa2cc", "parentComponentId": null }, { "bbox": null, "kind": "metric", "text": "Progress of AI Strategy", "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": "2026-04-25 12:20:11+00", "model": "or:google/gemini-3.1-flash-lite-preview", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "019dd952-5644-756a-a84a-0b5659798e9a", "parentComponentId": null }, { "bbox": { "h": 0.65, "w": 0.96, "x": 0.02, "y": 0.28 }, "kind": "table", "text": "Table containing AI strategy progress percentages by market", "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 17:31:43.103+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "2e6be87a-1b5b-498f-9eee-537b1456835b", "parentComponentId": null }, { "bbox": { "h": 0.03, "w": 0.2, "x": 0.05, "y": 0.07 }, "kind": "title", "text": "ITDMS BY MARKET", "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 17:31:43.103+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "2ee238d8-bcc3-4c00-bd76-f92319bbc2f9", "parentComponentId": null }, { "bbox": { "h": 0.04, "w": 0.2, "x": 0.4, "y": 0.21 }, "kind": "title", "text": "Progress of AI Strategy\nAmong all ITDMs, Showing % Selected", "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 17:31:43.103+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "c0290c35-b51e-4c9b-aaef-88629133e1f5", "parentComponentId": null } ], "metrics": [], "tools": [], "frameworks": [], "arcBeats": [ { "to": 77, "arc": { "name": "The Sparkline", "slug": "sparkline", "status": "active", "bestFor": "Keynotes, TED-style talks", "canonId": "019dd956-606e-720c-905a-42607ac0bf50", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "What Is -> What Could Be -> What Is -> What Could Be -> New Bliss", "description": null, "familyLabel": null }, "from": 29, "name": "Evidence", "beatId": "5bb325e2-e460-48c2-ba3f-ded31b7b7818", "matchId": "bf9fcf67-d39d-4c8d-8724-bdd9506a6c64", "beatType": { "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." }, "evidence": "The deck provides extensive data and evidence to support its findings and recommendations.", "position": 4, "isPrimaryArc": true, "parentBeatType": null, "alignedBlockIds": null, "matchConfidence": 0.8 } ], "loops": [], "locked": true }, { "page": 57, "type": "analysis", "title": "The table displays distribution of AI pilot counts across 13 countries grouped into 4 regions.", "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": "balanced", "densityScore": 39, "componentCount": 5, "textChars": 344, "nDataPoints": 65, "notes": "The table displays distribution of AI pilot counts across 13 countries grouped into 4 regions.", "elementsJson": [ "data_table" ], "confidence": 1, "extraction": { "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "at": "2026-05-02 17:31:40.794+00", "seconds": 2.948, "promptVersion": "v2-canon-conditioned" } }, "links": { "slide": "/slides/019dd923-5e88-73ef-bd5d-e266bb5de1d1/57", "deck": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1", "deckAnchor": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1#slide-57", "deckJson": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1.json" }, "components": [ { "bbox": { "h": 0.02, "w": 0.35, "x": 0.18, "y": 0.94 }, "kind": "disclaimer", "text": "IBM2 By the end of the year, how many AI pilots will your company have started in 2024?", "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 17:31:40.794+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "efe552cb-42bc-449d-afeb-52a0ebfe4e4b", "parentComponentId": null }, { "bbox": null, "kind": "metric", "text": "Number of AI Pilots: 51%", "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": "2026-04-25 12:20:13+00", "model": "or:google/gemini-3.1-flash-lite-preview", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "019dd952-5644-756a-a84a-e85cb672bfe1", "parentComponentId": null }, { "bbox": { "h": 0.55, "w": 0.96, "x": 0.02, "y": 0.37 }, "kind": "table", "text": "Table containing AI pilot counts (None, 1-10, 11-20, 21-30, More than 30) across regions (North America, LatAm, EMEA, APAC) and specific countries.", "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 17:31:40.794+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "13e97923-6145-412b-864b-8d77c03099e1", "parentComponentId": null }, { "bbox": { "h": 0.022, "w": 0.195, "x": 0.056, "y": 0.078 }, "kind": "title", "text": "ITDMS BY MARKET", "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 17:31:40.794+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "d99d6d4d-0b50-4ca0-bf9a-e843c7f717c7", "parentComponentId": null }, { "bbox": { "h": 0.04, "w": 0.21, "x": 0.395, "y": 0.22 }, "kind": "title", "text": "Number of AI Pilots Started in 2024\nAmong all ITDMs, Showing % Selected", "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 17:31:40.794+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "d9cbb8b2-3743-448f-b455-73a98d43c0d3", "parentComponentId": null } ], "metrics": [], "tools": [], "frameworks": [], "arcBeats": [ { "to": 77, "arc": { "name": "The Sparkline", "slug": "sparkline", "status": "active", "bestFor": "Keynotes, TED-style talks", "canonId": "019dd956-606e-720c-905a-42607ac0bf50", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "What Is -> What Could Be -> What Is -> What Could Be -> New Bliss", "description": null, "familyLabel": null }, "from": 29, "name": "Evidence", "beatId": "5bb325e2-e460-48c2-ba3f-ded31b7b7818", "matchId": "bf9fcf67-d39d-4c8d-8724-bdd9506a6c64", "beatType": { "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." }, "evidence": "The deck provides extensive data and evidence to support its findings and recommendations.", "position": 4, "isPrimaryArc": true, "parentBeatType": null, "alignedBlockIds": null, "matchConfidence": 0.8 } ], "loops": [], "locked": true }, { "page": 58, "type": "analysis", "title": "Data represents survey results from IT decision makers (ITDMs) at companies that started AI pilots in 2024.", "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": "balanced", "densityScore": 42, "componentCount": 5, "textChars": 409, "nDataPoints": 120, "notes": "Data represents survey results from IT decision makers (ITDMs) at companies that started AI pilots in 2024.", "elementsJson": [ "data_table" ], "confidence": 1, "extraction": { "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "at": "2026-05-02 17:31:41.13+00", "seconds": 2.929, "promptVersion": "v2-canon-conditioned" } }, "links": { "slide": "/slides/019dd923-5e88-73ef-bd5d-e266bb5de1d1/58", "deck": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1", "deckAnchor": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1#slide-58", "deckJson": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1.json" }, "components": [ { "bbox": null, "kind": "metric", "text": "Percentage of 2024 AI Pilots Fully Launched", "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": "2026-04-25 12:20:13+00", "model": "or:google/gemini-3.1-flash-lite-preview", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "019dd952-5644-756a-a84b-3f24cbf1b385", "parentComponentId": null }, { "bbox": { "h": 0.013, "w": 0.362, "x": 0.183, "y": 0.938 }, "kind": "source-note", "text": "IBM3 What percentage of the AI pilots started in 2024 will have fully launched by the end of the year?", "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 17:31:41.13+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "14247e99-d1c5-44d9-8b1f-093bf186fa10", "parentComponentId": null }, { "bbox": { "h": 0.515, "w": 0.958, "x": 0.021, "y": 0.392 }, "kind": "table", "text": "Table containing percentage distribution of AI pilot launches across 12 regions/countries and 10 percentage brackets.", "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 17:31:41.13+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "5c7259da-18ef-403e-8661-4298bce935d0", "parentComponentId": null }, { "bbox": { "h": 0.022, "w": 0.195, "x": 0.056, "y": 0.078 }, "kind": "title", "text": "ITDMS BY MARKET", "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 17:31:41.13+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "45e5ad0c-9e6a-4505-81af-02dbac170e18", "parentComponentId": null }, { "bbox": { "h": 0.035, "w": 0.354, "x": 0.323, "y": 0.221 }, "kind": "title", "text": "Percentage of 2024 AI Pilots Fully Launched in 2024\nAmong ITDMs at companies that have started AI pilots in 2024, Showing % Selected", "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 17:31:41.13+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "d907de79-e871-4667-aa42-3e789c4738c6", "parentComponentId": null } ], "metrics": [], "tools": [], "frameworks": [], "arcBeats": [ { "to": 77, "arc": { "name": "The Sparkline", "slug": "sparkline", "status": "active", "bestFor": "Keynotes, TED-style talks", "canonId": "019dd956-606e-720c-905a-42607ac0bf50", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "What Is -> What Could Be -> What Is -> What Could Be -> New Bliss", "description": null, "familyLabel": null }, "from": 29, "name": "Evidence", "beatId": "5bb325e2-e460-48c2-ba3f-ded31b7b7818", "matchId": "bf9fcf67-d39d-4c8d-8724-bdd9506a6c64", "beatType": { "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." }, "evidence": "The deck provides extensive data and evidence to support its findings and recommendations.", "position": 4, "isPrimaryArc": true, "parentBeatType": null, "alignedBlockIds": null, "matchConfidence": 0.8 } ], "loops": [], "locked": true }, { "page": 59, "type": "analysis", "title": "The table displays percentages across various time durations (Less than 6 months to More than 2 years) for 13 different regions/countries.", "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": "balanced", "densityScore": 25, "componentCount": 4, "textChars": 174, "nDataPoints": 78, "notes": "The table displays percentages across various time durations (Less than 6 months to More than 2 years) for 13 different regions/countries.", "elementsJson": [ "data_table" ], "confidence": 1, "extraction": { "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "at": "2026-05-02 