{
  "schemaVersion": "deck-intelligence.v1",
  "id": "019dd923-5e88-73ef-bd59-b7c870c8c8e8",
  "slug": "aa4f8ee42fe96cf8",
  "title": "Effects of GenAI on the German labor market",
  "subtitle": "EY Parthenon",
  "author": "EY Parthenon",
  "pageCount": 16,
  "kind": "consulting-deck",
  "orientation": "portrait",
  "aspectRatio": 0.773,
  "document": {
    "id": "019dd923-5e88-73ef-bd59-b7c870c8c8e8",
    "slug": "aa4f8ee42fe96cf8",
    "title": "Effects of GenAI on the German labor market",
    "rawTitle": "Effects of GenAI on the German labor market",
    "authorId": "McKinsey",
    "authorName": "EY Parthenon",
    "authorDisplay": "EY Parthenon",
    "kind": {
      "slug": "consulting-deck",
      "label": "Consulting deck"
    },
    "sourceType": {
      "slug": "strategy_consulting",
      "label": "Strategy consulting"
    },
    "fileName": "en_mckinsey_genai_implications_germany_labor_market.pdf",
    "sourceUrl": "https://www.mckinsey.com/de/~/media/mckinsey/locations/europe%20and%20middle%20east/deutschland/news/presse/2023/2023-11-24%20genai%20implikationen%20deutschlands%20arbeitsmarkt/en_mckinsey_genai_implications_germany_labor_market.pdf",
    "sourceDate": null,
    "presentationDate": null,
    "ingestedAt": "2026-04-24 14:50:29+00",
    "status": "ready",
    "pageCount": 16,
    "orientation": "portrait",
    "aspectRatio": 0.773,
    "targetCompany": null,
    "targetTicker": null,
    "metadata": {
      "local_root": "/tmp/legacy-images/aa4f8ee42fe96cf8",
      "origin_corpus": "consulting"
    }
  },
  "coverage": {
    "pageCount": 16,
    "pagesIndexed": 16,
    "pagesWithImages": 16,
    "pagesWithMetadata": 16,
    "imageCoveragePct": 100,
    "metadataCoveragePct": 100,
    "componentCount": 112,
    "chartCount": 8,
    "metricSlides": 0,
    "toolMatches": 18,
    "documentToolMatches": 0,
    "frameworkMatches": 2,
    "arcMatches": 1,
    "beatMatches": 4,
    "loopMatches": 2,
    "patternMatches": 0,
    "storymakersMatch": false,
    "scoreAvailable": true,
    "reviewAvailable": true,
    "activistThesisAvailable": false,
    "pitchdeckMetadataAvailable": false,
    "pitchdeckProfileAvailable": false
  },
  "blocks": [],
  "matches": {
    "arcs": [
      {
        "arc": {
          "name": "The Consultant's Gambit",
          "slug": "consultants-gambit",
          "status": "active",
          "bestFor": "Business cases, project proposals, strategic recommendations",
          "canonId": "019dd956-5e0a-73c8-b305-81c38c959e9c",
          "version": 1,
          "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49",
          "structure": "Situation & Context -> Problem & Complication -> Solution & Approach -> Evidence & Proof -> Impact & Next Steps",
          "description": null,
          "familyLabel": null,
          "categoryName": "Strategy & Business",
          "categorySlug": "strategy-business"
        },
        "matchId": "424d33e4-517f-4ec9-b9d0-2d8a129b071e",
        "evidence": "The deck follows a logical structure, starting with an executive summary and key takeaways, followed by data tables and scenario analysis",
        "isPrimary": true,
        "confidence": 0.8,
        "extraction": {
          "at": "2026-07-16 21:19:48.359473+00",
          "model": "or:meta-llama/llama-4-scout",
          "runId": null,
          "seconds": null,
          "promptVersion": "doc-narrative-v1"
        }
      }
    ],
    "beats": [
      {
        "to": 2,
        "arc": {
          "name": "The Consultant's Gambit",
          "slug": "consultants-gambit",
          "status": "active",
          "bestFor": "Business cases, project proposals, strategic recommendations",
          "canonId": "019dd956-5e0a-73c8-b305-81c38c959e9c",
          "version": 1,
          "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49",
          "structure": "Situation & Context -> Problem & Complication -> Solution & Approach -> Evidence & Proof -> Impact & Next Steps",
          "description": null,
          "familyLabel": null,
          "categoryName": "Strategy & Business",
          "categorySlug": "strategy-business"
        },
        "from": 1,
        "name": "Situation & Context",
        "beatId": "fb4a4551-e3d0-4a4d-ba42-a20d89d7443a",
        "matchId": "424d33e4-517f-4ec9-b9d0-2d8a129b071e",
        "beatType": {
          "name": "Situation & Context",
          "slug": "consultants-gambit-situation-context",
          "status": "active",
          "canonId": "019dd9b8-05ae-741b-992d-65ee83c639b3",
          "version": 1,
          "description": null
        },
        "evidence": "The cover and executive summary provide an overview of the topic",
        "position": 0,
        "isPrimaryArc": true,
        "parentBeatType": {
          "name": "Setup",
          "slug": "setup",
          "status": "active",
          "canonId": "019dd9b8-020e-7505-af9b-d9b9a4679bcc",
          "version": 1,
          "description": "Where the deck grounds the reader before doing anything else. Almost every arc opens here."
        },
        "alignedBlockIds": null,
        "matchConfidence": 0.8
      },
      {
        "to": 5,
        "arc": {
          "name": "The Consultant's Gambit",
          "slug": "consultants-gambit",
          "status": "active",
          "bestFor": "Business cases, project proposals, strategic recommendations",
          "canonId": "019dd956-5e0a-73c8-b305-81c38c959e9c",
          "version": 1,
          "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49",
          "structure": "Situation & Context -> Problem & Complication -> Solution & Approach -> Evidence & Proof -> Impact & Next Steps",
          "description": null,
          "familyLabel": null,
          "categoryName": "Strategy & Business",
          "categorySlug": "strategy-business"
        },
        "from": 3,
        "name": "Problem & Complication",
        "beatId": "55069988-7d18-4303-b0f8-10d40c6fef58",
        "matchId": "424d33e4-517f-4ec9-b9d0-2d8a129b071e",
        "beatType": {
          "name": "Problem & Complication",
          "slug": "consultants-gambit-problem-complication",
          "status": "active",
          "canonId": "019dd9b8-064a-777f-a374-e9a8c43dedd4",
          "version": 1,
          "description": null
        },
        "evidence": "The key takeaways and data tables highlight the complex effects of GenAI on the labor market",
        "position": 1,
        "isPrimaryArc": true,
        "parentBeatType": {
          "name": "Complication",
          "slug": "complication",
          "status": "active",
          "canonId": "019dd9b8-0275-7709-b2d6-4f77c3fc7579",
          "version": 1,
          "description": "The point in the narrative where the audience should feel discomfort. Required for argumentative arcs."
        },
        "alignedBlockIds": null,
        "matchConfidence": 0.8
      },
      {
        "to": 10,
        "arc": {
          "name": "The Consultant's Gambit",
          "slug": "consultants-gambit",
          "status": "active",
          "bestFor": "Business cases, project proposals, strategic recommendations",
          "canonId": "019dd956-5e0a-73c8-b305-81c38c959e9c",
          "version": 1,
          "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49",
          "structure": "Situation & Context -> Problem & Complication -> Solution & Approach -> Evidence & Proof -> Impact & Next Steps",
          "description": null,
          "familyLabel": null,
          "categoryName": "Strategy & Business",
          "categorySlug": "strategy-business"
        },
        "from": 6,
        "name": "Evidence & Proof",
        "beatId": "50595e69-1a4c-4b7a-9db4-2a10a64a59c8",
        "matchId": "424d33e4-517f-4ec9-b9d0-2d8a129b071e",
        "beatType": {
          "name": "Evidence & Proof",
          "slug": "consultants-gambit-evidence-proof",
          "status": "active",
          "canonId": "019dd9b8-07b1-7688-8e1e-7637fec3802a",
          "version": 1,
          "description": null
        },
        "evidence": "The data tables and industry trends provide evidence of GenAI's impact on various sectors",
        "position": 2,
        "isPrimaryArc": true,
        "parentBeatType": {
          "name": "Evidence",
          "slug": "evidence",
          "status": "active",
          "canonId": "019dd9b8-03f9-772a-b84a-4f07b415b77a",
          "version": 1,
          "description": "A dedicated proof beat exists in only ~4 arcs (Gambit, Sequoia, AIDA, Monroes). Other arcs embed evidence inline within development."
        },
        "alignedBlockIds": null,
        "matchConfidence": 0.8
      },
      {
        "to": 15,
        "arc": {
          "name": "The Consultant's Gambit",
          "slug": "consultants-gambit",
          "status": "active",
          "bestFor": "Business cases, project proposals, strategic recommendations",
          "canonId": "019dd956-5e0a-73c8-b305-81c38c959e9c",
          "version": 1,
          "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49",
          "structure": "Situation & Context -> Problem & Complication -> Solution & Approach -> Evidence & Proof -> Impact & Next Steps",
          "description": null,
          "familyLabel": null,
          "categoryName": "Strategy & Business",
          "categorySlug": "strategy-business"
        },
        "from": 14,
        "name": "Impact & Next Steps",
        "beatId": "9b3c4797-5730-4279-a276-4e3a6b90e40b",
        "matchId": "424d33e4-517f-4ec9-b9d0-2d8a129b071e",
        "beatType": {
          "name": "Impact & Next Steps",
          "slug": "consultants-gambit-impact-next-steps",
          "status": "active",
          "canonId": "019dd9b8-0849-7728-9ee9-fd1609c4c655",
          "version": 1,
          "description": null
        },
        "evidence": "The business implications and recommendation provide guidance for businesses",
        "position": 3,
        "isPrimaryArc": true,
        "parentBeatType": {
          "name": "Resolution",
          "slug": "resolution",
          "status": "active",
          "canonId": "019dd9b8-045d-703b-8dd7-e92aba3ba91b",
          "version": 1,
          "description": "How the deck ends. Required in 19/20 arcs. The exception (Sparkline) ends with new bliss which is functionally a resolution."
        },
        "alignedBlockIds": null,
        "matchConfidence": 0.8
      }
    ],
    "loops": [
      {
        "to": 5,
        "from": 3,
        "loop": {
          "name": "01_logic_chain",
          "slug": "01-logic-chain",
          "status": "active",
          "bestFor": "Skeptical audiences, controversial recommendations, rigorous analysis",
          "canonId": "019dd956-6638-7457-8650-9b0b42e59fb3",
          "version": 1,
          "bodyDocId": "019df22a-2420-77be-bc41-ded96d08cb21",
          "structure": "Premise 1 (Accepted truth) -> Premise 2 (Observed fact) -> Therefore... (Inevitable conclusion)",
          "description": "Build an airtight chain of logic where each premise leads inevitably to the conclusion",
          "familyLabel": null,
          "categoryName": "Logical Reasoning",
          "categorySlug": "logical-reasoning"
        },
        "matchId": "1679a32c-e543-4087-8767-8a695c8716c4",
        "evidence": "The key takeaways and data tables provide a logical chain of information",
        "position": 0,
        "objective": "What are the key findings of GenAI's potential impact on the labor market?",
        "confidence": 0.7,
        "extraction": {
          "at": "2026-07-16 21:19:48.518043+00",
          "model": "or:meta-llama/llama-4-scout",
          "runId": null,
          "seconds": null,
          "promptVersion": "doc-narrative-v1"
        }
      },
      {
        "to": 15,
        "from": 14,
        "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": "673cd046-6dde-4d2b-a046-feb6d0c92238",
        "evidence": "The business implications and recommendation highlight the importance of adapting to GenAI",
        "position": 1,
        "objective": "What are the business implications of not adapting to GenAI?",
        "confidence": 0.6,
        "extraction": {
          "at": "2026-07-16 21:19:48.55105+00",
          "model": "or:meta-llama/llama-4-scout",
          "runId": null,
          "seconds": null,
          "promptVersion": "doc-narrative-v1"
        }
      }
    ],
    "tools": [
      {
        "tool": {
          "name": "Slide recipe: Cover",
          "slug": "cover-slide",
          "status": "active",
          "bestFor": null,
          "canonId": "019df269-2a08-767d-9128-e7431e6fe8a3",
          "version": 1,
          "bodyDocId": "019df269-29e5-7738-b5fa-6892e5dc8e65",
          "description": "The first ten seconds. Build it deliberately.",
          "familyLabel": "slide-recipe",
          "categoryName": "Slide",
          "categorySlug": "slide"
        },
        "agent": "designer",
        "layer": "slide",
        "agents": [
          "designer"
        ],
        "matchId": "5db5b6f4-5cc1-435b-b232-ebc923f74c4c",
        "evidence": "This slide has a title, subtitle, and logo, which are typical elements of a cover slide.",
        "pageRefs": null,
        "priority": null,
        "whenToUse": null,
        "confidence": 0.9,
        "extraction": {
          "at": "2026-07-16 21:49:10.015468+00",
          "model": "or:meta-llama/llama-4-scout",
          "runId": null,
          "seconds": null,
          "promptVersion": null
        },
        "pageNumber": 1,
        "whyItWorks": null,
        "antipattern": null,
        "cardinality": null,
        "narrativePurpose": null
      },
      {
        "tool": {
          "name": "Executive summary",
          "slug": "executive-summary",
          "status": "active",
          "bestFor": null,
          "canonId": "019dd9e1-4b63-72d5-9734-da757d91ca61",
          "version": 1,
          "bodyDocId": null,
          "description": "A condensed view of the entire argument on a single slide / block.",
          "familyLabel": null,
          "categoryName": null,
          "categorySlug": null
        },
        "agent": null,
        "layer": "slide",
        "agents": null,
        "matchId": "8a38cd65-6d01-4d93-9d43-fedba8bc33cb",
        "evidence": "This slide provides a brief overview of the report, which is a common element of an executive summary.",
        "pageRefs": null,
        "priority": null,
        "whenToUse": null,
        "confidence": 0.9,
        "extraction": {
          "at": "2026-07-16 21:49:10.076218+00",
          "model": "or:meta-llama/llama-4-scout",
          "runId": null,
          "seconds": null,
          "promptVersion": null
        },
        "pageNumber": 2,
        "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": "e983bc2c-5953-435f-b5a2-5303bd1b94bc",
        "evidence": "Dr. Khalid Khan EY Americas Strategy and Transactions AI Leader",
        "pageRefs": null,
        "priority": "Core",
        "whenToUse": null,
        "confidence": 0.7,
        "extraction": {
          "at": "2026-07-16 21:49:28.161975+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": "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": "65ba9245-0fa7-4b42-8e90-8b2fa6290de8",
        "evidence": "1. Ubiquitous impact: ... 2. Plenty of skills in the game: ... 3. Sector exposure varies: ... 4. More money, more exposure: ...",
        "pageRefs": null,
        "priority": null,
        "whenToUse": null,
        "confidence": 0.9,
        "extraction": {
          "at": "2026-07-16 21:49:28.195726+00",
          "model": "or:meta-llama/llama-4-scout",
          "runId": null,
          "seconds": null,
          "promptVersion": null
        },
        "pageNumber": 3,
        "whyItWorks": null,
        "antipattern": null,
        "cardinality": "common",
        "narrativePurpose": null
      },
      {
        "tool": {
          "name": "Analytical method",
          "slug": "analytical-method",
          "status": "active",
          "bestFor": null,
          "canonId": "b42c4911-7946-49b5-951c-5f3d23f4e2bd",
          "version": 1,
          "bodyDocId": null,
          "description": "Diagnostic / structuring methods (5-whys, fishbone, issue tree, hypothesis-driven).",
          "familyLabel": null,
          "categoryName": null,
          "categorySlug": null
        },
        "agent": null,
        "layer": "slide",
        "agents": null,
        "matchId": "ef30d937-ca50-4338-989c-224d2461dfed",
        "evidence": "The verb-noun pairs are then compared to patents filed for AI technology... to see how exposed they are to AI.",
        "pageRefs": null,
        "priority": null,
        "whenToUse": null,
        "confidence": 0.7,
        "extraction": {
          "at": "2026-07-16 21:49:28.263681+00",
          "model": "or:meta-llama/llama-4-scout",
          "runId": null,
          "seconds": null,
          "promptVersion": null
        },
        "pageNumber": 4,
        "whyItWorks": null,
        "antipattern": null,
        "cardinality": "common",
        "narrativePurpose": null
      },
      {
        "tool": {
          "name": "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": "22840f89-f369-4412-b8e4-20d6add05f4c",
        "evidence": "Chart 1: US cumulative employment by rescaled AI augmentation score",
        "pageRefs": null,
        "priority": null,
        "whenToUse": null,
        "confidence": 0.7,
        "extraction": {
          "at": "2026-07-16 21:49:28.36906+00",
          "model": "or:meta-llama/llama-4-scout",
          "runId": null,
          "seconds": null,
          "promptVersion": null
        },
        "pageNumber": 5,
        "whyItWorks": null,
        "antipattern": null,
        "cardinality": null,
        "narrativePurpose": null
      },
      {
        "tool": {
          "name": "Data Story Arc",
          "slug": "data-story-arc",
          "status": "active",
          "bestFor": null,
          "canonId": "019dd956-9c30-728e-b974-d3fb123dcf5a",
          "version": 1,
          "bodyDocId": null,
          "description": "Context → Conflict → Insight → Implication structure for data narratives",
          "familyLabel": null,
          "categoryName": "Loop",
          "categorySlug": "loop"
        },
        "agent": "Storyteller",
        "layer": "slide",
        "agents": [
          "Storyteller"
        ],
        "matchId": "24a8d538-2b17-4eca-9b2e-92047408983e",
        "evidence": "Our findings are quite striking, with 66% of US employment with moderate to high GenAI exposure, or the equivalent of 104 million jobs across the country (Chart 1).",
        "pageRefs": null,
        "priority": "Core",
        "whenToUse": null,
        "confidence": 0.7,
        "extraction": {
          "at": "2026-07-16 21:49:28.333986+00",
          "model": "or:meta-llama/llama-4-scout",
          "runId": null,
          "seconds": null,
          "promptVersion": null
        },
        "pageNumber": 5,
        "whyItWorks": null,
        "antipattern": null,
        "cardinality": null,
        "narrativePurpose": null
      },
      {
        "tool": {
          "name": "Scenario Analysis",
          "slug": "scenario-analysis",
          "status": "active",
          "bestFor": null,
          "canonId": "ca76b81a-ec1d-403f-b1e6-8d6eec3bf93e",
          "version": 1,
          "bodyDocId": null,
          "description": null,
          "familyLabel": null,
          "categoryName": null,
          "categorySlug": null
        },
        "agent": null,
        "layer": "slide",
        "agents": null,
        "matchId": "25cd904e-13e5-493d-b36c-3749ff359c7a",
        "evidence": "Using the ICT period as a reference, we created three scenarios - trend, revival (our baseline) and boom - that correspond to three different productivity outcomes for the next decade.",
        "pageRefs": null,
        "priority": null,
        "whenToUse": null,
        "confidence": 0.9,
        "extraction": {
          "at": "2026-07-16 21:49:28.468182+00",
          "model": "or:meta-llama/llama-4-scout",
          "runId": null,
          "seconds": null,
          "promptVersion": null
        },
        "pageNumber": 7,
        "whyItWorks": null,
        "antipattern": null,
        "cardinality": null,
        "narrativePurpose": null
      },
      {
        "tool": {
          "name": "Chart Selection Guide",
          "slug": "chart-selection-guide",
          "status": "active",
          "bestFor": null,
          "canonId": "019dd956-b1a0-700b-ba17-0e16c4d5bcae",
          "version": 1,
          "bodyDocId": null,
          "description": "Choosing the right chart type for your data and message",
          "familyLabel": null,
          "categoryName": "Slide",
          "categorySlug": "slide"
        },
        "agent": "Designer",
        "layer": "slide",
        "agents": [
          "Designer"
        ],
        "matchId": "76f6c1bb-8779-4932-9683-7c44a4ac8773",
        "evidence": "Chart 3: Regression coefficients of labor skills contributing to AI augmentation scores",
        "pageRefs": null,
        "priority": null,
        "whenToUse": null,
        "confidence": 0.7,
        "extraction": {
          "at": "2026-07-16 21:49:28.534355+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": "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": "8fcaf46f-74a0-420c-a66d-8956c508554e",
        "evidence": "Chart 4: Median, max and min rescaled AI augmentation scores across 22 US “major occupation groups”",
        "pageRefs": null,
        "priority": null,
        "whenToUse": null,
        "confidence": 0.7,
        "extraction": {
          "at": "2026-07-16 21:49:28.642096+00",
          "model": "or:meta-llama/llama-4-scout",
          "runId": null,
          "seconds": null,
          "promptVersion": null
        },
        "pageNumber": 9,
        "whyItWorks": null,
        "antipattern": null,
        "cardinality": null,
        "narrativePurpose": null
      },
      {
        "tool": {
          "name": "Data Story Arc",
          "slug": "data-story-arc",
          "status": "active",
          "bestFor": null,
          "canonId": "019dd956-9c30-728e-b974-d3fb123dcf5a",
          "version": 1,
          "bodyDocId": null,
          "description": "Context → Conflict → Insight → Implication structure for data narratives",
          "familyLabel": null,
          "categoryName": "Loop",
          "categorySlug": "loop"
        },
        "agent": "Storyteller",
        "layer": "slide",
        "agents": [
          "Storyteller"
        ],
        "matchId": "253453d2-7b53-4fc7-9f22-f2c75590e0fe",
        "evidence": "GenAI is transforming the workforce by enabling workers to delegate routine, data-heavy tasks to GenAI systems, thereby enhancing their focus on areas where human skills like strategic thinking, empathy and crea",
        "pageRefs": null,
        "priority": "Core",
        "whenToUse": null,
        "confidence": 0.7,
        "extraction": {
          "at": "2026-07-16 21:49:28.60637+00",
          "model": "or:meta-llama/llama-4-scout",
          "runId": null,
          "seconds": null,
          "promptVersion": null
        },
        "pageNumber": 9,
        "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": "2b7e0997-1c78-4bb2-b97f-d5a1922d0461",
        "evidence": "Chart 5: Median, max and min rescaled AI augmentation scores across US \"minor occupation groups\" - ten highest median scores",
        "pageRefs": null,
        "priority": null,
        "whenToUse": null,
        "confidence": 0.7,
        "extraction": {
          "at": "2026-07-16 21:49:28.742363+00",
          "model": "or:meta-llama/llama-4-scout",
          "runId": null,
          "seconds": null,
          "promptVersion": null
        },
        "pageNumber": 10,
        "whyItWorks": null,
        "antipattern": null,
        "cardinality": null,
        "narrativePurpose": null
      },
      {
        "tool": {
          "name": "Data Story Arc",
          "slug": "data-story-arc",
          "status": "active",
          "bestFor": null,
          "canonId": "019dd956-9c30-728e-b974-d3fb123dcf5a",
          "version": 1,
          "bodyDocId": null,
          "description": "Context → Conflict → Insight → Implication structure for data narratives",
          "familyLabel": null,
          "categoryName": "Loop",
          "categorySlug": "loop"
        },
        "agent": "Storyteller",
        "layer": "slide",
        "agents": [
          "Storyteller"
        ],
        "matchId": "a4628bb3-c371-4bd5-aab9-6d3b412b41d6",
        "evidence": "Looking at the top 10 occupations with the highest AI augmentation scores, professions like plant and system operators, physical scientists, agricultural workers, drafters, programmers, engineers, an",
        "pageRefs": null,
        "priority": "Core",
        "whenToUse": null,
        "confidence": 0.7,
        "extraction": {
          "at": "2026-07-16 21:49:28.708065+00",
          "model": "or:meta-llama/llama-4-scout",
          "runId": null,
          "seconds": null,
          "promptVersion": null
        },
        "pageNumber": 10,
        "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": "f1a149ee-3b09-48a3-8b47-c99d412b090c",
        "evidence": "Chart 6: Median, max and min rescaled AI augmentation scores across US \"minor occupation groups\" - ten lowest median scores",
        "pageRefs": null,
        "priority": null,
        "whenToUse": null,
        "confidence": 0.7,
        "extraction": {
          "at": "2026-07-16 21:49:28.810223+00",
          "model": "or:meta-llama/llama-4-scout",
          "runId": null,
          "seconds": null,
          "promptVersion": null
        },
        "pageNumber": 11,
        "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": "9f3c0678-91ee-4ce6-bce0-c7db92823b04",
        "evidence": "Chart 7: US annual wages and occupation share by AI augmentation score",
        "pageRefs": null,
        "priority": null,
        "whenToUse": null,
        "confidence": 0.7,
        "extraction": {
          "at": "2026-07-16 21:49:28.911512+00",
          "model": "or:meta-llama/llama-4-scout",
          "runId": null,
          "seconds": null,
          "promptVersion": null
        },
        "pageNumber": 13,
        "whyItWorks": null,
        "antipattern": null,
        "cardinality": null,
        "narrativePurpose": null
      },
      {
        "tool": {
          "name": "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": "3a181e78-d9a6-48e5-a888-d50d3b01a8fe",
        "evidence": "The slide uses a list/bullet format to present information.",
        "pageRefs": null,
        "priority": null,
        "whenToUse": null,
        "confidence": 0.7,
        "extraction": {
          "at": "2026-07-16 21:49:24.181101+00",
          "model": "or:meta-llama/llama-4-scout",
          "runId": null,
          "seconds": null,
          "promptVersion": null
        },
        "pageNumber": 15,
        "whyItWorks": null,
        "antipattern": null,
        "cardinality": "common",
        "narrativePurpose": null
      },
      {
        "tool": {
          "name": "Three Pillars",
          "slug": "three-pillars",
          "status": "active",
          "bestFor": null,
          "canonId": "019dd956-81ef-7455-a365-b234d95a6bbb",
          "version": 1,
          "bodyDocId": null,
          "description": "Three major supporting arguments that are MECE and address key concerns",
          "familyLabel": null,
          "categoryName": "Block",
          "categorySlug": "block"
        },
        "agent": "Architect",
        "layer": "slide",
        "agents": [
          "Architect"
        ],
        "matchId": "abf14298-5e9b-4e02-904d-7bc1c0588575",
        "evidence": "The slide presents three pillars for developing a tailored AI utilization and deployment plan.",
        "pageRefs": null,
        "priority": "Core",
        "whenToUse": null,
        "confidence": 0.7,
        "extraction": {
          "at": "2026-07-16 21:49:24.14577+00",
          "model": "or:meta-llama/llama-4-scout",
          "runId": null,
          "seconds": null,
          "promptVersion": null
        },
        "pageNumber": 15,
        "whyItWorks": null,
        "antipattern": null,
        "cardinality": null,
        "narrativePurpose": null
      },
      {
        "tool": {
          "name": "Executive summary",
          "slug": "executive-summary",
          "status": "active",
          "bestFor": null,
          "canonId": "019dd9e1-4b63-72d5-9734-da757d91ca61",
          "version": 1,
          "bodyDocId": null,
          "description": "A condensed view of the entire argument on a single slide / block.",
          "familyLabel": null,
          "categoryName": null,
          "categorySlug": null
        },
        "agent": null,
        "layer": "slide",
        "agents": null,
        "matchId": "b8b93fb9-933e-4785-80ea-83d4b82244d7",
        "evidence": "The slide provides a brief overview of EY-Parthenon's focus and approach.",
        "pageRefs": null,
        "priority": null,
        "whenToUse": null,
        "confidence": 0.7,
        "extraction": {
          "at": "2026-07-16 21:49:24.248541+00",
          "model": "or:meta-llama/llama-4-scout",
          "runId": null,
          "seconds": null,
          "promptVersion": null
        },
        "pageNumber": 16,
        "whyItWorks": null,
        "antipattern": null,
        "cardinality": "common",
        "narrativePurpose": null
      }
    ],
    "frameworks": [
      {
        "matchId": "c57cb48a-9cf0-401c-a5d2-b2951a91e0ee",
        "evidence": "Verb-noun pairing framework for occupational task analysis",
        "framework": null,
        "confidence": 0.9,
        "extraction": {
          "at": "2026-05-02 18:01:19.097+00",
          "model": "google/gemini-3.1-flash-lite-preview-20260303",
          "runId": null,
          "seconds": null,
          "promptVersion": null
        },
        "pageNumber": 4,
        "frameworkName": "analytical-method"
      },
      {
        "matchId": "6a038329-3c6b-4672-b261-c31ec781c1aa",
        "evidence": "Mentions creating three scenarios (trend, revival, boom) based on historical ICT data.",
        "framework": null,
        "confidence": 1,
        "extraction": {
          "at": "2026-05-02 18:01:22.522+00",
          "model": "google/gemini-3.1-flash-lite-preview-20260303",
          "runId": null,
          "seconds": null,
          "promptVersion": null
        },
        "pageNumber": 7,
        "frameworkName": "scenario_analysis"
      }
    ],
    "patterns": []
  },
  "storymakers": null,
  "score": {
    "backend": "codex",
    "scoredAt": "2026-05-02 12:06:05.085+00",
    "subScores": {
      "scqa_arc": 55,
      "action_titles": 43,
      "mece_structure": 52,
      "closing_strength": 45,
      "evidence_quality": 70,
      "clarity_of_thesis": 62,
      "production_quality": 55,
      "visual_storytelling": 66
    },
    "totalScore": 57,
    "coveragePct": 94,
    "explanations": {
      "scqa_arc": "Slides 2-3 establish situation and findings, but the deck quickly becomes an analytical sequence of exposure charts on slides 5-13 rather than a clear Situation-Complication-Question-Answer build.",
      "action_titles": "Many titles are topic or chart labels rather than insight sentences, for example slide 5: \"Chart 1: US cumulative employment by rescaled AI augmentation score\".",
      "mece_structure": "The four-part structure on slides 4, 7, 12, and 14 is broadly logical, but exposure, sectors, skills, occupations, and wages overlap and leave gaps around the stated German labor-market focus.",
      "closing_strength": "Slide 15 introduces a deployment-plan recommendation, but the deck ends with only one pillar and then a disclaimer on slide 16, leaving no clear integrated call to action or implementation roadmap.",
      "evidence_quality": "Major claims are usually supported with charts, metrics, footnotes, and cited research on slides 4-13, though the evidence is weakened by repeated US data in a deck framed as the German labor market.",
      "clarity_of_thesis": "The central idea is partly identifiable by slides 2-5 as GenAI having broad but heterogeneous labor-market exposure, but it is framed as findings and methodology rather than a crisp declarative thesis.",
      "production_quality": "Production is serviceable with consistent consulting components and some footnotes, but overcrowded slides 4, 8, 9, and 11, chart-label titles, and EY/McKinsey branding inconsistency reduce polish.",
      "visual_storytelling": "The deck generally uses appropriate charts for quantitative claims on slides 5-13, but stock photography and dense callout-plus-chart layouts often dilute the message."