17:31:43.084+00", "seconds": 4.797, "promptVersion": "v2-canon-conditioned" } }, "links": { "slide": "/slides/019dd923-5e88-73ef-bd5d-e266bb5de1d1/59", "deck": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1", "deckAnchor": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1#slide-59", "deckJson": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1.json" }, "components": [ { "bbox": null, "kind": "metric", "text": "Time to transition from pilot to full production: 48%", "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": "2026-04-25 12:20:13+00", "model": "or:google/gemini-3.1-flash-lite-preview", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "019dd952-5644-756a-a84b-6e2e3825d04e", "parentComponentId": null }, { "bbox": { "h": 0.55, "w": 0.9, "x": 0.05, "y": 0.35 }, "kind": "table", "text": "Table showing transition times by region", "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 17:31:43.084+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "bfe120fb-5786-4a5b-b16d-6c706cb1d46c", "parentComponentId": null }, { "bbox": { "h": 0.03, "w": 0.2, "x": 0.05, "y": 0.07 }, "kind": "title", "text": "ITDMS BY MARKET", "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 17:31:43.084+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "c06f75fd-6730-4ba3-ae35-51582a877301", "parentComponentId": null }, { "bbox": { "h": 0.03, "w": 0.4, "x": 0.3, "y": 0.22 }, "kind": "title", "text": "Average Length of Time to Transition From Pilot to Full 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": "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 17:31:43.084+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "14174469-be58-487f-9147-1d86c4bb3a80", "parentComponentId": null } ], "metrics": [], "tools": [], "frameworks": [], "arcBeats": [ { "to": 77, "arc": { "name": "The Sparkline", "slug": "sparkline", "status": "active", "bestFor": "Keynotes, TED-style talks", "canonId": "019dd956-606e-720c-905a-42607ac0bf50", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "What Is -> What Could Be -> What Is -> What Could Be -> New Bliss", "description": null, "familyLabel": null }, "from": 29, "name": "Evidence", "beatId": "5bb325e2-e460-48c2-ba3f-ded31b7b7818", "matchId": "bf9fcf67-d39d-4c8d-8724-bdd9506a6c64", "beatType": { "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." }, "evidence": "The deck provides extensive data and evidence to support its findings and recommendations.", "position": 4, "isPrimaryArc": true, "parentBeatType": null, "alignedBlockIds": null, "matchConfidence": 0.8 } ], "loops": [], "locked": true }, { "page": 60, "type": "analysis", "title": "Data source: Morning Consult. The table includes 12 specific obstacles/categories across 12 countries/regions plus an 'All ITDMs' column.", "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": "balanced", "densityScore": 44, "componentCount": 5, "textChars": 455, "nDataPoints": 108, "notes": "Data source: Morning Consult. The table includes 12 specific obstacles/categories across 12 countries/regions plus an 'All ITDMs' column.", "elementsJson": [ "data_table" ], "confidence": 1, "extraction": { "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "at": "2026-05-02 17:31:41.896+00", "seconds": 3.499, "promptVersion": "v2-canon-conditioned" } }, "links": { "slide": "/slides/019dd923-5e88-73ef-bd5d-e266bb5de1d1/60", "deck": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1", "deckAnchor": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1#slide-60", "deckJson": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1.json" }, "components": [ { "bbox": null, "kind": "metric", "text": "Percentage of ITDMs reporting specific obstacles: 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": "2026-04-25 12:20:13+00", "model": "or:google/gemini-3.1-flash-lite-preview", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "019dd952-5644-756a-a84b-4ee61f8f3c41", "parentComponentId": null }, { "bbox": { "h": 0.02, "w": 0.64, "x": 0.18, "y": 0.935 }, "kind": "source-note", "text": "IBM5 Which of the following obstacles, if any, has your company encountered when moving AI projects from pilot to full implementation? Please select all that apply.", "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 17:31:41.896+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "cffb63e2-1d00-44f9-b1cc-ffda293c8bd6", "parentComponentId": null }, { "bbox": { "h": 0.02, "w": 0.34, "x": 0.33, "y": 0.245 }, "kind": "subtitle", "text": "Among ITDMs at Companies that have Launched an AI Pilot, Showing % Selected", "attrs": null, "canon": { "kind": { "name": "Subtitle", "slug": "subtitle", "status": "active", "canonId": "82d821ee-2793-42e7-8f16-c6131385a3ce", "version": 1, "description": "Header-zone supporting text near the title (= ex body.description with bbox)." }, "tool": null, "subkind": null, "framework": null }, "subkind": null, "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 17:31:41.896+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "3d014f8d-cbab-4c18-acc4-fc7b51941f2e", "parentComponentId": null }, { "bbox": { "h": 0.6, "w": 0.9, "x": 0.05, "y": 0.3 }, "kind": "table", "text": "Table containing obstacle categories as rows and geographic regions/countries as columns with percentage values.", "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 17:31:41.896+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "71f6c2ce-8c4c-4bc2-8ee8-a60b91d7c77d", "parentComponentId": null }, { "bbox": { "h": 0.03, "w": 0.34, "x": 0.33, "y": 0.22 }, "kind": "title", "text": "Obstacles Faced When Implementing AI Pilot Projects", "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 17:31:41.896+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "3ff0c2c6-6c7b-47f4-8d0e-7ba099cfa46c", "parentComponentId": null } ], "metrics": [], "tools": [], "frameworks": [], "arcBeats": [ { "to": 77, "arc": { "name": "The Sparkline", "slug": "sparkline", "status": "active", "bestFor": "Keynotes, TED-style talks", "canonId": "019dd956-606e-720c-905a-42607ac0bf50", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "What Is -> What Could Be -> What Is -> What Could Be -> New Bliss", "description": null, "familyLabel": null }, "from": 29, "name": "Evidence", "beatId": "5bb325e2-e460-48c2-ba3f-ded31b7b7818", "matchId": "bf9fcf67-d39d-4c8d-8724-bdd9506a6c64", "beatType": { "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." }, "evidence": "The deck provides extensive data and evidence to support its findings and recommendations.", "position": 4, "isPrimaryArc": true, "parentBeatType": null, "alignedBlockIds": null, "matchConfidence": 0.8 } ], "loops": [ { "to": 62, "from": 60, "loop": { "name": "51_voice_of_customer", "slug": "51-voice-of-customer", "status": "active", "bestFor": "Product strategy, customer experience, market research", "canonId": "019dd956-7aaf-750b-950b-af0df38f5266", "version": 1, "bodyDocId": "019df22a-2420-77be-bc41-ded96d08cb21", "structure": "What Customers Say (Verbatim) -> The Pattern Across Voices -> The Insight -> The Response", "description": "Let customer quotes and feedback drive the narrative and validate the insight", "familyLabel": null }, "matchId": "a3d9a36f-4000-4605-982d-a9adbd34243f", "evidence": "The deck presents data on the obstacles faced when implementing AI pilot projects.", "position": 2, "objective": "What are the key obstacles faced when implementing AI pilot projects?", "confidence": 0.6, "extraction": { "at": "2026-07-16 21:24:12.49511+00", "model": "or:meta-llama/llama-4-scout", "runId": null, "seconds": null, "promptVersion": "doc-narrative-v1" } } ], "locked": true }, { "page": 61, "type": "analysis", "title": "Data source: Morning Consult. Sample sizes are provided at the bottom of the table.", "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": "balanced", "densityScore": 35, "componentCount": 5, "textChars": 268, "nDataPoints": 36, "notes": "Data source: Morning Consult. Sample sizes are provided at the bottom of the table.", "elementsJson": [ "data_table" ], "confidence": 1, "extraction": { "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "at": "2026-05-02 17:31:43.682+00", "seconds": 5.067, "promptVersion": "v2-canon-conditioned" } }, "links": { "slide": "/slides/019dd923-5e88-73ef-bd5d-e266bb5de1d1/61", "deck": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1", "deckAnchor": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1#slide-61", "deckJson": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1.json" }, "components": [ { "bbox": null, "kind": "metric", "text": "Percentage of ITDMs: 89%", "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": "2026-04-25 12:20:13+00", "model": "or:google/gemini-3.1-flash-lite-preview", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "019dd952-5644-756a-a84b-0ee285ebf0f4", "parentComponentId": null }, { "bbox": { "h": 0.013, "w": 0.288, "x": 0.182, "y": 0.938 }, "kind": "source-note", "text": "IBM6 Where does your company source your AI tools?", "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 17:31:43.682+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "d4eb5327-04eb-4e07-9523-ceb80769b611", "parentComponentId": null }, { "bbox": { "h": 0.525, "w": 0.958, "x": 0.021, "y": 0.365 }, "kind": "table", "text": "Table containing sourcing percentages for Buy/Lease, Open-source, and In-house development across 12 countries and 4 regions.", "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 17:31:43.682+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "b0ea027b-64c2-4720-ab82-986323b326d0", "parentComponentId": null }, { "bbox": { "h": 0.022, "w": 0.195, "x": 0.056, "y": 0.078 }, "kind": "title", "text": "ITDMS BY MARKET", "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 17:31:43.682+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "00512aff-0835-44f8-be19-eaf261071e48", "parentComponentId": null }, { "bbox": { "h": 0.035, "w": 0.158, "x": 0.421, "y": 