    },
    "slidesAnalyzed": 15
  },
  "review": {
    "backend": null,
    "verdict": "A solid analytical mid-section wrapped in a broken narrative shell — promises four findings, delivers one pillar, and ends on a misbranded disclaimer; useful as a chart-craft reference, not as a Storymakers structural exemplar.",
    "reviewedAt": "2026-04-25 02:55:50+00",
    "slidesSeen": 16,
    "suggestions": [
      "Replace chart captions on p.5, p.6, p.11, p.13 with action titles that state the takeaway (e.g. 'Two-thirds of US jobs face moderate-to-high GenAI exposure' for p.5).",
      "Either deliver all four pillars promised on p.3 (and complete section 3) or rewrite p.3 to match the two pillars actually built — the current asymmetry breaks the MECE contract.",
      "Add a closing recommendation slide before p.16 with a concrete 'so what' for German business leaders, and fix the EY/McKinsey branding mismatch on the disclaimer."
    ],
    "closingScore": 28,
    "openingScore": 68,
    "topStrengths": [
      "p.8 'Departing from the low-skill obsolescence myth' is a genuine action title that asserts a counter-intuitive insight",
      "p.3 sets a clear 'Four key findings' promise that gives the audience a mental scaffold",
      "Quantified hook on p.5 (66% / 104M jobs) anchors the analytical section in a memorable number"
    ],
    "topWeaknesses": [
      "Section numbering breaks MECE: dividers labeled 1, 2, 4 with no section 3 (p.4, p.7, p.14)",
      "p.3 promises four findings but the deck only delivers 'Pillar 1' on p.15 with no Pillars 2-4",
      "Final slide (p.16) carries EY branding while the cover (p.1) is McKinsey — a credibility-destroying inconsistency",
      "Most chart slides use descriptive captions ('Chart 6: Median, max and min...') instead of stating what the chart proves",
      "No explicit recommendation, decision, or call-to-action slide before the appendix"
    ],
    "narrativeScore": 52,
    "pillarCritique": "Two section dividers exist (p.7 'Plenty of skills in the game' and p.14 'Business implications'), but they are numbered 2 and 4 with section 3 missing, so the pillars are neither MECE nor complete — they read as topic stubs rather than a structured argument.",
    "closingCritique": "There is no real close: p.15 introduces 'Pillar 1' with no Pillar 2/3/4 visible, there is no call to action or next-steps slide, and p.16 is an 'EY | Building a better working world' disclaimer that contradicts the McKinsey cover — a jarring branding artifact that kills any memorable ending.",
    "openingCritique": "The exec summary (p.2) frames the three impact mechanisms and p.3 promises 'Four key findings,' which is a serviceable setup, but the deck never leads with the answer — the headline 66% stat doesn't surface until p.5 and the recommendation is deferred to the very end.",
    "extractionSeconds": 56.09283,
    "narrativeCritique": "The deck establishes context (p.2-3) and runs a long analytical middle (p.4-13), but the resolution collapses: section numbering jumps from '2' (p.7) to '4' (p.14), section 3 is missing entirely, and the implications act is a single 'Pillar 1' slide before the disclaimer. The result is an analysis-heavy build with no payoff.",
    "titleQualityScore": 48,
    "titleQualityCritique": "Titles are mixed: 'Departing from the low-skill obsolescence myth' (p.8) is a strong insight-bearing action title, but most are topic labels or chart captions like 'Chart 1: US cumulative employment by rescaled AI augmentation score' (p.5) and 'Most and least exposed occupations' (p.10), and p.12 is a rhetorical question rather than an answer."
  },
  "activistThesis": null,
  "pitchdeck": {
    "metadata": null,
    "profile": null
  },
  "slides": [
    {
      "page": 1,
      "type": "setup",
      "title": "EY Parthenon branding present.",
      "function": "front_matter",
      "imagePath": "https://imgproxy.kitesheet.com/PykAfDimOQGEgtnMPIx1G5sHAtyxUnwCEnmiDY0gBME/rs:fit:1200:1200:0/q:82/f:webp/czM6Ly9raXRlc2hlZXQvY29ycHVzL3NsaWRlcy9hYTRmOGVlNDJmZTk2Y2Y4L3AwMDEuanBn",
      "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": 8,
        "componentCount": 3,
        "textChars": 100,
        "nDataPoints": 0,
        "notes": "EY Parthenon branding present.",
        "elementsJson": [
          "headline_text",
          "photo",
          "logo_grid"
        ],
        "confidence": 1,
        "extraction": {
          "model": "google/gemini-3.1-flash-lite-preview-20260303",
          "runId": null,
          "at": "2026-05-02 18:01:16.737+00",
          "seconds": 1.984,
          "promptVersion": "v2-canon-conditioned"
        }
      },
      "links": {
        "slide": "/slides/019dd923-5e88-73ef-bd59-b7c870c8c8e8/1",
        "deck": "/decks/019dd923-5e88-73ef-bd59-b7c870c8c8e8",
        "deckAnchor": "/decks/019dd923-5e88-73ef-bd59-b7c870c8c8e8#slide-1",
        "deckJson": "/decks/019dd923-5e88-73ef-bd59-b7c870c8c8e8.json"
      },
      "components": [
        {
          "bbox": {
            "h": 0.07,
            "w": 0.25,
            "x": 0.68,
            "y": 0.9
          },
          "kind": "image",
          "text": "EY Parthenon logo",
          "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 18:01:16.737+00",
            "model": "google/gemini-3.1-flash-lite-preview-20260303",
            "runId": null,
            "seconds": null,
            "promptVersion": null
          },
          "componentId": "4cf15bf8-9f9c-45c1-a6e3-cd898edbdc7c",
          "parentComponentId": null
        },
        {
          "bbox": {
            "h": 1,
            "w": 1,
            "x": 0,
            "y": 0
          },
          "kind": "image",
          "text": "Woman in a server room with digital overlays",
          "attrs": null,
          "canon": {
            "kind": {
              "name": "Image",
              "slug": "image",
              "status": "active",
              "canonId": "019de52c-f978-701f-a720-51d029d769e7",
              "version": 1,
              "description": "Photo, illustration, screenshot or icon."
            },
            "tool": null,
            "subkind": {
              "name": "Photo",
              "slug": "photo",
              "status": "active",
              "canonId": "019de52c-fd37-757f-b4a8-ca26d4888875",
              "version": 1,
              "description": null
            },
            "framework": null
          },
          "subkind": "photo",
          "groupRole": null,
          "confidence": null,
          "extraction": {
            "at": "2026-05-02 18:01:16.737+00",
            "model": "google/gemini-3.1-flash-lite-preview-20260303",
            "runId": null,
            "seconds": null,
            "promptVersion": null
          },
          "componentId": "78bd8014-b9e1-4d6f-a743-380edbf874fb",
          "parentComponentId": null
        },
        {
          "bbox": {
            "h": 0.1,
            "w": 0.4,
            "x": 0.1,
            "y": 0.08
          },
          "kind": "title",
          "text": "The impact of GenAI on the labor 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 18:01:16.737+00",
            "model": "google/gemini-3.1-flash-lite-preview-20260303",
            "runId": null,
            "seconds": null,
            "promptVersion": null
          },
          "componentId": "7974efe8-ec00-4875-8199-a5cd6a3c700e",
          "parentComponentId": null
        }
      ],
      "metrics": [],
      "tools": [
        {
          "tool": {
            "name": "Slide recipe: Cover",
            "slug": "cover-slide",
            "status": "active",
            "bestFor": null,
            "canonId": "019df269-2a08-767d-9128-e7431e6fe8a3",
            "version": 1,
            "bodyDocId": "019df269-29e5-7738-b5fa-6892e5dc8e65",
            "description": "The first ten seconds. Build it deliberately.",
            "familyLabel": "slide-recipe",
            "categoryName": "Slide",
            "categorySlug": "slide"
          },
          "agent": "designer",
          "layer": "slide",
          "agents": [
            "designer"
          ],
          "matchId": "5db5b6f4-5cc1-435b-b232-ebc923f74c4c",
          "evidence": "This slide has a title, subtitle, and logo, which are typical elements of a cover slide.",
          "pageRefs": null,
          "priority": null,
          "whenToUse": null,
          "confidence": 0.9,
          "extraction": {
            "at": "2026-07-16 21:49:10.015468+00",
            "model": "or:meta-llama/llama-4-scout",
            "runId": null,
            "seconds": null,
            "promptVersion": null
          },
          "pageNumber": 1,
          "whyItWorks": null,
          "antipattern": null,
          "cardinality": null,
          "narrativePurpose": null
        }
      ],
      "frameworks": [],
      "arcBeats": [
        {
          "to": 2,
          "arc": {
            "name": "The Consultant's Gambit",
            "slug": "consultants-gambit",
            "status": "active",
            "bestFor": "Business cases, project proposals, strategic recommendations",
            "canonId": "019dd956-5e0a-73c8-b305-81c38c959e9c",
            "version": 1,
            "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49",
            "structure": "Situation & Context -> Problem & Complication -> Solution & Approach -> Evidence & Proof -> Impact & Next Steps",
            "description": null,
            "familyLabel": null
          },
          "from": 1,
          "name": "Situation & Context",
          "beatId": "fb4a4551-e3d0-4a4d-ba42-a20d89d7443a",
          "matchId": "424d33e4-517f-4ec9-b9d0-2d8a129b071e",
          "beatType": {
            "name": "Situation & Context",
            "slug": "consultants-gambit-situation-context",
            "status": "active",
            "canonId": "019dd9b8-05ae-741b-992d-65ee83c639b3",
            "version": 1,
            "description": null
          },
          "evidence": "The cover and executive summary provide an overview of the topic",
          "position": 0,
          "isPrimaryArc": true,
          "parentBeatType": {
            "name": "Setup",
            "slug": "setup",
            "status": "active",
            "canonId": "019dd9b8-020e-7505-af9b-d9b9a4679bcc",
            "version": 1,
            "description": "Where the deck grounds the reader before doing anything else. Almost every arc opens here."