0.218 }, "kind": "title", "text": "Source of AI Tools\nAmong all ITDMs, Showing % Selected", "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 17:31:43.682+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "0a239e83-6fdf-4e87-b5a5-128773a2165d", "parentComponentId": null } ], "metrics": [], "tools": [], "frameworks": [], "arcBeats": [ { "to": 77, "arc": { "name": "The Sparkline", "slug": "sparkline", "status": "active", "bestFor": "Keynotes, TED-style talks", "canonId": "019dd956-606e-720c-905a-42607ac0bf50", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "What Is -> What Could Be -> What Is -> What Could Be -> New Bliss", "description": null, "familyLabel": null }, "from": 29, "name": "Evidence", "beatId": "5bb325e2-e460-48c2-ba3f-ded31b7b7818", "matchId": "bf9fcf67-d39d-4c8d-8724-bdd9506a6c64", "beatType": { "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." }, "evidence": "The deck provides extensive data and evidence to support its findings and recommendations.", "position": 4, "isPrimaryArc": true, "parentBeatType": null, "alignedBlockIds": null, "matchConfidence": 0.8 } ], "loops": [ { "to": 62, "from": 60, "loop": { "name": "51_voice_of_customer", "slug": "51-voice-of-customer", "status": "active", "bestFor": "Product strategy, customer experience, market research", "canonId": "019dd956-7aaf-750b-950b-af0df38f5266", "version": 1, "bodyDocId": "019df22a-2420-77be-bc41-ded96d08cb21", "structure": "What Customers Say (Verbatim) -> The Pattern Across Voices -> The Insight -> The Response", "description": "Let customer quotes and feedback drive the narrative and validate the insight", "familyLabel": null }, "matchId": "a3d9a36f-4000-4605-982d-a9adbd34243f", "evidence": "The deck presents data on the obstacles faced when implementing AI pilot projects.", "position": 2, "objective": "What are the key obstacles faced when implementing AI pilot projects?", "confidence": 0.6, "extraction": { "at": "2026-07-16 21:24:12.49511+00", "model": "or:meta-llama/llama-4-scout", "runId": null, "seconds": null, "promptVersion": "doc-narrative-v1" } } ], "locked": true }, { "page": 62, "type": "analysis", "title": "The table includes sample sizes for each country/region at the bottom.", "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": "balanced", "densityScore": 28, "componentCount": 4, "textChars": 242, "nDataPoints": 91, "notes": "The table includes sample sizes for each country/region at the bottom.", "elementsJson": [ "data_table" ], "confidence": 1, "extraction": { "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "at": "2026-05-02 17:31:41.71+00", "seconds": 3.076, "promptVersion": "v2-canon-conditioned" } }, "links": { "slide": "/slides/019dd923-5e88-73ef-bd5d-e266bb5de1d1/62", "deck": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1", "deckAnchor": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1#slide-62", "deckJson": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1.json" }, "components": [ { "bbox": null, "kind": "metric", "text": "Percentage of ITDMs selecting 'Very challenging': 51%", "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": "2026-04-25 12:20:13+00", "model": "or:google/gemini-3.1-flash-lite-preview", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "019dd952-5644-756a-a84b-2c67ae8a59fd", "parentComponentId": null }, { "bbox": { "h": 0.02, "w": 0.35, "x": 0.18, "y": 0.935 }, "kind": "source-note", "text": "IBM7 How challenging are the following obstacles for your company when implementing AI?", "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 17:31:41.71+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "15e392cd-8bcd-4ba2-946c-d4ca245eb464", "parentComponentId": null }, { "bbox": { "h": 0.55, "w": 0.96, "x": 0.02, "y": 0.34 }, "kind": "table", "text": "Table showing challenges (rows) by country/region (columns)", "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 17:31:41.71+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "0420a85d-5fe3-48c5-b228-902aca44ee13", "parentComponentId": null }, { "bbox": { "h": 0.02, "w": 0.28, "x": 0.36, "y": 0.22 }, "kind": "title", "text": "Significant Challenges When Implementing 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 17:31:41.71+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "070f2c42-5501-4336-b885-45b588bc02a6", "parentComponentId": null } ], "metrics": [], "tools": [], "frameworks": [], "arcBeats": [ { "to": 77, "arc": { "name": "The Sparkline", "slug": "sparkline", "status": "active", "bestFor": "Keynotes, TED-style talks", "canonId": "019dd956-606e-720c-905a-42607ac0bf50", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "What Is -> What Could Be -> What Is -> What Could Be -> New Bliss", "description": null, "familyLabel": null }, "from": 29, "name": "Evidence", "beatId": "5bb325e2-e460-48c2-ba3f-ded31b7b7818", "matchId": "bf9fcf67-d39d-4c8d-8724-bdd9506a6c64", "beatType": { "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." }, "evidence": "The deck provides extensive data and evidence to support its findings and recommendations.", "position": 4, "isPrimaryArc": true, "parentBeatType": null, "alignedBlockIds": null, "matchConfidence": 0.8 } ], "loops": [ { "to": 62, "from": 60, "loop": { "name": "51_voice_of_customer", "slug": "51-voice-of-customer", "status": "active", "bestFor": "Product strategy, customer experience, market research", "canonId": "019dd956-7aaf-750b-950b-af0df38f5266", "version": 1, "bodyDocId": "019df22a-2420-77be-bc41-ded96d08cb21", "structure": "What Customers Say (Verbatim) -> The Pattern Across Voices -> The Insight -> The Response", "description": "Let customer quotes and feedback drive the narrative and validate the insight", "familyLabel": null }, "matchId": "a3d9a36f-4000-4605-982d-a9adbd34243f", "evidence": "The deck presents data on the obstacles faced when implementing AI pilot projects.", "position": 2, "objective": "What are the key obstacles faced when implementing AI pilot projects?", "confidence": 0.6, "extraction": { "at": "2026-07-16 21:24:12.49511+00", "model": "or:meta-llama/llama-4-scout", "runId": null, "seconds": null, "promptVersion": "doc-narrative-v1" } } ], "locked": true }, { "page": 63, "type": "analysis", "title": "The table segments data by region (North America, LatAm, EMEA, APAC) and country, with sample sizes provided at the bottom.", "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": "balanced", "densityScore": 36, "componentCount": 5, "textChars": 278, "nDataPoints": 72, "notes": "The table segments data by region (North America, LatAm, EMEA, APAC) and country, with sample sizes provided at the bottom.", "elementsJson": [ "data_table" ], "confidence": 1, "extraction": { "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "at": "2026-05-02 17:31:41.026+00", "seconds": 2.327, "promptVersion": "v2-canon-conditioned" } }, "links": { "slide": "/slides/019dd923-5e88-73ef-bd5d-e266bb5de1d1/63", "deck": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1", "deckAnchor": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1#slide-63", "deckJson": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1.json" }, "components": [ { "bbox": null, "kind": "metric", "text": "Number of AI Pilots", "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": "2026-04-25 12:20:13+00", "model": "or:google/gemini-3.1-flash-lite-preview", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "019dd952-5644-756a-a84b-7eded912b21e", "parentComponentId": null }, { "bbox": { "h": 0.015, "w": 0.27, "x": 0.18, "y": 0.935 }, "kind": "source-note", "text": "IBM8 How many AI pilots does your company have planned for 2025?", "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 17:31:41.026+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "aa6ac97c-7c27-4b15-a704-f87e797b4ec0", "parentComponentId": null }, { "bbox": { "h": 0.55, "w": 0.96, "x": 0.02, "y": 0.35 }, "kind": "table", "text": "Table containing survey results for AI pilot planning across 12 markets and an aggregate 'All ITDMs' column.", "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 17:31:41.026+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "2926bfdd-780e-46c7-b890-7790eb77824c", "parentComponentId": null }, { "bbox": { "h": 0.022, "w": 0.195, "x": 0.056, "y": 0.078 }, "kind": "title", "text": "ITDMS BY MARKET", "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 17:31:41.026+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "2627dc38-767b-4b8a-af52-cc71be010bd3", "parentComponentId": null }, { "bbox": { "h": 0.035, "w": 0.22, "x": 0.39, "y": 0.218 }, "kind": "title", "text": "Number of AI Pilots Planned for 2025\nAmong all ITDMs, Showing % Selected", "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 17:31:41.026+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "0a87643f-13ac-44c6-bccc-213a5d759e4e", "parentComponentId": null } ], "metrics": [], "tools": [], "frameworks": [], "arcBeats": [ { "to": 77, "arc": { "name": "The Sparkline", "slug": "sparkline", "status": "active", "bestFor": "Keynotes, TED-style talks", "canonId": "019dd956-606e-720c-905a-42607ac0bf50", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "What Is -> What Could Be -> What Is -> What Could Be -> New Bliss", "description": null, "familyLabel": null }, "from": 29, "name": "Evidence", "beatId": "5bb325e2-e460-48c2-ba3f-ded31b7b7818", "matchId": "bf9fcf67-d39d-4c8d-8724-bdd9506a6c64", "beatType": { "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." }, "evidence": "The deck provides extensive data and evidence to support its findings and recommendations.", "position": 4, "isPrimaryArc": true, "parentBeatType": null, "alignedBlockIds": null, "matchConfidence": 0.8 } ], "loops": [], "locked": true }, { "page": 64, "type": "analysis", "title": "The table displays distribution percentages across five categories (0% to 75-100%) for 12 countries and an 'All ITDMs' aggregate.", "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": "balanced", "densityScore": 