          },
          "alignedBlockIds": null,
          "matchConfidence": 0.8
        }
      ],
      "loops": [],
      "thumbSrc": "https://imgproxy.kitesheet.com/u9_-9LPUp-9_h1OGPktXq9isFJgo4S0VxpiCsNGCrfc/rs:fit:480:480:0/q:78/f:webp/czM6Ly9raXRlc2hlZXQvY29ycHVzL3NsaWRlcy9hYTRmOGVlNDJmZTk2Y2Y4L3AwMDEuanBn",
      "imagePathAlt": "https://imgproxy.kitesheet.com/jM2r0dLTks_FLBY_A87NHi5sNlTL0SbHJU-aau4kwLc/rs:fit:1200:1200:0/q:82/f:webp/czM6Ly9raXRlc2hlZXQvY29ycHVzL3NsaWRlcy9hYTRmOGVlNDJmZTk2Y2Y4L3AwMDEucG5n",
      "thumbSrcAlt": "https://imgproxy.kitesheet.com/bp29Z3mikZlHKxFS65eGT31LaPwHpdCcI2mQg5qIbNw/rs:fit:480:480:0/q:78/f:webp/czM6Ly9raXRlc2hlZXQvY29ycHVzL3NsaWRlcy9hYTRmOGVlNDJmZTk2Y2Y4L3AwMDEucG5n"
    },
    {
      "page": 2,
      "type": "setup",
      "title": "Includes a headshot and bio of Gregory Daco, EY-Parthenon Chief Economist.",
      "function": "summarize",
      "rawType": "executive_summary",
      "block": null,
      "metadata": {
        "slideType": "executive_summary",
        "slideTypeCanon": {
          "name": "Executive summary",
          "slug": "executive_summary",
          "status": "active",
          "canonId": "019de52d-06be-73ff-81b3-f99fe7f0025e",
          "version": 1,
          "description": null
        },
        "function": "summarize",
        "functionCanon": {
          "name": "Summarize",
          "slug": "summarize",
          "status": "active",
          "canonId": "019de52d-1541-704f-b86f-bf7b75056373",
          "version": 1,
          "description": null
        },
        "density": "dense",
        "densityScore": 66,
        "componentCount": 7,
        "textChars": 1145,
        "nDataPoints": 0,
        "notes": "Includes a headshot and bio of Gregory Daco, EY-Parthenon Chief Economist.",
        "elementsJson": [
          "photo",
          "headshot",
          "paragraph",
          "bullet_list"
        ],
        "confidence": 1,
        "extraction": {
          "model": "google/gemini-3.1-flash-lite-preview-20260303",
          "runId": null,
          "at": "2026-05-02 18:01:17.424+00",
          "seconds": 2.49,
          "promptVersion": "v2-canon-conditioned"
        }
      },
      "links": {
        "slide": "/slides/019dd923-5e88-73ef-bd59-b7c870c8c8e8/2",
        "deck": "/decks/019dd923-5e88-73ef-bd59-b7c870c8c8e8",
        "deckAnchor": "/decks/019dd923-5e88-73ef-bd59-b7c870c8c8e8#slide-2",
        "deckJson": "/decks/019dd923-5e88-73ef-bd59-b7c870c8c8e8.json"
      },
      "components": [
        {
          "bbox": null,
          "kind": "callout",
          "text": "What will the impact of GenAI on the labor market entail? Indeed, technological innovation affects labor via: Job creation, Job displacement, and Job transformation.",
          "attrs": null,
          "canon": {
            "kind": {
              "name": "Callout",
              "slug": "callout",
              "status": "active",
              "canonId": "019de52c-f8d3-761a-8953-7d37080de5e2",
              "version": 1,
              "description": "Highlighted callout box."
            },
            "tool": {
              "name": "Visual emphasis",
              "slug": "visual-emphasis",
              "status": "active",
              "bestFor": null,
              "canonId": "019dd9e1-474b-736b-a8eb-a794dd88241c",
              "version": 1,
              "bodyDocId": null,
              "description": "Drawing the eye to one element above the rest of the slide.",
              "familyLabel": null
            },
            "subkind": null,
            "framework": null
          },
          "subkind": null,
          "groupRole": null,
          "confidence": null,
          "extraction": {
            "at": "2026-04-24 16:10:25+00",
            "model": "or:google/gemini-3.1-flash-lite-preview",
            "runId": null,
            "seconds": null,
            "promptVersion": null
          },
          "componentId": "019dd952-2e35-763d-838d-2caf588d0d3b",
          "parentComponentId": null
        },
        {
          "bbox": {
            "h": 0.208,
            "w": 0.196,
            "x": 0.09,
            "y": 0.556
          },
          "kind": "image",
          "text": "Gregory Daco headshot",
          "attrs": null,
          "canon": {
            "kind": {
              "name": "Image",
              "slug": "image",
              "status": "active",
              "canonId": "019de52c-f978-701f-a720-51d029d769e7",
              "version": 1,
              "description": "Photo, illustration, screenshot or icon."
            },
            "tool": null,
            "subkind": {
              "name": "Headshot",
              "slug": "headshot",
              "status": "active",
              "canonId": "019de52c-fd5f-765c-9282-38b54f61bbbf",
              "version": 1,
              "description": null
            },
            "framework": null
          },
          "subkind": "headshot",
          "groupRole": null,
          "confidence": null,
          "extraction": {
            "at": "2026-05-02 18:01:17.424+00",
            "model": "google/gemini-3.1-flash-lite-preview-20260303",
            "runId": null,
            "seconds": null,
            "promptVersion": null
          },
          "componentId": "69e7662e-4c37-4954-8d36-8d221b8818b3",
          "parentComponentId": null
        },
        {
          "bbox": {
            "h": 0.066,
            "w": 0.57,
            "x": 0.343,
            "y": 0.804
          },
          "kind": "list",
          "text": "Job creation, where emerging technologies can seed new roles and job opportunities\nJob displacement, where some jobs or functions become obsolete due to automation\nJob transformation, where the nature of a function or task is augmented",
          "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 18:01:17.424+00",
            "model": "google/gemini-3.1-flash-lite-preview-20260303",
            "runId": null,
            "seconds": null,
            "promptVersion": null
          },
          "componentId": "c13fb73b-8468-40d5-97dd-d82b8e2435bd",
          "parentComponentId": null
        },
        {
          "bbox": {
            "h": 0.084,
            "w": 0.57,
            "x": 0.343,
            "y": 0.671
          },
          "kind": "paragraph",
          "text": "The rapid development of generative artificial intelligence (GenAI), capable of automating tasks across various industries, has reignited these concerns. However, as we illustrated in the first article of our series, employment levels have consistently risen over the last century, as new technologies often create more jobs than they eliminate.",
          "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 18:01:17.424+00",
            "model": "google/gemini-3.1-flash-lite-preview-20260303",
            "runId": null,
            "seconds": null,
            "promptVersion": null
          },
          "componentId": "6f803237-132b-44e7-9ad1-78436a67db09",
          "parentComponentId": null
        },
        {
          "bbox": {
            "h": 0.024,
            "w": 0.57,
            "x": 0.343,
            "y": 0.763
          },
          "kind": "paragraph",
          "text": "What will the impact of GenAI on the labor market entail? Indeed, technological innovation affects labor via:",
          "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 18:01:17.424+00",
            "model": "google/gemini-3.1-flash-lite-preview-20260303",
            "runId": null,
            "seconds": null,
            "promptVersion": null
          },
          "componentId": "9f648381-6ee4-4e2e-851e-c2667c3817bc",
          "parentComponentId": null
        },
        {
          "bbox": {
            "h": 0.06,
            "w": 0.57,
            "x": 0.343,
            "y": 0.595
          },
          "kind": "paragraph",
          "text": "Technological progress has long sparked fears of machines making human labor redundant. Throughout history, technology has transformed work, replacing some jobs while creating new ones, yet widespread unemployment due to technology has not materialized.",
          "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 18:01:17.424+00",
            "model": "google/gemini-3.1-flash-lite-preview-20260303",
            "runId": null,
            "seconds": null,
            "promptVersion": null
          },
          "componentId": "c454e023-0f7b-47fa-8578-b27a8a9ee26a",
          "parentComponentId": null
        },
        {
          "bbox": {
            "h": 0.028,
            "w": 0.225,
            "x": 0.343,
            "y": 0.548
          },
          "kind": "title",
          "text": "Executive summary",
          "attrs": null,
          "canon": {
            "kind": {
              "name": "Title",
              "slug": "title",
              "status": "active",
              "canonId": "019de52c-f7dd-76d9-b848-b1f12bd85cf4",
              "version": 1,
              "description": "Slide title or headline."
            },
            "tool": null,
            "subkind": {
              "name": "Headline",
              "slug": "headline",
              "status": "active",
              "canonId": "019de52c-fae1-7463-9a7c-d60668eced0d",
              "version": 1,
              "description": null
            },
            "framework": null
          },
          "subkind": "headline",
          "groupRole": null,
          "confidence": null,
          "extraction": {
            "at": "2026-05-02 18:01:17.424+00",
            "model": "google/gemini-3.1-flash-lite-preview-20260303",
            "runId": null,
            "seconds": null,
            "promptVersion": null
          },
          "componentId": "ee3e26f1-ecff-46f1-8c3d-8f72e3213bfd",
          "parentComponentId": null
        }
      ],
      "metrics": [],
      "tools": [
        {
          "tool": {
            "name": "Executive summary",
            "slug": "executive-summary",
            "status": "active",
            "bestFor": null,
            "canonId": "019dd9e1-4b63-72d5-9734-da757d91ca61",
            "version": 1,
            "bodyDocId": null,
            "description": "A condensed view of the entire argument on a single slide / block.",
            "familyLabel": null,
            "categoryName": null,
            "categorySlug": null
          },
          "agent": null,
          "layer": "slide",
          "agents": null,
          "matchId": "8a38cd65-6d01-4d93-9d43-fedba8bc33cb",
          "evidence": "This slide provides a brief overview of the report, which is a common element of an executive summary.",
          "pageRefs": null,
          "priority": null,
          "whenToUse": null,
          "confidence": 0.9,
          "extraction": {
            "at": "2026-07-16 21:49:10.076218+00",
            "model": "or:meta-llama/llama-4-scout",
            "runId": null,
            "seconds": null,
            "promptVersion": null
          },
          "pageNumber": 2,
          "whyItWorks": null,
          "antipattern": null,
          "cardinality": "common",
          "narrativePurpose": null
        }
      ],
      "frameworks": [],
      "arcBeats": [
        {
          "to": 2,
          "arc": {
            "name": "The Consultant's Gambit",
            "slug": "consultants-gambit",
            "status": "active",
            "bestFor": "Business cases, project proposals, strategic recommendations",
            "canonId": "019dd956-5e0a-73c8-b305-81c38c959e9c",
            "version": 1,
            "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49",
            "structure": "Situation & Context -> Problem & Complication -> Solution & Approach -> Evidence & Proof -> Impact & Next Steps",
            "description": null,
            "familyLabel": null
          },
          "from": 1,
          "name": "Situation & Context",
          "beatId": "fb4a4551-e3d0-4a4d-ba42-a20d89d7443a",
          "matchId": "424d33e4-517f-4ec9-b9d0-2d8a129b071e",
          "beatType": {
            "name": "Situation & Context",
            "slug": "consultants-gambit-situation-context",
            "status": "active",
            "canonId": "019dd9b8-05ae-741b-992d-65ee83c639b3",
            "version": 1,
            "description": null
          },
          "evidence": "The cover and executive summary provide an overview of the topic",
          "position": 0,
          "isPrimaryArc": true,
          "parentBeatType": {
            "name": "Setup",
            "slug": "setup",
            "status": "active",
            "canonId": "019dd9b8-020e-7505-af9b-d9b9a4679bcc",
            "version": 1,
            "description": "Where the deck grounds the reader before doing anything else. Almost every arc opens here."
          },
          "alignedBlockIds": null,
          "matchConfidence": 0.8
        }
      ],
      "loops": [],
      "locked": true
    },
    {
      "page": 3,
      "type": "resolution",
      "function": "summarize",
      "rawType": "key_takeaways",
      "block": null,
      "metadata": {
        "slideType": "key_takeaways",
        "slideTypeCanon": {
          "name": "Key takeaways",
          "slug": "key_takeaways",
          "status": "active",
          "canonId": "019de52d-06e7-7674-a891-9f7de3b11b6d",
          "version": 1,
          "description": null
        },
        "function": "summarize",
        "functionCanon": {
          "name": "Summarize",
          "slug": "summarize",
          "status": "active",
          "canonId": "019de52d-1541-704f-b86f-bf7b75056373",
          "version": 1,
          "description": null
        },
        "density": "dense",
        "densityScore": 57,
        "componentCount": 6,
        "textChars": 745,
        "nDataPoints": 4,
        "notes": null,
        "elementsJson": [
          "numbered_list",
          "quote_block"
        ],
        "confidence": 1,
        "extraction": {
          "model": "google/gemini-3.1-flash-lite-preview-20260303",
          "runId": null,
          "at": "2026-05-02 18:01:17.771+00",
          "seconds": 2.705,
          "promptVersion": "v2-canon-conditioned"
        }
      },
      "links": {
        "slide": "/slides/019dd923-5e88-73ef-bd59-b7c870c8c8e8/3",
        "deck": "/decks/019dd923-5e88-73ef-bd59-b7c870c8c8e8",
        "deckAnchor": "/decks/019dd923-5e88-73ef-bd59-b7c870c8c8e8#slide-3",
        "deckJson": "/decks/019dd923-5e88-73ef-bd59-b7c870c8c8e8.json"
      },
      "components": [
        {
          "bbox": null,
          "kind": "callout",
          "text": "GenAI in this early stage is boosting productivity, but the use cases are expansive.",
          "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": "2026-04-24 16:10:25+00",
            "model": "or:google/gemini-3.1-flash-lite-preview",
            "runId": null,
            "seconds": null,
            "promptVersion": null
          },
          "componentId": "019dd952-2e36-76f2-aee1-7de85caa51ca",
          "parentComponentId": null
        },
        {
          "bbox": {
            "h": 0.35,
            "w": 0.55,
            "x": 0.343,
            "y": 0.183
          },
          "kind": "list",
          "text": "1. Ubiquitous impact: ... 2. Plenty of skills in the game: ... 3. Sector exposure varies: ... 4. More money, more exposure: ...",
          "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 18:01:17.771+00",
            "model": "google/gemini-3.1-flash-lite-preview-20260303",
            "runId": null,
            "seconds": null,
            "promptVersion": null
          },
          "componentId": "eace923f-1de8-4aa6-a788-fec351de8f98",
          "parentComponentId": null
        },
        {
          "bbox": null,
          "kind": "metric",
          "text": "labor market exposure: 66%",
          "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": "2026-04-24 16:10:25+00",
            "model": "or:google/gemini-3.1-flash-lite-preview",
            "runId": null,
            "seconds": null,
            "promptVersion": null
          },
          "componentId": "019dd952-2e36-76f2-aee1-83faffae2bd4",
          "parentComponentId": null
        },
        {
          "bbox": {
            "h": 0.04,
            "w": 0.3,
            "x": 0.343,
            "y": 0.875
          },
          "kind": "paragraph",
          "text": "Dr. Khalid Khan\nEY Americas Strategy and Transactions AI Leader",
          "attrs": null,
          "canon": {
            "kind": {
              "name": "Paragraph",
              "slug": "paragraph",
              "status": "active",
              "canonId": "5f2affc0-941d-4d07-959d-4bfc1930cea4",
              "version": 1,
              "description": "Single prose block in the body of a slide."