36, "componentCount": 5, "textChars": 288, "nDataPoints": 60, "notes": "The table displays distribution percentages across five categories (0% to 75-100%) for 12 countries and an 'All ITDMs' aggregate.", "elementsJson": [ "data_table" ], "confidence": 1, "extraction": { "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "at": "2026-05-02 17:31:45.308+00", "seconds": 6.514, "promptVersion": "v2-canon-conditioned" } }, "links": { "slide": "/slides/019dd923-5e88-73ef-bd5d-e266bb5de1d1/64", "deck": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1", "deckAnchor": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1#slide-64", "deckJson": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1.json" }, "components": [ { "bbox": { "h": 0.02, "w": 0.4, "x": 0.18, "y": 0.94 }, "kind": "disclaimer", "text": "IBM10 What percentage of your company's current AI solutions or platforms are based on opensource?", "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 17:31:45.308+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "f7d86e9d-7e14-4a83-9070-16484e4ac1f5", "parentComponentId": null }, { "bbox": null, "kind": "metric", "text": "Percentage of AI solutions based on open-source: 46%", "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": "2026-04-25 12:20:13+00", "model": "or:google/gemini-3.1-flash-lite-preview", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "019dd952-5644-756a-a84b-aff9a9c1dc05", "parentComponentId": null }, { "bbox": { "h": 0.6, "w": 0.9, "x": 0.05, "y": 0.3 }, "kind": "table", "text": "Table showing percentage distribution of open-source AI solutions by country", "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 17:31:45.308+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "88e1c32a-41dd-44df-b6f5-67d4961f7d3f", "parentComponentId": null }, { "bbox": { "h": 0.03, "w": 0.2, "x": 0.05, "y": 0.07 }, "kind": "title", "text": "ITDMS BY MARKET", "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 17:31:45.308+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "0fcedcc8-3aa0-4db6-bb96-698fb253100b", "parentComponentId": null }, { "bbox": { "h": 0.03, "w": 0.3, "x": 0.35, "y": 0.22 }, "kind": "title", "text": "Percentage of AI Solutions Based on Open-Source", "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 17:31:45.308+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "f4c5aa3f-f2bd-46ff-bbbd-2dbefd9b4a0b", "parentComponentId": null } ], "metrics": [], "tools": [], "frameworks": [], "arcBeats": [ { "to": 77, "arc": { "name": "The Sparkline", "slug": "sparkline", "status": "active", "bestFor": "Keynotes, TED-style talks", "canonId": "019dd956-606e-720c-905a-42607ac0bf50", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "What Is -> What Could Be -> What Is -> What Could Be -> New Bliss", "description": null, "familyLabel": null }, "from": 29, "name": "Evidence", "beatId": "5bb325e2-e460-48c2-ba3f-ded31b7b7818", "matchId": "bf9fcf67-d39d-4c8d-8724-bdd9506a6c64", "beatType": { "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." }, "evidence": "The deck provides extensive data and evidence to support its findings and recommendations.", "position": 4, "isPrimaryArc": true, "parentBeatType": null, "alignedBlockIds": null, "matchConfidence": 0.8 } ], "loops": [], "locked": true }, { "page": 65, "type": "analysis", "title": "The table segments ITDMs by their primary motivation for AI implementation (innovation vs. ROI) across 12 countries/regions.", "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": "balanced", "densityScore": 37, "componentCount": 5, "textChars": 307, "nDataPoints": 60, "notes": "The table segments ITDMs by their primary motivation for AI implementation (innovation vs. ROI) across 12 countries/regions.", "elementsJson": [ "data_table" ], "confidence": 1, "extraction": { "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "at": "2026-05-02 17:31:41.246+00", "seconds": 2.313, "promptVersion": "v2-canon-conditioned" } }, "links": { "slide": "/slides/019dd923-5e88-73ef-bd5d-e266bb5de1d1/65", "deck": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1", "deckAnchor": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1#slide-65", "deckJson": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1.json" }, "components": [ { "bbox": null, "kind": "metric", "text": "Percentage of ITDMs: 41%", "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": "2026-04-25 12:20:13+00", "model": "or:google/gemini-3.1-flash-lite-preview", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "019dd952-5644-756a-a84b-dd3eaf5e6552", "parentComponentId": null }, { "bbox": { "h": 0.02, "w": 0.3, "x": 0.18, "y": 0.93 }, "kind": "source-note", "text": "IBM11 What is the primary motivation driving AI implementation at your company?", "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 17:31:41.246+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "e9704fda-7f06-4e0e-bb94-4dd7ee4d950d", "parentComponentId": null }, { "bbox": { "h": 0.6, "w": 0.9, "x": 0.05, "y": 0.28 }, "kind": "table", "text": "Table containing percentages of ITDMs categorized by motivation (innovation-driven to ROI-driven) across 12 markets.", "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 17:31:41.246+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "ecad8d84-7ac3-47dc-a3b9-b6d8a9349a33", "parentComponentId": null }, { "bbox": { "h": 0.03, "w": 0.2, "x": 0.05, "y": 0.07 }, "kind": "title", "text": "ITDMS BY MARKET", "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 17:31:41.246+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "01a21045-e8f5-456c-b589-61ecbc1ffabe", "parentComponentId": null }, { "bbox": { "h": 0.05, "w": 0.3, "x": 0.35, "y": 0.21 }, "kind": "title", "text": "Motivations Driving AI Implementation\nAmong all ITDMs, Showing % Selected", "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 17:31:41.246+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "9301a0ce-8582-4995-98c5-a8ef5c9eedb5", "parentComponentId": null } ], "metrics": [], "tools": [], "frameworks": [], "arcBeats": [ { "to": 77, "arc": { "name": "The Sparkline", "slug": "sparkline", "status": "active", "bestFor": "Keynotes, TED-style talks", "canonId": "019dd956-606e-720c-905a-42607ac0bf50", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "What Is -> What Could Be -> What Is -> What Could Be -> New Bliss", "description": null, "familyLabel": null }, "from": 29, "name": "Evidence", "beatId": "5bb325e2-e460-48c2-ba3f-ded31b7b7818", "matchId": "bf9fcf67-d39d-4c8d-8724-bdd9506a6c64", "beatType": { "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." }, "evidence": "The deck provides extensive data and evidence to support its findings and recommendations.", "position": 4, "isPrimaryArc": true, "parentBeatType": null, "alignedBlockIds": null, "matchConfidence": 0.8 } ], "loops": [], "locked": true }, { "page": 66, "type": "analysis", "title": "The table displays percentage responses for various ROI metrics across 12 countries/regions, plus an 'All ITDMs' aggregate.", "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": "balanced", "densityScore": 38, "componentCount": 5, "textChars": 327, "nDataPoints": 88, "notes": "The table displays percentage responses for various ROI metrics across 12 countries/regions, plus an 'All ITDMs' aggregate.", "elementsJson": [ "data_table" ], "confidence": 1, "extraction": { "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "at": "2026-05-02 17:31:41.739+00", "seconds": 2.448, "promptVersion": "v2-canon-conditioned" } }, "links": { "slide": "/slides/019dd923-5e88-73ef-bd5d-e266bb5de1d1/66", "deck": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1", "deckAnchor": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1#slide-66", "deckJson": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1.json" }, "components": [ { "bbox": null, "kind": "metric", "text": "ROI measurement metrics", "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": "2026-04-25 12:20:13+00", "model": "or:google/gemini-3.1-flash-lite-preview", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "019dd952-5644-756a-a84b-5c62dada433a", "parentComponentId": null }, { "bbox": { "h": 0.02, "w": 0.45, "x": 0.18, "y": 0.94 }, "kind": "source-note", "text": "IBM12 How does your company calculate return on investment (ROI) from AI investments? Please select all that apply.", "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 17:31:41.739+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "5c55ea41-3c39-4de7-bd34-e57998bcf83d", "parentComponentId": null }, { "bbox": { "h": 0.6, "w": 0.9, "x": 0.05, "y": 0.3 }, "kind": "table", "text": "Table containing ROI metrics (rows) vs geographic markets (columns) with percentage values.", "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 17:31:41.739+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "0e5551be-8d18-4bcc-99fd-3a4accf3040f", "parentComponentId": null }, { "bbox": { "h": 0.03, "w": 0.2, "x": 0.05, "y": 0.07 }, "kind": "title", "text": "ITDMS BY MARKET", "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 17:31:41.739+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "12ee7f4b-512d-4db2-923e-c681aef9e304", "parentComponentId": null }, { "bbox": { "h": 0.04, "w": 0.3, "x": 0.35, "y": 0.22 }, "kind": "title", "text": "Metrics Used to Measure ROI from AI Investments\nAmong all ITDMs, Showing % Selected", "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 17:31:41.739+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "f8ce6616-448a-434d-a72b-5fe64ef71fbc", "parentComponentId": null } ], "metrics": [], "tools": [], "frameworks": [], "arcBeats": [ { "to": 77, "arc": { "name": "The Sparkline", "slug": "sparkline", "status": "active", "bestFor": "Keynotes, TED-style talks", "canonId": "019dd956-606e-720c-905a-42607ac0bf50", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "What Is -> What Could Be -> What Is -> What Could Be -> New Bliss", "description": null, "familyLabel": null }, "from": 29, "name": "Evidence", "beatId": "5bb325e2-e460-48c2-ba3f-ded31b7b7818", "matchId": "bf9fcf67-d39d-4c8d-8724-bdd9506a6c64", "beatType": { "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." }, "evidence": "The deck provides extensive data and evidence to support its findings and recommendations.", "position": 4, "isPrimaryArc": true, "parentBeatType": null, "alignedBlockIds": null, "matchConfidence": 0.8 } ], "loops": [], "locked": true }, { "page": 67, "type": "analysis", "title": "Data source: Morning Consult. Sample sizes provided at the bottom of the table.", "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": "balanced", "densityScore": 36, "componentCount": 5, "textChars": 288, "nDataPoints": 65, "notes": "Data source: Morning Consult. Sample sizes provided at the bottom of the table.", "elementsJson": [ "data_table" ], "confidence": 1, "extraction": { "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "at": "2026-05-02 17:31:43.303+00", "seconds": 3.811, "promptVersion": "v2-canon-conditioned" } }, "links": { "slide": "/slides/019dd923-5e88-73ef-bd5d-e266bb5de1d1/67", "deck": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1", "deckAnchor": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1#slide-67", "deckJson": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1.json" }, "components": [ { "bbox": { "h": 0.02, "w": 0.5, "x": 0.18, "y": 0.93 }, "kind": "disclaimer", "text": "IBM12a Which of these metrics is most important to your company when measuring ROI from AI investments? (Rebased to Total)", "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 17:31:43.303+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "a27401a0-26cb-42fa-b98c-9b02be9c78f8", "parentComponentId": null }, { "bbox": null, "kind": "metric", "text": "Most Important Metric When Calculating ROI", "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": "2026-04-25 12:20:13+00", "model": "or:google/gemini-3.1-flash-lite-preview", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "019dd952-5644-756a-a84b-bf87ea0cdaf8", "parentComponentId": null }, { "bbox": { "h": 0.6, "w": 0.9, "x": 0.05, "y": 0.3 }, "kind": "table", "text": "Table showing ROI metrics by region and country", "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 17:31:43.303+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "4bc28db8-159d-4f3e-af72-2aa33192295a", "parentComponentId": null }, { "bbox": { "h": 0.03, "w": 0.4, "x": 0.3, "y": 0.21 }, "kind": "title", "text": "Most Important Metric When Calculating ROI 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": "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 17:31:43.303+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "ff762569-2ff3-41a2-9c1a-e1d877b70187", "parentComponentId": null }, { "bbox": { "h": 0.03, "w": 0.2, "x": 0.05, "y": 0.07 }, "kind": "title", "text": "ITDMS BY MARKET", "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 17:31:43.303+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "d7ae3dad-6a99-4deb-829e-4aeb34b7abd0", "parentComponentId": null } ], "metrics": [], "tools": [], "frameworks": [], "arcBeats": [ { "to": 77, "arc": { "name": "The Sparkline", "slug": "sparkline", "status": "active", "bestFor": "Keynotes, TED-style talks", "canonId": "019dd956-606e-720c-905a-42607ac0bf50", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "What Is -> What Could Be -> What Is -> What Could Be -> New Bliss", "description": null, "familyLabel": null }, "from": 29, "name": "Evidence", "beatId": "5bb325e2-e460-48c2-ba3f-ded31b7b7818", "matchId": "bf9fcf67-d39d-4c8d-8724-bdd9506a6c64", "beatType": { "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." }, "evidence": "The deck provides extensive data and evidence to support its findings and recommendations.", "position": 4, "isPrimaryArc": true, "parentBeatType": null, "alignedBlockIds": null, "matchConfidence": 0.8 } ], "loops": [], "locked": true }, { "page": 68, "type": "analysis", "title": "The table includes data for 12 countries across 4 regions, plus an 'All ITDMs' aggregate column.", "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": "balanced", "densityScore": 36, "componentCount": 5, "textChars": 291, "nDataPoints": 65, "notes": "The table includes data for 12 countries across 4 regions, plus an 'All ITDMs' aggregate column.", "elementsJson": [ "data_table" ], "confidence": 1, "extraction": { "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "at": "2026-05-02 17:31:44.685+00", "seconds": 5.151, "promptVersion": "v2-canon-conditioned" } }, "links": { "slide": "/slides/019dd923-5e88-73ef-bd5d-e266bb5de1d1/68", "deck": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1", "deckAnchor": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1#slide-68", "deckJson": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1.json" }, "components": [ { "bbox": null, "kind": "metric", "text": "Percentage of ITDMs selecting indicator: 47%", "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": "2026-04-25 12:20:13+00", "model": "or:google/gemini-3.1-flash-lite-preview", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "019dd952-5644-756a-a84b-9e55581db0d6", "parentComponentId": null }, { "bbox": { "h": 0.013, "w": 0.378, "x": 0.182, "y": 0.938 }, "kind": "source-note", "text": "IBM13 Which outcome is most important to demonstrate the success of your company's AI strategy?", "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 17:31:44.685+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "bcdbf194-9204-4ed1-bfa0-da4298632351", "parentComponentId": null }, { "bbox": { "h": 0.592, "w": 0.958, "x": 0.021, "y": 0.312 }, "kind": "table", "text": "Table showing survey results by region and country for 5 key AI strategy indicators.", "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 17:31:44.685+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "408b17b8-20dd-4052-9b64-ff0c21ed5099", "parentComponentId": null }, { "bbox": { "h": 0.022, "w": 0.316, "x": 0.342, "y": 0.221 }, "kind": "title", "text": "Most Important Indicators of a Successful AI Strategy", "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 17:31:44.685+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "d5020819-32bc-4c59-b85a-92b06888efd5", "parentComponentId": null }, { "bbox": { "h": 0.022, "w": 0.196, "x": 0.056, "y": 0.078 }, "kind": "title", "text": "ITDMS BY MARKET", "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 17:31:44.685+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "d5500976-0bdd-4083-9a4a-9e70197b4382", "parentComponentId": null } ], "metrics": [], "tools": [], "frameworks": [], "arcBeats": [ { "to": 77, "arc": { "name": "The Sparkline", "slug": "sparkline", "status": "active", "bestFor": "Keynotes, TED-style talks", "canonId": "019dd956-606e-720c-905a-42607ac0bf50", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "What Is -> What Could Be -> What Is -> What Could Be -> New Bliss", "description": null, "familyLabel": null }, "from": 29, "name": "Evidence", "beatId": "5bb325e2-e460-48c2-ba3f-ded31b7b7818", "matchId": "bf9fcf67-d39d-4c8d-8724-bdd9506a6c64", "beatType": { "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." }, "evidence": "The deck provides extensive data and evidence to support its findings and recommendations.", "position": 4, "isPrimaryArc": true, "parentBeatType": null, "alignedBlockIds": null, "matchConfidence": 0.8 } ], "loops": [], "locked": true }, { "page": 69, "type": "analysis", "title": "The table displays percentages of ITDMs reporting positive, break-even, or negative ROI, or difficulty measuring ROI, across 12 countries/regions.", "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": "balanced", "densityScore": 33, "componentCount": 5, "textChars": 217, "nDataPoints": 52, "notes": "The table displays percentages of ITDMs reporting positive, break-even, or negative ROI, or difficulty measuring ROI, across 12 countries/regions.", "elementsJson": [ "data_table" ], "confidence": 1, "extraction": { "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "at": "2026-05-02 17:31:42.973+00", "seconds": 3.196, "promptVersion": "v2-canon-conditioned" } }, "links": { "slide": "/slides/019dd923-5e88-73ef-bd5d-e266bb5de1d1/69", "deck": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1", "deckAnchor": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1#slide-69", "deckJson": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1.json" }, "components": [ { "bbox": { "h": 0.014, "w": 0.435, "x": 0.181, "y": 0.938 }, "kind": "disclaimer", "text": "IBM14 How would you rate ROI from your company's AI investments in 2024?", "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 17:31:42.973+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "ad790a47-b532-47e6-bfcb-0020daf41a71", "parentComponentId": null }, { "bbox": null, "kind": "metric", "text": "ROI from AI investments: 47%", "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": "2026-04-25 12:20:13+00", "model": "or:google/gemini-3.1-flash-lite-preview", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "019dd952-5644-756a-a84b-8d7235404980", "parentComponentId": null }, { "bbox": { "h": 0.635, "w": 0.958, "x": 0.021, "y": 0.285 }, "kind": "table", "text": "Table containing ROI metrics by market", "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 17:31:42.973+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "04f586f3-0cb4-4845-8bef-2af664c9738e", "parentComponentId": null }, { "bbox": { "h": 0.022, "w": 0.196, "x": 0.056, "y": 0.078 }, "kind": "title", "text": "ITDMS BY MARKET", "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 17:31:42.973+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "eaf52d0e-9b05-438f-ae01-93b0b34d64dd", "parentComponentId": null }, { "bbox": { "h": 0.035, "w": 0.184, "x": 0.408, "y": 0.218 }, "kind": "title", "text": "ROI From 2024 AI Investments\nAmong all ITDMs, Showing % Selected", "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 17:31:42.973+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "ffdaaffd-9dab-4d11-8dd6-870efa0d414a", "parentComponentId": null } ], "metrics": [], "tools": [], "frameworks": [], "arcBeats": [ { "to": 77, "arc": { "name": "The Sparkline", "slug": "sparkline", "status": "active", "bestFor": "Keynotes, TED-style talks", "canonId": "019dd956-606e-720c-905a-42607ac0bf50", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "What Is -> What Could Be -> What Is -> What Could Be -> New Bliss", "description": null, "familyLabel": null }, "from": 29, "name": "Evidence", "beatId": "5bb325e2-e460-48c2-ba3f-ded31b7b7818", "matchId": "bf9fcf67-d39d-4c8d-8724-bdd9506a6c64", "beatType": { "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." }, "evidence": "The deck provides extensive data and evidence to support its findings and recommendations.", "position": 4, "isPrimaryArc": true, "parentBeatType": null, "alignedBlockIds": null, "matchConfidence": 0.8 } ], "loops": [], "locked": true }, { "page": 70, "type": "analysis", "title": "The table displays percentage distributions of IT decision-makers' expectations for ROI timelines across various countries and regions.", "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": "balanced", "densityScore": 46, "componentCount": 6, "textChars": 325, "nDataPoints": 91, "notes": "The table displays percentage distributions of IT decision-makers' expectations for ROI timelines across various countries and regions.", "elementsJson": [ "data_table" ], "confidence": 1, "extraction": { "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "at": "2026-05-02 17:31:43.422+00", "seconds": 2.76, "promptVersion": "v2-canon-conditioned" } }, "links": { "slide": "/slides/019dd923-5e88-73ef-bd5d-e266bb5de1d1/70", "deck": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1", "deckAnchor": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1#slide-70", "deckJson": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1.json" }, "components": [ { "bbox": null, "kind": "metric", "text": "Expected timeline for positive ROI: 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": "2026-04-25 12:20:17+00", "model": "or:google/gemini-3.1-flash-lite-preview", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "019dd952-5644-756a-a84d-8e8113ca5ea7", "parentComponentId": null }, { "bbox": { "h": 0.02, "w": 0.35, "x": 0.18, "y": 0.935 }, "kind": "source-note", "text": "IBM15 When do you expect your company will see positive ROI from its AI investments?", "attrs": { "numbered": true }, "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 17:31:43.422+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "f7e802eb-8fbc-49a1-91e7-5913a6447057", "parentComponentId": null }, { "bbox": { "h": 0.02, "w": 0.38, "x": 0.31, "y": 0.245 }, "kind": "subtitle", "text": "Among all ITDMs at Companies Not Currently Seeing Positive ROI, Showing % Selected", "attrs": null, "canon": { "kind": { "name": "Subtitle", "slug": "subtitle", "status": "active", "canonId": "82d821ee-2793-42e7-8f16-c6131385a3ce", "version": 1, "description": "Header-zone supporting text near the title (= ex body.description with bbox)." }, "tool": null, "subkind": null, "framework": null }, "subkind": null, "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 17:31:43.422+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "4cd3cb6d-dfd4-45f4-88b8-e8d84c597951", "parentComponentId": null }, { "bbox": { "h": 0.55, "w": 0.9, "x": 0.05, "y": 0.31 }, "kind": "table", "text": "Full table of ROI timeline expectations by region and country", "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 17:31:43.422+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "e70e8385-1b3c-4402-a20d-e2d0bfa8ade9", "parentComponentId": null }, { "bbox": { "h": 0.03, "w": 0.2, "x": 0.05, "y": 0.07 }, "kind": "title", "text": "ITDMS BY MARKET", "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 17:31:43.422+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "22602d3a-4f43-47ee-b004-088c2dc0a6db", "parentComponentId": null }, { "bbox": { "h": 0.02, "w": 0.28, "x": 0.36, "y": 0.22 }, "kind": "title", "text": "Expected Timeline for Achieving Positive ROI", "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 17:31:43.422+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "77f6d308-d485-420e-8326-e374b5d28aff", "parentComponentId": null } ], "metrics": [], "tools": [], "frameworks": [], "arcBeats": [ { "to": 77, "arc": { "name": "The Sparkline", "slug": "sparkline", "status": "active", "bestFor": "Keynotes, TED-style talks", "canonId": "019dd956-606e-720c-905a-42607ac0bf50", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "What Is -> What Could Be -> What Is -> What Could Be -> New Bliss", "description": null, "familyLabel": null }, "from": 29, "name": "Evidence", "beatId": "5bb325e2-e460-48c2-ba3f-ded31b7b7818", "matchId": "bf9fcf67-d39d-4c8d-8724-bdd9506a6c64", "beatType": { "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." }, "evidence": "The deck provides extensive data and evidence to support its findings and recommendations.", "position": 4, "isPrimaryArc": true, "parentBeatType": null, "alignedBlockIds": null, "matchConfidence": 0.8 } ], "loops": [], "locked": true }, { "page": 71, "type": "analysis", "title": "Data source: Morning Consult. The table displays four key factors: Employee adoption, Computing costs, Business value/vision, and User experience.", "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": "balanced", "densityScore": 39, "componentCount": 5, "textChars": 361, "nDataPoints": 48, "notes": "Data source: Morning Consult. The table displays four key factors: Employee adoption, Computing costs, Business value/vision, and User experience.", "elementsJson": [ "data_table" ], "confidence": 1, "extraction": { "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "at": "2026-05-02 17:31:43.36+00", "seconds": 2.506, "promptVersion": "v2-canon-conditioned" } }, "links": { "slide": "/slides/019dd923-5e88-73ef-bd5d-e266bb5de1d1/71", "deck": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1", "deckAnchor": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1#slide-71", "deckJson": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1.json" }, "components": [ { "bbox": { "h": 0.03, "w": 0.65, "x": 0.18, "y": 0.93 }, "kind": "disclaimer", "text": "IBM16 What factors do you think most impact the ROI of your company's AI investments? Please rank the top 4 options, with 1 being the most impactful and 4 being the fourth most impactful.", "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 17:31:43.36+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "712999ab-edec-455a-a8c4-d31179f141c6", "parentComponentId": null }, { "bbox": null, "kind": "metric", "text": "Percentage of ITDMs ranking factor as #1: 40%", "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": "2026-04-25 12:20:13+00", "model": "or:google/gemini-3.1-flash-lite-preview", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "019dd952-5644-756a-a84b-ce80c70846ba", "parentComponentId": null }, { "bbox": { "h": 0.55, "w": 0.9, "x": 0.05, "y": 0.33 }, "kind": "table", "text": "Table showing ROI factors by region and country", "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 17:31:43.36+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "d61b3fd3-7446-47a4-90f1-7933c2f7031a", "parentComponentId": null }, { "bbox": { "h": 0.04, "w": 0.5, "x": 0.25, "y": 0.22 }, "kind": "title", "text": "Most Influential Factor Impacting the ROI of AI Investments: Rank 1", "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 17:31:43.36+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "4262a649-b441-4241-ab88-0b1dc0fcdcec", "parentComponentId": null }, { "bbox": { "h": 0.03, "w": 0.2, "x": 0.05, "y": 0.07 }, "kind": "title", "text": "ITDMS BY MARKET", "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 17:31:43.36+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "f8908185-9569-43db-a21d-ca7aa082a5d9", "parentComponentId": null } ], "metrics": [], "tools": [], "frameworks": [], "arcBeats": [ { "to": 77, "arc": { "name": "The Sparkline", "slug": "sparkline", "status": "active", "bestFor": "Keynotes, TED-style talks", "canonId": "019dd956-606e-720c-905a-42607ac0bf50", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "What Is -> What Could Be -> What Is -> What Could Be -> New Bliss", "description": null, "familyLabel": null }, "from": 29, "name": "Evidence", "beatId": "5bb325e2-e460-48c2-ba3f-ded31b7b7818", "matchId": "bf9fcf67-d39d-4c8d-8724-bdd9506a6c64", "beatType": { "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." }, "evidence": "The deck provides extensive data and evidence to support its findings and recommendations.", "position": 4, "isPrimaryArc": true, "parentBeatType": null, "alignedBlockIds": null, "matchConfidence": 0.8 } ], "loops": [], "locked": true }, { "page": 72, "type": "analysis", "title": "Data source: Morning Consult. Survey question: 'IBM17 How does your company plan to allocate its AI budget in 2025? My company plans to...'", "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": "balanced", "densityScore": 37, "componentCount": 5, "textChars": 316, "nDataPoints": 60, "notes": "Data source: Morning Consult. Survey question: 'IBM17 How does your company plan to allocate its AI budget in 2025? My company plans to...'", "elementsJson": [ "data_table" ], "confidence": 1, "extraction": { "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "at": "2026-05-02 17:31:44.069+00", "seconds": 3.057, "promptVersion": "v2-canon-conditioned" } }, "links": { "slide": "/slides/019dd923-5e88-73ef-bd5d-e266bb5de1d1/72", "deck": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1", "deckAnchor": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1#slide-72", "deckJson": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1.json" }, "components": [ { "bbox": null, "kind": "metric", "text": "AI