            },
            "tool": null,
            "subkind": {
              "name": "Paragraph",
              "slug": "paragraph",
              "status": "active",
              "canonId": "019de52c-fb80-75af-aa5c-a7a4bfac2433",
              "version": 1,
              "description": null
            },
            "framework": null
          },
          "subkind": "paragraph",
          "groupRole": null,
          "confidence": null,
          "extraction": {
            "at": "2026-05-02 18:01:17.771+00",
            "model": "google/gemini-3.1-flash-lite-preview-20260303",
            "runId": null,
            "seconds": null,
            "promptVersion": null
          },
          "componentId": "f5c00501-acac-4112-9f97-fa5016f9e8b6",
          "parentComponentId": null
        },
        {
          "bbox": {
            "h": 0.15,
            "w": 0.55,
            "x": 0.343,
            "y": 0.698
          },
          "kind": "quote",
          "text": "GenAI in this early stage is boosting productivity, but the use cases are expansive. It has the potential to spur new business models that will give rise to new products, new ways to engage customers and new ways to get these products in the hands of these customers. As has been the case in the past, transformative business models require both different and new ways of working.",
          "attrs": null,
          "canon": {
            "kind": {
              "name": "Quote",
              "slug": "quote",
              "status": "active",
              "canonId": "019de52c-f8fb-751e-8bc6-d58e2d59562a",
              "version": 1,
              "description": "Pull quote or testimonial."
            },
            "tool": null,
            "subkind": {
              "name": "Pull quote",
              "slug": "pull-quote",
              "status": "active",
              "canonId": "019de52c-fbf9-76fe-97e1-a0b7540445c9",
              "version": 1,
              "description": null
            },
            "framework": null
          },
          "subkind": "pull-quote",
          "groupRole": null,
          "confidence": null,
          "extraction": {
            "at": "2026-05-02 18:01:17.771+00",
            "model": "google/gemini-3.1-flash-lite-preview-20260303",
            "runId": null,
            "seconds": null,
            "promptVersion": null
          },
          "componentId": "d3c127e1-5639-4a60-beaa-6558b6b960a8",
          "parentComponentId": null
        },
        {
          "bbox": {
            "h": 0.02,
            "w": 0.45,
            "x": 0.343,
            "y": 0.158
          },
          "kind": "title",
          "text": "Four key findings of GenAI's potential impact on the labor 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 18:01:17.771+00",
            "model": "google/gemini-3.1-flash-lite-preview-20260303",
            "runId": null,
            "seconds": null,
            "promptVersion": null
          },
          "componentId": "bef0da5e-4695-4b00-9656-b84fe022b79e",
          "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": "e983bc2c-5953-435f-b5a2-5303bd1b94bc",
          "evidence": "Dr. Khalid Khan EY Americas Strategy and Transactions AI Leader",
          "pageRefs": null,
          "priority": "Core",
          "whenToUse": null,
          "confidence": 0.7,
          "extraction": {
            "at": "2026-07-16 21:49:28.161975+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": "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": "65ba9245-0fa7-4b42-8e90-8b2fa6290de8",
          "evidence": "1. Ubiquitous impact: ... 2. Plenty of skills in the game: ... 3. Sector exposure varies: ... 4. More money, more exposure: ...",
          "pageRefs": null,
          "priority": null,
          "whenToUse": null,
          "confidence": 0.9,
          "extraction": {
            "at": "2026-07-16 21:49:28.195726+00",
            "model": "or:meta-llama/llama-4-scout",
            "runId": null,
            "seconds": null,
            "promptVersion": null
          },
          "pageNumber": 3,
          "whyItWorks": null,
          "antipattern": null,
          "cardinality": "common",
          "narrativePurpose": null
        }
      ],
      "frameworks": [],
      "arcBeats": [
        {
          "to": 5,
          "arc": {
            "name": "The Consultant's Gambit",
            "slug": "consultants-gambit",
            "status": "active",
            "bestFor": "Business cases, project proposals, strategic recommendations",
            "canonId": "019dd956-5e0a-73c8-b305-81c38c959e9c",
            "version": 1,
            "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49",
            "structure": "Situation & Context -> Problem & Complication -> Solution & Approach -> Evidence & Proof -> Impact & Next Steps",
            "description": null,
            "familyLabel": null
          },
          "from": 3,
          "name": "Problem & Complication",
          "beatId": "55069988-7d18-4303-b0f8-10d40c6fef58",
          "matchId": "424d33e4-517f-4ec9-b9d0-2d8a129b071e",
          "beatType": {
            "name": "Problem & Complication",
            "slug": "consultants-gambit-problem-complication",
            "status": "active",
            "canonId": "019dd9b8-064a-777f-a374-e9a8c43dedd4",
            "version": 1,
            "description": null
          },
          "evidence": "The key takeaways and data tables highlight the complex effects of GenAI on the labor market",
          "position": 1,
          "isPrimaryArc": true,
          "parentBeatType": {
            "name": "Complication",
            "slug": "complication",
            "status": "active",
            "canonId": "019dd9b8-0275-7709-b2d6-4f77c3fc7579",
            "version": 1,
            "description": "The point in the narrative where the audience should feel discomfort. Required for argumentative arcs."
          },
          "alignedBlockIds": null,
          "matchConfidence": 0.8
        }
      ],
      "loops": [
        {
          "to": 5,
          "from": 3,
          "loop": {
            "name": "01_logic_chain",
            "slug": "01-logic-chain",
            "status": "active",
            "bestFor": "Skeptical audiences, controversial recommendations, rigorous analysis",
            "canonId": "019dd956-6638-7457-8650-9b0b42e59fb3",
            "version": 1,
            "bodyDocId": "019df22a-2420-77be-bc41-ded96d08cb21",
            "structure": "Premise 1 (Accepted truth) -> Premise 2 (Observed fact) -> Therefore... (Inevitable conclusion)",
            "description": "Build an airtight chain of logic where each premise leads inevitably to the conclusion",
            "familyLabel": null
          },
          "matchId": "1679a32c-e543-4087-8767-8a695c8716c4",
          "evidence": "The key takeaways and data tables provide a logical chain of information",
          "position": 0,
          "objective": "What are the key findings of GenAI's potential impact on the labor market?",
          "confidence": 0.7,
          "extraction": {
            "at": "2026-07-16 21:19:48.518043+00",
            "model": "or:meta-llama/llama-4-scout",
            "runId": null,
            "seconds": null,
            "promptVersion": "doc-narrative-v1"
          }
        }
      ],
      "locked": true
    },
    {
      "page": 4,
      "type": "setup",
      "title": "The methodology relies on mapping O*NET task descriptions to AI patent data to calculate an impact score.",
      "function": "present_framework",
      "rawType": "appendix_methodology",
      "block": null,
      "metadata": {
        "slideType": "appendix_methodology",
        "slideTypeCanon": {
          "name": "Appendix methodology",
          "slug": "appendix_methodology",
          "status": "active",
          "canonId": "019de52d-07d9-726c-8599-167f2d2ffaa7",
          "version": 1,
          "description": null
        },
        "function": "present_framework",
        "functionCanon": {
          "name": "Present framework",
          "slug": "present_framework",
          "status": "active",
          "canonId": "019de52d-1403-7667-9100-d2ac6709f750",
          "version": 1,
          "description": null
        },
        "density": "overcrowded",
        "densityScore": 75,
        "componentCount": 8,
        "textChars": 1296,
        "nDataPoints": 0,
        "notes": "The methodology relies on mapping O*NET task descriptions to AI patent data to calculate an impact score.",
        "elementsJson": [
          "photo",
          "headline_text",
          "paragraph",
          "footnote"
        ],
        "confidence": 1,
        "extraction": {
          "model": "google/gemini-3.1-flash-lite-preview-20260303",
          "runId": null,
          "at": "2026-05-02 18:01:19.097+00",
          "seconds": 3.965,
          "promptVersion": "v2-canon-conditioned"
        }
      },
      "links": {
        "slide": "/slides/019dd923-5e88-73ef-bd59-b7c870c8c8e8/4",
        "deck": "/decks/019dd923-5e88-73ef-bd59-b7c870c8c8e8",
        "deckAnchor": "/decks/019dd923-5e88-73ef-bd59-b7c870c8c8e8#slide-4",
        "deckJson": "/decks/019dd923-5e88-73ef-bd59-b7c870c8c8e8.json"
      },
      "components": [
        {
          "bbox": null,
          "kind": "callout",
          "text": "Research shows most US jobs could have moderate to high exposure to AI, with high or very high augmentation for roughly a third of those.",
          "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": "2026-04-24 16:10:25+00",
            "model": "or:google/gemini-3.1-flash-lite-preview",
            "runId": null,
            "seconds": null,
            "promptVersion": null
          },
          "componentId": "019dd952-2e35-763d-838d-1246f06ae4ac",
          "parentComponentId": null
        },
        {
          "bbox": {
            "h": 0.1,
            "w": 0.62,
            "x": 0.34,
            "y": 0.76
          },
          "kind": "paragraph",
          "text": "For example, the role of an agricultural technician includes a task for 'developing soil sampling grids,' which has an associated verb-noun pair of 'develop grid' representing 5% of an agricultural technicians' functions.",
          "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 18:01:19.097+00",
            "model": "google/gemini-3.1-flash-lite-preview-20260303",
            "runId": null,
            "seconds": null,
            "promptVersion": null
          },
          "componentId": "02ba7af7-8dc4-403a-a07b-55d6f37a1065",
          "parentComponentId": null
        },
        {
          "bbox": {
            "h": 0.15,
            "w": 0.62,
            "x": 0.34,
            "y": 0.61
          },
          "kind": "paragraph",
          "text": "The verb-noun pairs are then compared to patents filed for AI technology... to see how exposed they are to AI. The sum product of each task's exposure score and the frequency of tasks in every occupation is then used to estimate an aggregate raw AI impact score per occupation.",
          "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 18:01:19.097+00",
            "model": "google/gemini-3.1-flash-lite-preview-20260303",
            "runId": null,
            "seconds": null,
            "promptVersion": null
          },
          "componentId": "58b427ea-4970-4347-b227-aea062677ae0",
          "parentComponentId": null
        },
        {
          "bbox": {
            "h": 0.1,
            "w": 0.62,
            "x": 0.34,
            "y": 0.5
          },
          "kind": "paragraph",
          "text": "To estimate the potential impact of GenAI across occupations, we leveraged research from Michael Webb at Stanford. The analysis uses a verb-noun pairing framework covering over 800 occupations and their task descriptions from O*NET.",
          "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 18:01:19.097+00",
            "model": "google/gemini-3.1-flash-lite-preview-20260303",
            "runId": null,
            "seconds": null,
            "promptVersion": null
          },
          "componentId": "7d728401-6b67-4723-8944-a1b7c2e4456e",
          "parentComponentId": null
        },
        {
          "bbox": {
            "h": 0.06,
            "w": 0.62,
            "x": 0.34,
            "y": 0.43
          },
          "kind": "paragraph",
          "text": "Research shows most US jobs could have moderate to high exposure to AI, with high or very high augmentation for roughly a third of those.",
          "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 18:01:19.097+00",
            "model": "google/gemini-3.1-flash-lite-preview-20260303",
            "runId": null,
            "seconds": null,
            "promptVersion": null
          },
          "componentId": "dde7c7c7-c55c-4e0f-9f15-3e897bc8a10f",
          "parentComponentId": null
        },
        {
          "bbox": null,
          "kind": "quote",
          "text": "Webb, Michael, \"The Impact of Artificial Intelligence on the Labor Market,\" SSNR - Elsevier, 11 January 2020",
          "attrs": null,
          "canon": {
            "kind": {
              "name": "Quote",
              "slug": "quote",
              "status": "active",
              "canonId": "019de52c-f8fb-751e-8bc6-d58e2d59562a",
              "version": 1,
              "description": "Pull quote or testimonial."
            },
            "tool": {
              "name": "Authority citation",
              "slug": "authority-citation",
              "status": "active",
              "bestFor": null,
              "canonId": "019dd9e1-49ae-7557-89ad-3fca70469b45",
              "version": 1,
              "bodyDocId": null,
              "description": "Quoting an authority figure, study, or precedent to lend weight.",
              "familyLabel": null
            },
            "subkind": null,
            "framework": null
          },
          "subkind": null,
          "groupRole": null,
          "confidence": null,
          "extraction": {
            "at": "2026-04-24 16:10:25+00",
            "model": "or:google/gemini-3.1-flash-lite-preview",
            "runId": null,
            "seconds": null,
            "promptVersion": null
          },
          "componentId": "019dd952-2e35-763d-838d-1400f1de8e55",
          "parentComponentId": null
        },
        {
          "bbox": {
            "h": 0.03,
            "w": 0.62,
            "x": 0.34,
            "y": 0.92
          },
          "kind": "source-note",
          "text": "References: 1. Webb, Michael, 'The Impact of Artificial Intelligence on the Labor Market,' SSNR - Elsevier, 11 January 2020",
          "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 18:01:19.097+00",
            "model": "google/gemini-3.1-flash-lite-preview-20260303",
            "runId": null,
            "seconds": null,
            "promptVersion": null
          },
          "componentId": "de4b2035-2334-46d1-bd38-ada78a60a0f7",
          "parentComponentId": null
        },
        {
          "bbox": {
            "h": 0.06,
            "w": 0.62,
            "x": 0.34,
            "y": 0.345
          },
          "kind": "title",
          "text": "1. AI job augmentation potential: ubiquitous but heterogenous",
          "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 18:01:19.097+00",
            "model": "google/gemini-3.1-flash-lite-preview-20260303",
            "runId": null,
            "seconds": null,
            "promptVersion": null
          },
          "componentId": "51ac67a1-ac1a-401b-9504-3211e81498e6",
          "parentComponentId": null
        }
      ],
      "metrics": [],
      "tools": [
        {
          "tool": {
            "name": "Analytical method",
            "slug": "analytical-method",
            "status": "active",
            "bestFor": null,
            "canonId": "b42c4911-7946-49b5-951c-5f3d23f4e2bd",
            "version": 1,
            "bodyDocId": null,
            "description": "Diagnostic / structuring methods (5-whys, fishbone, issue tree, hypothesis-driven).",
            "familyLabel": null,
            "categoryName": null,
            "categorySlug": null
          },
          "agent": null,
          "layer": "slide",
          "agents": null,
          "matchId": "ef30d937-ca50-4338-989c-224d2461dfed",
          "evidence": "The verb-noun pairs are then compared to patents filed for AI technology... to see how exposed they are to AI.",
          "pageRefs": null,
          "priority": null,
          "whenToUse": null,
          "confidence": 0.7,
          "extraction": {
            "at": "2026-07-16 21:49:28.263681+00",
            "model": "or:meta-llama/llama-4-scout",
            "runId": null,
            "seconds": null,
            "promptVersion": null
          },
          "pageNumber": 4,
          "whyItWorks": null,
          "antipattern": null,
          "cardinality": "common",
          "narrativePurpose": null
        }
      ],
      "frameworks": [
        {
          "matchId": "c57cb48a-9cf0-401c-a5d2-b2951a91e0ee",
          "evidence": "Verb-noun pairing framework for occupational task analysis",
          "framework": null,
          "confidence": 0.9,
          "extraction": {
            "at": "2026-05-02 18:01:19.097+00",
            "model": "google/gemini-3.1-flash-lite-preview-20260303",
            "runId": null,
            "seconds": null,
            "promptVersion": null
          },
          "pageNumber": 4,
          "frameworkName": "analytical-method"
        }
      ],
      "arcBeats": [
        {
          "to": 5,
          "arc": {
            "name": "The Consultant's Gambit",
            "slug": "consultants-gambit",
            "status": "active",
            "bestFor": "Business cases, project proposals, strategic recommendations",
            "canonId": "019dd956-5e0a-73c8-b305-81c38c959e9c",
            "version": 1,
            "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49",
            "structure": "Situation & Context -> Problem & Complication -> Solution & Approach -> Evidence & Proof -> Impact & Next Steps",
            "description": null,
            "familyLabel": null
          },
          "from": 3,
          "name": "Problem & Complication",
          "beatId": "55069988-7d18-4303-b0f8-10d40c6fef58",
          "matchId": "424d33e4-517f-4ec9-b9d0-2d8a129b071e",
          "beatType": {
            "name": "Problem & Complication",
            "slug": "consultants-gambit-problem-complication",
            "status": "active",
            "canonId": "019dd9b8-064a-777f-a374-e9a8c43dedd4",
            "version": 1,
            "description": null
          },
          "evidence": "The key takeaways and data tables highlight the complex effects of GenAI on the labor market",
          "position": 1,
          "isPrimaryArc": true,
          "parentBeatType": {
            "name": "Complication",
            "slug": "complication",
            "status": "active",
            "canonId": "019dd9b8-0275-7709-b2d6-4f77c3fc7579",
            "version": 1,
            "description": "The point in the narrative where the audience should feel discomfort. Required for argumentative arcs."
          },
          "alignedBlockIds": null,
          "matchConfidence": 0.8
        }
      ],
      "loops": [
        {
          "to": 5,
          "from": 3,
          "loop": {
            "name": "01_logic_chain",
            "slug": "01-logic-chain",
            "status": "active",
            "bestFor": "Skeptical audiences, controversial recommendations, rigorous analysis",
            "canonId": "019dd956-6638-7457-8650-9b0b42e59fb3",
            "version": 1,
            "bodyDocId": "019df22a-2420-77be-bc41-ded96d08cb21",
            "structure": "Premise 1 (Accepted truth) -> Premise 2 (Observed fact) -> Therefore... (Inevitable conclusion)",
            "description": "Build an airtight chain of logic where each premise leads inevitably to the conclusion",
            "familyLabel": null
          },
          "matchId": "1679a32c-e543-4087-8767-8a695c8716c4",
          "evidence": "The key takeaways and data tables provide a logical chain of information",
          "position": 0,
          "objective": "What are the key findings of GenAI's potential impact on the labor market?",
          "confidence": 0.7,
          "extraction": {
            "at": "2026-07-16 21:19:48.518043+00",
            "model": "or:meta-llama/llama-4-scout",
            "runId": null,
            "seconds": null,
            "promptVersion": "doc-narrative-v1"
          }
        }
      ],
      "locked": true
    },
    {
      "page": 5,
      "type": "analysis",
      "title": "The chart plots rescaled AI augmentation score (y-axis) against cumulative US employment share (x-axis).",
      "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": 74,
        "componentCount": 7,
        "textChars": 1291,
        "nDataPoints": 12,
        "notes": "The chart plots rescaled AI augmentation score (y-axis) against cumulative US employment share (x-axis).",
        "elementsJson": [
          "headline_text",
          "paragraph",
          "line_chart",
          "footnote"
        ],
        "confidence": 1,
        "extraction": {
          "model": "google/gemini-3.1-flash-lite-preview-20260303",
          "runId": null,
          "at": "2026-05-02 18:01:17.806+00",
          "seconds": 2.622,
          "promptVersion": "v2-canon-conditioned"
        }
      },
      "links": {
        "slide": "/slides/019dd923-5e88-73ef-bd59-b7c870c8c8e8/5",
        "deck": "/decks/019dd923-5e88-73ef-bd59-b7c870c8c8e8",
        "deckAnchor": "/decks/019dd923-5e88-73ef-bd59-b7c870c8c8e8#slide-5",
        "deckJson": "/decks/019dd923-5e88-73ef-bd59-b7c870c8c8e8.json"
      },
      "components": [
        {
          "bbox": null,
          "kind": "callout",
          "text": "Our findings are quite striking, with 66% of US employment with moderate to high GenAI exposure, or the equivalent of 104 million jobs across the country.",
          "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": "2026-04-24 16:10:25+00",
            "model": "or:google/gemini-3.1-flash-lite-preview",
            "runId": null,
            "seconds": null,
            "promptVersion": null
          },
          "componentId": "019dd952-2e35-763d-838c-bb12a4119392",
          "parentComponentId": null
        },
        {
          "bbox": {
            "h": 0.25,
            "w": 0.58,
            "x": 0.343,
            "y": 0.298
          },
          "kind": "chart",
          "text": "Chart 1: US cumulative employment by rescaled AI augmentation score",
          "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": "Line chart",
              "slug": "line",
              "status": "active",
              "canonId": "019de52c-ff62-778f-8f6c-a952ceae8677",
              "version": 1,
              "description": null
            },
            "framework": null
          },
          "subkind": "line",
          "groupRole": null,
          "confidence": null,
          "extraction": {
            "at": "2026-05-02 18:01:17.806+00",
            "model": "google/gemini-3.1-flash-lite-preview-20260303",
            "runId": null,
            "seconds": null,
            "promptVersion": null
          },
          "componentId": "384a65c5-a585-4dda-bcc2-7e67f215522b",
          "parentComponentId": null
        },
        {
          "bbox": null,
          "kind": "metric",
          "text": "US employment share: 66%",
          "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": "2026-04-24 16:10:25+00",
            "model": "or:google/gemini-3.1-flash-lite-preview",
            "runId": null,
            "seconds": null,
            "promptVersion": null
          },
          "componentId": "019dd952-2e35-763d-838c-be3f5742f848",
          "parentComponentId": null
        },
        {
          "bbox": {
            "h": 0.1,
            "w": 0.58,
            "x": 0.343,
            "y": 0.157
          },
          "kind": "paragraph",
          "text": "Our findings are quite striking, with 66% of US employment with moderate to high GenAI exposure, or the equivalent of 104 million jobs across the country (Chart 1). Within those, roughly 18% of total employment, or 28 million jobs, would have a high AI augmentation score, and 5% of employment, or 8 million jobs, would have a very high augmentation score. Importantly, the remaining 34%, which have the lowest AI-exposure score, could still be marginally affected by AI via some secondary tasks.",
          "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 18:01:17.806+00",
            "model": "google/gemini-3.1-flash-lite-preview-20260303",
            "runId": null,
            "seconds": null,
            "promptVersion": null
          },
          "componentId": "2457d9b4-822a-4552-89aa-b4f72894462e",
          "parentComponentId": null
        },
        {
          "bbox": {
            "h": 0.1,
            "w": 0.58,
            "x": 0.343,
            "y": 0.662
          },
          "kind": "paragraph",
          "text": "Using the International Labor Organization's International Standard Industrial Classification of all economic activities, we then applied the raw AI augmentation scores across industries in 80 economies worldwide. We assumed that in emerging markets the agriculture, forestry and fishing sector had a low AI exposure score. Our findings show that globally about 59% of the workforce is highly or moderately exposed to GenAI, with 67% in developed economies and 57% across emerging economies.",
          "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 18:01:17.806+00",
            "model": "google/gemini-3.1-flash-lite-preview-20260303",
            "runId": null,
            "seconds": null,
            "promptVersion": null
          },
          "componentId": "892d644a-c361-4efd-ab3c-4ef75c1e6569",
          "parentComponentId": null
        },
        {
          "bbox": {
            "h": 0.02,
            "w": 0.1,
            "x": 0.343,
            "y": 0.615
          },
          "kind": "source-note",
          "text": "Source: EY-Parthenon",
          "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 18:01:17.806+00",
            "model": "google/gemini-3.1-flash-lite-preview-20260303",
            "runId": null,
            "seconds": null,
            "promptVersion": null
          },
          "componentId": "0c6b731e-1639-45a0-a7f6-288404df8283",
          "parentComponentId": null
        },
        {
          "bbox": {
            "h": 0.02,
            "w": 0.3,
            "x": 0.07,
            "y": 0.04
          },
          "kind": "title",
          "text": "The impact of GenAI on the labor 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 18:01:17.806+00",
            "model": "google/gemini-3.1-flash-lite-preview-20260303",
            "runId": null,
            "seconds": null,
            "promptVersion": null
          },
          "componentId": "15213947-70ff-404f-ad2b-98e20cc81d55",
          "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": "22840f89-f369-4412-b8e4-20d6add05f4c",
          "evidence": "Chart 1: US cumulative employment by rescaled AI augmentation score",
          "pageRefs": null,
          "priority": null,
          "whenToUse": null,
          "confidence": 0.7,
          "extraction": {
            "at": "2026-07-16 21:49:28.36906+00",
            "model": "or:meta-llama/llama-4-scout",
            "runId": null,
            "seconds": null,
            "promptVersion": null
          },
          "pageNumber": 5,
          "whyItWorks": null,
          "antipattern": null,
          "cardinality": null,
          "narrativePurpose": null
        },
        {
          "tool": {
            "name": "Data Story Arc",
            "slug": "data-story-arc",
            "status": "active",
            "bestFor": null,
            "canonId": "019dd956-9c30-728e-b974-d3fb123dcf5a",
            "version": 1,
            "bodyDocId": null,
            "description": "Context → Conflict → Insight → Implication structure for data narratives",
            "familyLabel": null,
            "categoryName": "Loop",
            "categorySlug": "loop"
          },
          "agent": "Storyteller",
          "layer": "slide",
          "agents": [
            "Storyteller"
          ],
          "matchId": "24a8d538-2b17-4eca-9b2e-92047408983e",
          "evidence": "Our findings are quite striking, with 66% of US employment with moderate to high GenAI exposure, or the equivalent of 104 million jobs across the country (Chart 1).",
          "pageRefs": null,
          "priority": "Core",
          "whenToUse": null,
          "confidence": 0.7,
          "extraction": {
            "at": "2026-07-16 21:49:28.333986+00",
            "model": "or:meta-llama/llama-4-scout",
            "runId": null,
            "seconds": null,
            "promptVersion": null
          },
          "pageNumber": 5,
          "whyItWorks": null,
          "antipattern": null,
          "cardinality": null,
          "narrativePurpose": null
        }
      ],
      "frameworks": [],
      "arcBeats": [
        {
          "to": 5,
          "arc": {
            "name": "The Consultant's Gambit",
            "slug": "consultants-gambit",
            "status": "active",
            "bestFor": "Business cases, project proposals, strategic recommendations",
            "canonId": "019dd956-5e0a-73c8-b305-81c38c959e9c",
            "version": 1,
            "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49",
            "structure": "Situation & Context -> Problem & Complication -> Solution & Approach -> Evidence & Proof -> Impact & Next Steps",
            "description": null,
            "familyLabel": null
          },
          "from": 3,
          "name": "Problem & Complication",
          "beatId": "55069988-7d18-4303-b0f8-10d40c6fef58",
          "matchId": "424d33e4-517f-4ec9-b9d0-2d8a129b071e",
          "beatType": {
            "name": "Problem & Complication",
            "slug": "consultants-gambit-problem-complication",
            "status": "active",
            "canonId": "019dd9b8-064a-777f-a374-e9a8c43dedd4",
            "version": 1,
            "description": null
          },
          "evidence": "The key takeaways and data tables highlight the complex effects of GenAI on the labor market",
          "position": 1,
          "isPrimaryArc": true,
          "parentBeatType": {
            "name": "Complication",
            "slug": "complication",
            "status": "active",
            "canonId": "019dd9b8-0275-7709-b2d6-4f77c3fc7579",
            "version": 1,
            "description": "The point in the narrative where the audience should feel discomfort. Required for argumentative arcs."