budget allocation intent: 62%", "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": "2026-04-25 12:20:13+00", "model": "or:google/gemini-3.1-flash-lite-preview", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "019dd952-5644-756a-a84b-ecde242c696c", "parentComponentId": null }, { "bbox": { "h": 0.02, "w": 0.4, "x": 0.18, "y": 0.94 }, "kind": "source-note", "text": "IBM17 How does your company plan to allocate its AI budget in 2025? My company plans to...", "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 17:31:44.069+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "21b0edb2-2c6a-4f39-8092-eb091bd0cf33", "parentComponentId": null }, { "bbox": { "h": 0.55, "w": 0.9, "x": 0.05, "y": 0.33 }, "kind": "table", "text": "Table containing AI investment plans (Increase, Maintain, Decrease, Reallocate, Not sure) across 12 markets and total.", "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 17:31:44.069+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "df1e7fb8-5600-4c97-9a44-cfa2280c49ae", "parentComponentId": null }, { "bbox": { "h": 0.03, "w": 0.2, "x": 0.05, "y": 0.07 }, "kind": "title", "text": "ITDMS BY MARKET", "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 17:31:44.069+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "a1a50a8b-5805-4ee3-b968-104602432a5c", "parentComponentId": null }, { "bbox": { "h": 0.05, "w": 0.2, "x": 0.4, "y": 0.21 }, "kind": "title", "text": "2025 AI Budget Allocation\nAmong all ITDMs, Showing % Selected", "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 17:31:44.069+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "01bb1cb3-1954-417e-80b7-6045c17f94e1", "parentComponentId": null } ], "metrics": [], "tools": [], "frameworks": [], "arcBeats": [ { "to": 77, "arc": { "name": "The Sparkline", "slug": "sparkline", "status": "active", "bestFor": "Keynotes, TED-style talks", "canonId": "019dd956-606e-720c-905a-42607ac0bf50", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "What Is -> What Could Be -> What Is -> What Could Be -> New Bliss", "description": null, "familyLabel": null }, "from": 29, "name": "Evidence", "beatId": "5bb325e2-e460-48c2-ba3f-ded31b7b7818", "matchId": "bf9fcf67-d39d-4c8d-8724-bdd9506a6c64", "beatType": { "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." }, "evidence": "The deck provides extensive data and evidence to support its findings and recommendations.", "position": 4, "isPrimaryArc": true, "parentBeatType": null, "alignedBlockIds": null, "matchConfidence": 0.8 } ], "loops": [], "locked": true }, { "page": 73, "type": "analysis", "title": "The table is segmented by region (North America, LatAm, EMEA, APAC) and country, with 'All ITDMs' as a baseline.", "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": "balanced", "densityScore": 32, "componentCount": 4, "textChars": 331, "nDataPoints": 108, "notes": "The table is segmented by region (North America, LatAm, EMEA, APAC) and country, with 'All ITDMs' as a baseline.", "elementsJson": [ "data_table" ], "confidence": 1, "extraction": { "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "at": "2026-05-02 17:31:44.013+00", "seconds": 2.958, "promptVersion": "v2-canon-conditioned" } }, "links": { "slide": "/slides/019dd923-5e88-73ef-bd5d-e266bb5de1d1/73", "deck": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1", "deckAnchor": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1#slide-73", "deckJson": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1.json" }, "components": [ { "bbox": { "h": 0.02, "w": 0.5, "x": 0.18, "y": 0.935 }, "kind": "disclaimer", "text": "IBM18 In which areas is your company most interested in allocating its AI investments in 2025? Please select up to three options.", "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 17:31:44.013+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "bfedec04-2ebd-4106-9f50-3e69e744dbb8", "parentComponentId": null }, { "bbox": null, "kind": "metric", "text": "Percentage of ITDMs selecting investment area: 83%", "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": "2026-04-25 12:20:16+00", "model": "or:google/gemini-3.1-flash-lite-preview", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "019dd952-5644-756a-a84c-f9c4c63d7ea0", "parentComponentId": null }, { "bbox": { "h": 0.55, "w": 0.9, "x": 0.05, "y": 0.32 }, "kind": "table", "text": "Table containing AI investment allocation percentages by region and country across 8 business categories.", "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 17:31:44.013+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "ee111dcf-1504-4a5e-91e1-1b360cdc2826", "parentComponentId": null }, { "bbox": { "h": 0.03, "w": 0.3, "x": 0.35, "y": 0.215 }, "kind": "title", "text": "Top Areas for Allocating AI Investments in 2025", "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 17:31:44.013+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "e24e578a-2b7d-4b90-97ba-d96078289bda", "parentComponentId": null } ], "metrics": [], "tools": [], "frameworks": [], "arcBeats": [ { "to": 77, "arc": { "name": "The Sparkline", "slug": "sparkline", "status": "active", "bestFor": "Keynotes, TED-style talks", "canonId": "019dd956-606e-720c-905a-42607ac0bf50", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "What Is -> What Could Be -> What Is -> What Could Be -> New Bliss", "description": null, "familyLabel": null }, "from": 29, "name": "Evidence", "beatId": "5bb325e2-e460-48c2-ba3f-ded31b7b7818", "matchId": "bf9fcf67-d39d-4c8d-8724-bdd9506a6c64", "beatType": { "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." }, "evidence": "The deck provides extensive data and evidence to support its findings and recommendations.", "position": 4, "isPrimaryArc": true, "parentBeatType": null, "alignedBlockIds": null, "matchConfidence": 0.8 } ], "loops": [], "locked": true }, { "page": 74, "type": "analysis", "title": "The table segments data by region (North America, LatAm, EMEA, APAC) and specific countries, with 'All ITDMs' as a baseline.", "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": "balanced", "densityScore": 33, "componentCount": 4, "textChars": 347, "nDataPoints": 120, "notes": "The table segments data by region (North America, LatAm, EMEA, APAC) and specific countries, with 'All ITDMs' as a baseline.", "elementsJson": [ "data_table" ], "confidence": 1, "extraction": { "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "at": "2026-05-02 17:31:48.157+00", "seconds": 6.848, "promptVersion": "v2-canon-conditioned" } }, "links": { "slide": "/slides/019dd923-5e88-73ef-bd5d-e266bb5de1d1/74", "deck": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1", "deckAnchor": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1#slide-74", "deckJson": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1.json" }, "components": [ { "bbox": { "h": 0.02, "w": 0.5, "x": 0.18, "y": 0.935 }, "kind": "disclaimer", "text": "IBM19 In which areas is your company most likely to consider reducing its AI investments in 2025? Please select up to three options.", "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 17:31:48.157+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "4f368933-f338-4f1b-802a-af08f234e297", "parentComponentId": null }, { "bbox": null, "kind": "metric", "text": "Percentage of ITDMs selecting area for investment reduction: 61%", "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": "2026-04-25 12:20:14+00", "model": "or:google/gemini-3.1-flash-lite-preview", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "019dd952-5644-756a-a84b-fdfd1d5febb7", "parentComponentId": null }, { "bbox": { "h": 0.55, "w": 0.9, "x": 0.05, "y": 0.32 }, "kind": "table", "text": "Table showing percentage of ITDMs selecting specific areas for AI investment reduction by market.", "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 17:31:48.157+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "756f2cf5-3eb3-4a41-8aa4-fe25b8c8f439", "parentComponentId": null }, { "bbox": { "h": 0.03, "w": 0.34, "x": 0.33, "y": 0.22 }, "kind": "title", "text": "Top Areas Likely to See AI Investments Reduced in 2025", "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 17:31:48.157+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "485b397c-741b-485d-9e93-5d4a433ebeb1", "parentComponentId": null } ], "metrics": [], "tools": [], "frameworks": [], "arcBeats": [ { "to": 77, "arc": { "name": "The Sparkline", "slug": "sparkline", "status": "active", "bestFor": "Keynotes, TED-style talks", "canonId": "019dd956-606e-720c-905a-42607ac0bf50", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "What Is -> What Could Be -> What Is -> What Could Be -> New Bliss", "description": null, "familyLabel": null }, "from": 29, "name": "Evidence", "beatId": "5bb325e2-e460-48c2-ba3f-ded31b7b7818", "matchId": "bf9fcf67-d39d-4c8d-8724-bdd9506a6c64", "beatType": { "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." }, "evidence": "The deck provides extensive data and evidence to support its findings and recommendations.", "position": 4, "isPrimaryArc": true, "parentBeatType": null, "alignedBlockIds": null, "matchConfidence": 0.8 } ], "loops": [], "locked": true }, { "page": 75, "type": "analysis", "title": "The table displays survey results across 12 countries/regions, categorized by the percentage of open-source usage in AI solutions.", "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": "balanced", "densityScore": 37, "componentCount": 5, "textChars": 311, "nDataPoints": 72, "notes": "The table displays survey results across 12 countries/regions, categorized by the percentage of open-source usage in AI solutions.", "elementsJson": [ "data_table" ], "confidence": 1, "extraction": { "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "at": "2026-05-02 17:31:44.878+00", "seconds": 