          },
          "alignedBlockIds": null,
          "matchConfidence": 0.8
        }
      ],
      "loops": [
        {
          "to": 5,
          "from": 3,
          "loop": {
            "name": "01_logic_chain",
            "slug": "01-logic-chain",
            "status": "active",
            "bestFor": "Skeptical audiences, controversial recommendations, rigorous analysis",
            "canonId": "019dd956-6638-7457-8650-9b0b42e59fb3",
            "version": 1,
            "bodyDocId": "019df22a-2420-77be-bc41-ded96d08cb21",
            "structure": "Premise 1 (Accepted truth) -> Premise 2 (Observed fact) -> Therefore... (Inevitable conclusion)",
            "description": "Build an airtight chain of logic where each premise leads inevitably to the conclusion",
            "familyLabel": null
          },
          "matchId": "1679a32c-e543-4087-8767-8a695c8716c4",
          "evidence": "The key takeaways and data tables provide a logical chain of information",
          "position": 0,
          "objective": "What are the key findings of GenAI's potential impact on the labor market?",
          "confidence": 0.7,
          "extraction": {
            "at": "2026-07-16 21:19:48.518043+00",
            "model": "or:meta-llama/llama-4-scout",
            "runId": null,
            "seconds": null,
            "promptVersion": "doc-narrative-v1"
          }
        }
      ],
      "locked": true
    },
    {
      "page": 6,
      "type": "analysis",
      "title": "The chart illustrates the varying degrees of AI impact on labor markets across different economic 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": 6,
        "textChars": 238,
        "nDataPoints": 12,
        "notes": "The chart illustrates the varying degrees of AI impact on labor markets across different economic regions.",
        "elementsJson": [
          "bar_chart_stacked",
          "photo"
        ],
        "confidence": 1,
        "extraction": {
          "model": "google/gemini-3.1-flash-lite-preview-20260303",
          "runId": null,
          "at": "2026-05-02 18:01:17.821+00",
          "seconds": 2.563,
          "promptVersion": "v2-canon-conditioned"
        }
      },
      "links": {
        "slide": "/slides/019dd923-5e88-73ef-bd59-b7c870c8c8e8/6",
        "deck": "/decks/019dd923-5e88-73ef-bd59-b7c870c8c8e8",
        "deckAnchor": "/decks/019dd923-5e88-73ef-bd59-b7c870c8c8e8#slide-6",
        "deckJson": "/decks/019dd923-5e88-73ef-bd59-b7c870c8c8e8.json"
      },
      "components": [
        {
          "bbox": {
            "h": 0.31,
            "w": 0.58,
            "x": 0.34,
            "y": 0.16
          },
          "kind": "chart",
          "text": "Stacked bar chart showing employment exposure 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": "Stacked bar chart",
              "slug": "bar-stacked",
              "status": "active",
              "canonId": "019de52c-feec-74bf-9028-15b74f84f0a7",
              "version": 1,
              "description": null
            },
            "framework": null
          },
          "subkind": "bar-stacked",
          "groupRole": null,
          "confidence": null,
          "extraction": {
            "at": "2026-05-02 18:01:17.821+00",
            "model": "google/gemini-3.1-flash-lite-preview-20260303",
            "runId": null,
            "seconds": null,
            "promptVersion": null
          },
          "componentId": "6cc11a05-3221-4523-927f-642633db5f17",
          "parentComponentId": null
        },
        {
          "bbox": {
            "h": 0.38,
            "w": 0.86,
            "x": 0.07,
            "y": 0.55
          },
          "kind": "image",
          "text": "Office setting with people working on laptops",
          "attrs": null,
          "canon": {
            "kind": {
              "name": "Image",
              "slug": "image",
              "status": "active",
              "canonId": "019de52c-f978-701f-a720-51d029d769e7",
              "version": 1,
              "description": "Photo, illustration, screenshot or icon."
            },
            "tool": null,
            "subkind": {
              "name": "Photo",
              "slug": "photo",
              "status": "active",
              "canonId": "019de52c-fd37-757f-b4a8-ca26d4888875",
              "version": 1,
              "description": null
            },
            "framework": null
          },
          "subkind": "photo",
          "groupRole": null,
          "confidence": null,
          "extraction": {
            "at": "2026-05-02 18:01:17.821+00",
            "model": "google/gemini-3.1-flash-lite-preview-20260303",
            "runId": null,
            "seconds": null,
            "promptVersion": null
          },
          "componentId": "9bd2e2e7-bf36-4865-9af4-56f97d8461d5",
          "parentComponentId": null
        },
        {
          "bbox": {
            "h": 0.02,
            "w": 0.45,
            "x": 0.34,
            "y": 0.47
          },
          "kind": "legend",
          "text": "Low exposure; Medium exposure; High exposure",
          "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 18:01:17.821+00",
            "model": "google/gemini-3.1-flash-lite-preview-20260303",
            "runId": null,
            "seconds": null,
            "promptVersion": null
          },
          "componentId": "bcbaef90-a512-456c-a466-a3ca3cc7b608",
          "parentComponentId": null
        },
        {
          "bbox": null,
          "kind": "metric",
          "text": "Share of employment: 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": "2026-04-24 16:10:29+00",
            "model": "or:google/gemini-3.1-flash-lite-preview",
            "runId": null,
            "seconds": null,
            "promptVersion": null
          },
          "componentId": "019dd952-2e37-719d-8bdc-ee0db4ef6377",
          "parentComponentId": null
        },
        {
          "bbox": {
            "h": 0.01,
            "w": 0.1,
            "x": 0.34,
            "y": 0.51
          },
          "kind": "source-note",
          "text": "Source: EY-Parthenon",
          "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 18:01:17.821+00",
            "model": "google/gemini-3.1-flash-lite-preview-20260303",
            "runId": null,
            "seconds": null,
            "promptVersion": null
          },
          "componentId": "04582a71-9414-467e-a51c-bd5f46062c9b",
          "parentComponentId": null
        },
        {
          "bbox": {
            "h": 0.03,
            "w": 0.25,
            "x": 0.07,
            "y": 0.17
          },
          "kind": "title",
          "text": "Chart 2: Share of employment by AI augmentation score",
          "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 18:01:17.821+00",
            "model": "google/gemini-3.1-flash-lite-preview-20260303",
            "runId": null,
            "seconds": null,
            "promptVersion": null
          },
          "componentId": "2022d0f0-5c03-4649-8f96-ec9952fa505d",
          "parentComponentId": null
        }
      ],
      "metrics": [],
      "tools": [],
      "frameworks": [],
      "arcBeats": [
        {
          "to": 10,
          "arc": {
            "name": "The Consultant's Gambit",
            "slug": "consultants-gambit",
            "status": "active",
            "bestFor": "Business cases, project proposals, strategic recommendations",
            "canonId": "019dd956-5e0a-73c8-b305-81c38c959e9c",
            "version": 1,
            "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49",
            "structure": "Situation & Context -> Problem & Complication -> Solution & Approach -> Evidence & Proof -> Impact & Next Steps",
            "description": null,
            "familyLabel": null
          },
          "from": 6,
          "name": "Evidence & Proof",
          "beatId": "50595e69-1a4c-4b7a-9db4-2a10a64a59c8",
          "matchId": "424d33e4-517f-4ec9-b9d0-2d8a129b071e",
          "beatType": {
            "name": "Evidence & Proof",
            "slug": "consultants-gambit-evidence-proof",
            "status": "active",
            "canonId": "019dd9b8-07b1-7688-8e1e-7637fec3802a",
            "version": 1,
            "description": null
          },
          "evidence": "The data tables and industry trends provide evidence of GenAI's impact on various sectors",
          "position": 2,
          "isPrimaryArc": true,
          "parentBeatType": {
            "name": "Evidence",
            "slug": "evidence",
            "status": "active",
            "canonId": "019dd9b8-03f9-772a-b84a-4f07b415b77a",
            "version": 1,
            "description": "A dedicated proof beat exists in only ~4 arcs (Gambit, Sequoia, AIDA, Monroes). Other arcs embed evidence inline within development."
          },
          "alignedBlockIds": null,
          "matchConfidence": 0.8
        }
      ],
      "loops": [],
      "locked": true
    },
    {
      "page": 7,
      "type": "analysis",
      "title": "The slide sets up a methodology for future analysis using Fernald (2014) growth accounting.",
      "function": "analyze_data",
      "rawType": "scenario_analysis",
      "block": null,
      "metadata": {
        "slideType": "scenario_analysis",
        "slideTypeCanon": {
          "name": "Scenario analysis",
          "slug": "scenario_analysis",
          "status": "active",
          "canonId": "019de52d-0d4d-7022-a603-242c1dd0d760",
          "version": 1,
          "description": null
        },
        "function": "analyze_data",
        "functionCanon": {
          "name": "Analyze data",
          "slug": "analyze_data",
          "status": "active",
          "canonId": "019de52d-1590-7413-8c82-cc218cff40b4",
          "version": 1,
          "description": null
        },
        "density": "overcrowded",
        "densityScore": 79,
        "componentCount": 8,
        "textChars": 1267,
        "nDataPoints": 2,
        "notes": "The slide sets up a methodology for future analysis using Fernald (2014) growth accounting.",
        "elementsJson": [
          "paragraph",
          "photo"
        ],
        "confidence": 0.9,
        "extraction": {
          "model": "google/gemini-3.1-flash-lite-preview-20260303",
          "runId": null,
          "at": "2026-05-02 18:01:22.522+00",
          "seconds": 7.256,
          "promptVersion": "v2-canon-conditioned"
        }
      },
      "links": {
        "slide": "/slides/019dd923-5e88-73ef-bd59-b7c870c8c8e8/7",
        "deck": "/decks/019dd923-5e88-73ef-bd59-b7c870c8c8e8",
        "deckAnchor": "/decks/019dd923-5e88-73ef-bd59-b7c870c8c8e8#slide-7",
        "deckJson": "/decks/019dd923-5e88-73ef-bd59-b7c870c8c8e8.json"
      },
      "components": [
        {
          "bbox": null,
          "kind": "callout",
          "text": "With GenAI improving efficiency and accuracy, workers can transform their roles by focusing on what humans do best.",
          "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": "2026-04-24 16:10:25+00",
            "model": "or:google/gemini-3.1-flash-lite-preview",
            "runId": null,
            "seconds": null,
            "promptVersion": null
          },
          "componentId": "019dd952-2e35-763d-838c-d9f1e8343256",
          "parentComponentId": null
        },
        {
          "bbox": {
            "h": 0.41,
            "w": 1,
            "x": 0,
            "y": 0.59
          },
          "kind": "image",
          "text": null,
          "attrs": null,
          "canon": {
            "kind": {
              "name": "Image",
              "slug": "image",
              "status": "active",
              "canonId": "019de52c-f978-701f-a720-51d029d769e7",
              "version": 1,
              "description": "Photo, illustration, screenshot or icon."