3.483, "promptVersion": "v2-canon-conditioned" } }, "links": { "slide": "/slides/019dd923-5e88-73ef-bd5d-e266bb5de1d1/75", "deck": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1", "deckAnchor": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1#slide-75", "deckJson": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1.json" }, "components": [ { "bbox": null, "kind": "metric", "text": "Percentage of AI solutions based on open-source", "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": "2026-04-25 12:20:15+00", "model": "or:google/gemini-3.1-flash-lite-preview", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "019dd952-5644-756a-a84c-0e80980a74f9", "parentComponentId": null }, { "bbox": { "h": 0.02, "w": 0.4, "x": 0.18, "y": 0.93 }, "kind": "source-note", "text": "IBM20 In the next year, what percentage of your AI solutions or platforms will be based on open source?", "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 17:31:44.878+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "cdb27367-1a56-4b94-a785-ed49f844c5db", "parentComponentId": null }, { "bbox": { "h": 0.55, "w": 0.9, "x": 0.05, "y": 0.35 }, "kind": "table", "text": "Table containing survey data for 12 regions across 6 response categories plus sample sizes.", "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 17:31:44.878+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "7dc11e72-ae80-4df8-8f7e-f00a14d1f676", "parentComponentId": null }, { "bbox": { "h": 0.03, "w": 0.2, "x": 0.05, "y": 0.07 }, "kind": "title", "text": "ITDMS BY MARKET", "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 17:31:44.878+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "a3c825e1-b77f-45e3-8dec-a641c7bd05fe", "parentComponentId": null }, { "bbox": { "h": 0.03, "w": 0.36, "x": 0.32, "y": 0.21 }, "kind": "title", "text": "Percentage of AI Solutions Based on Open-Source in 2025", "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 17:31:44.878+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "db5724f3-a0cc-4df7-9e23-2abf903cbfe4", "parentComponentId": null } ], "metrics": [], "tools": [], "frameworks": [], "arcBeats": [ { "to": 77, "arc": { "name": "The Sparkline", "slug": "sparkline", "status": "active", "bestFor": "Keynotes, TED-style talks", "canonId": "019dd956-606e-720c-905a-42607ac0bf50", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "What Is -> What Could Be -> What Is -> What Could Be -> New Bliss", "description": null, "familyLabel": null }, "from": 29, "name": "Evidence", "beatId": "5bb325e2-e460-48c2-ba3f-ded31b7b7818", "matchId": "bf9fcf67-d39d-4c8d-8724-bdd9506a6c64", "beatType": { "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." }, "evidence": "The deck provides extensive data and evidence to support its findings and recommendations.", "position": 4, "isPrimaryArc": true, "parentBeatType": null, "alignedBlockIds": null, "matchConfidence": 0.8 } ], "loops": [], "locked": true }, { "page": 76, "type": "analysis", "title": "The table includes a 'Sample Sizes' row at the bottom and a source/question disclosure at the footer.", "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": "balanced", "densityScore": 40, "componentCount": 5, "textChars": 353, "nDataPoints": 110, "notes": "The table includes a 'Sample Sizes' row at the bottom and a source/question disclosure at the footer.", "elementsJson": [ "data_table" ], "confidence": 1, "extraction": { "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "at": "2026-05-02 17:31:43.725+00", "seconds": 2.211, "promptVersion": "v2-canon-conditioned" } }, "links": { "slide": "/slides/019dd923-5e88-73ef-bd5d-e266bb5de1d1/76", "deck": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1", "deckAnchor": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1#slide-76", "deckJson": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1.json" }, "components": [ { "bbox": { "h": 0.02, "w": 0.6, "x": 0.18, "y": 0.935 }, "kind": "disclaimer", "text": "IBM21 Which of the following strategic changes, if any, is your company planning for 2025 to optimize AI implementations? Please select all that apply.", "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 17:31:43.725+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "b6a123b6-6aef-401f-975d-f8df554436dc", "parentComponentId": null }, { "bbox": null, "kind": "metric", "text": "Percentage of ITDMs planning strategic changes: 71%", "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": "2026-04-25 12:20:15+00", "model": "or:google/gemini-3.1-flash-lite-preview", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "019dd952-5644-756a-a84c-45a843b26015", "parentComponentId": null }, { "bbox": { "h": 0.5, "w": 0.9, "x": 0.05, "y": 0.35 }, "kind": "table", "text": "Table containing strategic AI implementation plans by region and country", "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 17:31:43.725+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "b1737a56-bd4b-4ec6-8b28-0bee53cefdd4", "parentComponentId": null }, { "bbox": { "h": 0.03, "w": 0.2, "x": 0.05, "y": 0.07 }, "kind": "title", "text": "ITDMS BY MARKET", "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 17:31:43.725+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "287e39ac-99a2-4fbf-a585-f8c56e5ea0f8", "parentComponentId": null }, { "bbox": { "h": 0.04, "w": 0.5, "x": 0.25, "y": 0.22 }, "kind": "title", "text": "Strategic Changes to Optimize AI Implementation Planned for 2025", "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 17:31:43.725+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "66cfb414-9541-4ccb-ac60-1ce5fa3abb4d", "parentComponentId": null } ], "metrics": [], "tools": [], "frameworks": [], "arcBeats": [ { "to": 77, "arc": { "name": "The Sparkline", "slug": "sparkline", "status": "active", "bestFor": "Keynotes, TED-style talks", "canonId": "019dd956-606e-720c-905a-42607ac0bf50", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "What Is -> What Could Be -> What Is -> What Could Be -> New Bliss", "description": null, "familyLabel": null }, "from": 29, "name": "Evidence", "beatId": "5bb325e2-e460-48c2-ba3f-ded31b7b7818", "matchId": "bf9fcf67-d39d-4c8d-8724-bdd9506a6c64", "beatType": { "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." }, "evidence": "The deck provides extensive data and evidence to support its findings and recommendations.", "position": 4, "isPrimaryArc": true, "parentBeatType": null, "alignedBlockIds": null, "matchConfidence": 0.8 } ], "loops": [], "locked": true }, { "page": 77, "type": "setup", "function": "front_matter", "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": 3, "componentCount": 2, "textChars": 59, "nDataPoints": 0, "notes": null, "elementsJson": [ "logo_grid" ], "confidence": 1, "extraction": { "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "at": "2026-05-02 17:31:43.572+00", "seconds": 2.039, "promptVersion": "v2-canon-conditioned" } }, "links": { "slide": "/slides/019dd923-5e88-73ef-bd5d-e266bb5de1d1/77", "deck": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1", "deckAnchor": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1#slide-77", "deckJson": "/decks/019dd923-5e88-73ef-bd5d-e266bb5de1d1.json" }, "components": [ { "bbox": { "h": 0.012, "w": 0.164, "x": 0.418, "y": 0.906 }, "kind": "disclaimer", "text": "© 2024 Morning Consult. All rights reserved.", "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 17:31:43.572+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "2858a9b7-acfb-446c-8427-92fcd16412c4", "parentComponentId": null }, { "bbox": { "h": 0.044, "w": 0.314, "x": 0.343, "y": 0.478 }, "kind": "image", "text": "MORNING CONSULT", "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": "Logo", "slug": "logo", "status": "active", "canonId": "019de52c-fdaf-743d-94c4-d7c6a0e55302", "version": 1, "description": null }, "framework": null }, "subkind": "logo", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 17:31:43.572+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "af03bfb8-f585-48bc-9b6d-5ea7b9997ec3", "parentComponentId": null } ], "metrics": [], "tools": [], "frameworks": [], "arcBeats": [ { "to": 77, "arc": { "name": "The Sparkline", "slug": "sparkline", "status": "active", "bestFor": "Keynotes, TED-style talks", "canonId": "019dd956-606e-720c-905a-42607ac0bf50", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "What Is -> What Could Be -> What Is -> What Could Be -> New Bliss", "description": null, "familyLabel": null }, "from": 29, "name": "Evidence", "beatId": "5bb325e2-e460-48c2-ba3f-ded31b7b7818", "matchId": "bf9fcf67-d39d-4c8d-8724-bdd9506a6c64", "beatType": { "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." }, "evidence": "The deck provides extensive data and evidence to support its findings and recommendations.", "position": 4, "isPrimaryArc": true, "parentBeatType": null, "alignedBlockIds": null, "matchConfidence": 0.8 } ], "loops": [], "locked": true } ], "arcBeats": [ { "from": 1, "to": 4, "label": "Setup", "description": "The deck begins with an introduction to the topic, methodology, and key findings." }, { "from": 6, "to": 12, "label": "Industry Trends", "description": "The deck presents industry trends and data on the current landscape of AI investments and ROI." }, { "from": 20, "to": 21, "label": "Complication", "description": "The deck highlights the challenges of AI implementation, including data quality and availability issues." }, { "from": 23, "to": 26, "label": "Development", "description": "The deck discusses the future of AI investments and plans for 2025." }, { "from": 29, "to": 77, "label": "Evidence", "description": "The deck provides extensive data and evidence to support its findings and recommendations." } ], "loops": [ { "from": 20, "to": 21, "label": "Cost Of Inaction", "description": "What are the consequences of not addressing AI implementation challenges?" }, { "from": 23, "to": 26, "label": "Why Now", "description": "Why is now the right time to invest in AI?" }, { "from": 60, "to": 62, "label": "Voice Of Customer", "description": "What are the key obstacles faced when implementing AI pilot projects?" } ] }