            },
            "tool": null,
            "subkind": {
              "name": "Photo",
              "slug": "photo",
              "status": "active",
              "canonId": "019de52c-fd37-757f-b4a8-ca26d4888875",
              "version": 1,
              "description": null
            },
            "framework": null
          },
          "subkind": "photo",
          "groupRole": null,
          "confidence": null,
          "extraction": {
            "at": "2026-05-02 18:01:22.522+00",
            "model": "google/gemini-3.1-flash-lite-preview-20260303",
            "runId": null,
            "seconds": null,
            "promptVersion": null
          },
          "componentId": "b5785028-18f9-4ea4-9dee-482e9c95fde1",
          "parentComponentId": null
        },
        {
          "bbox": {
            "h": 0.06,
            "w": 0.315,
            "x": 0.343,
            "y": 0.29
          },
          "kind": "paragraph",
          "text": "By executing and automating complex cognitive tasks that previously only humans could perform, GenAI has the potential to enhance workers' efficiency, accelerate capital deepening and unlock substantial productivity gains across the economy.",
          "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 18:01:22.522+00",
            "model": "google/gemini-3.1-flash-lite-preview-20260303",
            "runId": null,
            "seconds": null,
            "promptVersion": null
          },
          "componentId": "38bcea1f-4099-46c8-a884-dc4b08a86ca5",
          "parentComponentId": null
        },
        {
          "bbox": {
            "h": 0.05,
            "w": 0.315,
            "x": 0.343,
            "y": 0.22
          },
          "kind": "paragraph",
          "text": "With GenAI improving efficiency and accuracy, workers can transform their roles by focusing on what humans do best.",
          "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 18:01:22.522+00",
            "model": "google/gemini-3.1-flash-lite-preview-20260303",
            "runId": null,
            "seconds": null,
            "promptVersion": null
          },
          "componentId": "7550b2ff-5ae0-4410-aee9-9dab8473e13d",
          "parentComponentId": null
        },
        {
          "bbox": {
            "h": 0.08,
            "w": 0.315,
            "x": 0.343,
            "y": 0.375
          },
          "kind": "paragraph",
          "text": "In assessing the potential economic impact of GenAI from a productivity perspective, it is worthwhile to consider the TFP dynamics observed during the ICT revolution. From the early 1970s through 1995, TFP rose about 0.7% per year. But that pace more than doubled to a rate of 1.3% between 1995 and 2003.",
          "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 18:01:22.522+00",
            "model": "google/gemini-3.1-flash-lite-preview-20260303",
            "runId": null,
            "seconds": null,
            "promptVersion": null
          },
          "componentId": "bc36b5b0-f46a-48b4-b230-f9598434db81",
          "parentComponentId": null
        },
        {
          "bbox": {
            "h": 0.1,
            "w": 0.315,
            "x": 0.343,
            "y": 0.45
          },
          "kind": "paragraph",
          "text": "Using the ICT period as a reference, we created three scenarios - trend, revival (our baseline) and boom - that correspond to three different productivity outcomes for the next decade. Our analysis builds on the scenarios developed in the previous chapter on capital investment. We then estimated the growth effects of these productivity scenarios on long-run GDP growth using a growth accounting approach such as Fernald (2014).",
          "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 18:01:22.522+00",
            "model": "google/gemini-3.1-flash-lite-preview-20260303",
            "runId": null,
            "seconds": null,
            "promptVersion": null
          },
          "componentId": "f10052f3-325f-4ac2-a278-6c8bf6da0385",
          "parentComponentId": null
        },
        {
          "bbox": {
            "h": 0.025,
            "w": 0.315,
            "x": 0.343,
            "y": 0.165
          },
          "kind": "title",
          "text": "2. Plenty of skills in the game across sectors",
          "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 18:01:22.522+00",
            "model": "google/gemini-3.1-flash-lite-preview-20260303",
            "runId": null,
            "seconds": null,
            "promptVersion": null
          },
          "componentId": "e42e18ed-ad3f-40a2-be3e-7eb9aeab3fae",
          "parentComponentId": null
        },
        {
          "bbox": {
            "h": 0.02,
            "w": 0.1,
            "x": 0.343,
            "y": 0.35
          },
          "kind": "title",
          "text": "Scenario analysis",
          "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 18:01:22.522+00",
            "model": "google/gemini-3.1-flash-lite-preview-20260303",
            "runId": null,
            "seconds": null,
            "promptVersion": null
          },
          "componentId": "de6c0a18-38ca-4327-aec4-2087fa08b8ac",
          "parentComponentId": null
        }
      ],
      "metrics": [],
      "tools": [
        {
          "tool": {
            "name": "Scenario Analysis",
            "slug": "scenario-analysis",
            "status": "active",
            "bestFor": null,
            "canonId": "ca76b81a-ec1d-403f-b1e6-8d6eec3bf93e",
            "version": 1,
            "bodyDocId": null,
            "description": null,
            "familyLabel": null,
            "categoryName": null,
            "categorySlug": null
          },
          "agent": null,
          "layer": "slide",
          "agents": null,
          "matchId": "25cd904e-13e5-493d-b36c-3749ff359c7a",
          "evidence": "Using the ICT period as a reference, we created three scenarios - trend, revival (our baseline) and boom - that correspond to three different productivity outcomes for the next decade.",
          "pageRefs": null,
          "priority": null,
          "whenToUse": null,
          "confidence": 0.9,
          "extraction": {
            "at": "2026-07-16 21:49:28.468182+00",
            "model": "or:meta-llama/llama-4-scout",
            "runId": null,
            "seconds": null,
            "promptVersion": null
          },
          "pageNumber": 7,
          "whyItWorks": null,
          "antipattern": null,
          "cardinality": null,
          "narrativePurpose": null
        }
      ],
      "frameworks": [
        {
          "matchId": "6a038329-3c6b-4672-b261-c31ec781c1aa",
          "evidence": "Mentions creating three scenarios (trend, revival, boom) based on historical ICT data.",
          "framework": null,
          "confidence": 1,
          "extraction": {
            "at": "2026-05-02 18:01:22.522+00",
            "model": "google/gemini-3.1-flash-lite-preview-20260303",
            "runId": null,
            "seconds": null,
            "promptVersion": null
          },
          "pageNumber": 7,
          "frameworkName": "scenario_analysis"
        }
      ],
      "arcBeats": [
        {
          "to": 10,
          "arc": {
            "name": "The Consultant's Gambit",
            "slug": "consultants-gambit",
            "status": "active",
            "bestFor": "Business cases, project proposals, strategic recommendations",
            "canonId": "019dd956-5e0a-73c8-b305-81c38c959e9c",
            "version": 1,
            "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49",
            "structure": "Situation & Context -> Problem & Complication -> Solution & Approach -> Evidence & Proof -> Impact & Next Steps",
            "description": null,
            "familyLabel": null
          },
          "from": 6,
          "name": "Evidence & Proof",
          "beatId": "50595e69-1a4c-4b7a-9db4-2a10a64a59c8",
          "matchId": "424d33e4-517f-4ec9-b9d0-2d8a129b071e",
          "beatType": {
            "name": "Evidence & Proof",
            "slug": "consultants-gambit-evidence-proof",
            "status": "active",
            "canonId": "019dd9b8-07b1-7688-8e1e-7637fec3802a",
            "version": 1,
            "description": null
          },
          "evidence": "The data tables and industry trends provide evidence of GenAI's impact on various sectors",
          "position": 2,
          "isPrimaryArc": true,
          "parentBeatType": {
            "name": "Evidence",
            "slug": "evidence",
            "status": "active",
            "canonId": "019dd9b8-03f9-772a-b84a-4f07b415b77a",
            "version": 1,
            "description": "A dedicated proof beat exists in only ~4 arcs (Gambit, Sequoia, AIDA, Monroes). Other arcs embed evidence inline within development."
          },
          "alignedBlockIds": null,
          "matchConfidence": 0.8
        }
      ],
      "loops": [],
      "locked": true
    },
    {
      "page": 8,
      "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": "overcrowded",
        "densityScore": 83,
        "componentCount": 8,
        "textChars": 1515,
        "nDataPoints": 10,
        "notes": null,
        "elementsJson": [
          "headline_text",
          "paragraph",
          "bar_chart_horizontal",
          "footnote"
        ],
        "confidence": 1,
        "extraction": {
          "model": "google/gemini-3.1-flash-lite-preview-20260303",
          "runId": null,
          "at": "2026-05-02 18:01:18.432+00",
          "seconds": 3.147,
          "promptVersion": "v2-canon-conditioned"
        }
      },
      "links": {
        "slide": "/slides/019dd923-5e88-73ef-bd59-b7c870c8c8e8/8",
        "deck": "/decks/019dd923-5e88-73ef-bd59-b7c870c8c8e8",
        "deckAnchor": "/decks/019dd923-5e88-73ef-bd59-b7c870c8c8e8#slide-8",
        "deckJson": "/decks/019dd923-5e88-73ef-bd59-b7c870c8c8e8.json"
      },
      "components": [
        {
          "bbox": null,
          "kind": "callout",
          "text": "Programming and mathematics present the highest correlation with our GenAI augmentation score, while active listening and speaking rank the lowest.",
          "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": "2026-04-24 16:10:25+00",
            "model": "or:google/gemini-3.1-flash-lite-preview",
            "runId": null,
            "seconds": null,
            "promptVersion": null
          },
          "componentId": "019dd952-2e35-763d-838c-f39851bce554",
          "parentComponentId": null
        },
        {
          "bbox": {
            "h": 0.35,
            "w": 0.55,
            "x": 0.343,
            "y": 0.515
          },
          "kind": "chart",
          "text": "Chart 3: Regression coefficients of labor skills contributing to AI augmentation scores",
          "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 18:01:18.432+00",
            "model": "google/gemini-3.1-flash-lite-preview-20260303",
            "runId": null,
            "seconds": null,
            "promptVersion": null
          },
          "componentId": "c57ab87b-a543-4bbe-be2e-0b552b3e893b",
          "parentComponentId": null
        },
        {
          "bbox": null,
          "kind": "metric",
          "text": "Regression coefficients: 0.072",
          "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": "2026-04-24 16:10:25+00",
            "model": "or:google/gemini-3.1-flash-lite-preview",
            "runId": null,
            "seconds": null,
            "promptVersion": null
          },
          "componentId": "019dd952-2e35-763d-838c-f7a730199c51",
          "parentComponentId": null
        },
        {
          "bbox": {
            "h": 0.08,
            "w": 0.55,
            "x": 0.343,
            "y": 0.183
          },
          "kind": "paragraph",
          "text": "The role of GenAI in augmenting human skills varies significantly across different domains, reflecting the diverse capabilities and limitations of AI technologies. Unsurprisingly, looking at a subset of 10 human skills, we find that programming and mathematics present the highest correlation with our GenAI augmentation score, while active listening and speaking rank the lowest (Chart 3).",
          "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 18:01:18.432+00",
            "model": "google/gemini-3.1-flash-lite-preview-20260303",
            "runId": null,
            "seconds": null,
            "promptVersion": null
          },
          "componentId": "d6917a5c-ac95-49ae-90d3-6026c03a0b54",
          "parentComponentId": null
        },
        {
          "bbox": {
            "h": 0.08,
            "w": 0.55,
            "x": 0.343,
            "y": 0.275
          },
          "kind": "paragraph",
          "text": "GenAI's ability to automate coding tasks, such as debugging and writing simple code, enhances productivity and allows programmers to concentrate on complex, creative aspects of software development. Similarly, in mathematics, AI excels in performing complex calculations quickly and accurately, proving invaluable in data-intensive tasks.",
          "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 18:01:18.432+00",
            "model": "google/gemini-3.1-flash-lite-preview-20260303",
            "runId": null,
            "seconds": null,
            "promptVersion": null
          },
          "componentId": "ed260e60-c864-4780-9346-d0ad4369fb31",
          "parentComponentId": null
        },
        {
          "bbox": {
            "h": 0.08,
            "w": 0.55,
            "x": 0.343,
            "y": 0.367
          },
          "kind": "paragraph",
          "text": "Conversely, areas such as learning strategies, speaking and active listening exhibit lower AI augmentation scores. While AI can support learning and communication processes, it still requires significant human input and oversight, particularly in tasks involving complex human interaction, creativity and emotional understanding. These scores underline the ongoing potential of AI technologies and their varying degrees of impact across the skills spectrum.",
          "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 18:01:18.432+00",
            "model": "google/gemini-3.1-flash-lite-preview-20260303",
            "runId": null,
            "seconds": null,
            "promptVersion": null
          },
          "componentId": "ef877c9b-cf81-46d1-83a1-11b7f9949921",
          "parentComponentId": null
        },
        {
          "bbox": {
            "h": 0.01,
            "w": 0.1,
            "x": 0.343,
            "y": 0.845
          },
          "kind": "source-note",
          "text": "Source: EY-Parthenon",
          "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 18:01:18.432+00",
            "model": "google/gemini-3.1-flash-lite-preview-20260303",
            "runId": null,
            "seconds": null,
            "promptVersion": null
          },
          "componentId": "4b27071c-9f37-485d-afcc-33d09720a975",
          "parentComponentId": null
        },
        {
          "bbox": {
            "h": 0.015,
            "w": 0.33,
            "x": 0.343,
            "y": 0.158
          },
          "kind": "title",
          "text": "Departing from the low-skill obsolescence myth",
          "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 18:01:18.432+00",
            "model": "google/gemini-3.1-flash-lite-preview-20260303",
            "runId": null,
            "seconds": null,
            "promptVersion": null
          },
          "componentId": "cd0b4dbc-5970-4278-a317-3a1980df0643",
          "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": "76f6c1bb-8779-4932-9683-7c44a4ac8773",
          "evidence": "Chart 3: Regression coefficients of labor skills contributing to AI augmentation scores",
          "pageRefs": null,
          "priority": null,
          "whenToUse": null,
          "confidence": 0.7,
          "extraction": {
            "at": "2026-07-16 21:49:28.534355+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": 10,
          "arc": {
            "name": "The Consultant's Gambit",
            "slug": "consultants-gambit",
            "status": "active",
            "bestFor": "Business cases, project proposals, strategic recommendations",
            "canonId": "019dd956-5e0a-73c8-b305-81c38c959e9c",
            "version": 1,
            "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49",
            "structure": "Situation & Context -> Problem & Complication -> Solution & Approach -> Evidence & Proof -> Impact & Next Steps",
            "description": null,
            "familyLabel": null
          },
          "from": 6,
          "name": "Evidence & Proof",
          "beatId": "50595e69-1a4c-4b7a-9db4-2a10a64a59c8",
          "matchId": "424d33e4-517f-4ec9-b9d0-2d8a129b071e",
          "beatType": {
            "name": "Evidence & Proof",
            "slug": "consultants-gambit-evidence-proof",
            "status": "active",
            "canonId": "019dd9b8-07b1-7688-8e1e-7637fec3802a",
            "version": 1,
            "description": null
          },
          "evidence": "The data tables and industry trends provide evidence of GenAI's impact on various sectors",
          "position": 2,
          "isPrimaryArc": true,
          "parentBeatType": {
            "name": "Evidence",
            "slug": "evidence",
            "status": "active",
            "canonId": "019dd9b8-03f9-772a-b84a-4f07b415b77a",
            "version": 1,
            "description": "A dedicated proof beat exists in only ~4 arcs (Gambit, Sequoia, AIDA, Monroes). Other arcs embed evidence inline within development."
          },
          "alignedBlockIds": null,
          "matchConfidence": 0.8
        }
      ],
      "loops": [],
      "locked": true
    },
    {
      "page": 9,
      "type": "analysis",
      "title": "The chart uses a dot plot to show min, median, and max scores for each occupation group.",
      "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": 57,
        "componentCount": 6,
        "textChars": 602,
        "nDataPoints": 66,
        "notes": "The chart uses a dot plot to show min, median, and max scores for each occupation group.",
        "elementsJson": [
          "headline_text",
          "paragraph",
          "scatter_plot"
        ],
        "confidence": 1,
        "extraction": {
          "model": "google/gemini-3.1-flash-lite-preview-20260303",
          "runId": null,
          "at": "2026-05-02 18:01:18.059+00",
          "seconds": 2.601,
          "promptVersion": "v2-canon-conditioned"
        }
      },
      "links": {
        "slide": "/slides/019dd923-5e88-73ef-bd59-b7c870c8c8e8/9",
        "deck": "/decks/019dd923-5e88-73ef-bd59-b7c870c8c8e8",
        "deckAnchor": "/decks/019dd923-5e88-73ef-bd59-b7c870c8c8e8#slide-9",
        "deckJson": "/decks/019dd923-5e88-73ef-bd59-b7c870c8c8e8.json"
      },
      "components": [
        {
          "bbox": null,
          "kind": "callout",
          "text": "GenAI is transforming the workforce by enabling workers to delegate routine, data-heavy tasks to GenAI systems, thereby enhancing their focus on areas where human skills like strategic thinking, empathy and creativity are paramount.",
          "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": "2026-04-24 16:10:25+00",
            "model": "or:google/gemini-3.1-flash-lite-preview",
            "runId": null,
            "seconds": null,
            "promptVersion": null
          },
          "componentId": "019dd952-2e36-76f2-aee1-61ad394bb696",
          "parentComponentId": null
        },
        {
          "bbox": {
            "h": 0.25,
            "w": 0.55,
            "x": 0.365,
            "y": 0.625
          },
          "kind": "chart",
          "text": "Chart 4: Median, max and min rescaled AI augmentation scores across 22 US “major occupation groups”",
          "attrs": null,
          "canon": {
            "kind": {
              "name": "Chart",
              "slug": "chart",
              "status": "active",
              "canonId": "019de52c-f9a0-76ef-adc6-0b859109d1f8",
              "version": 1,
              "description": "Quantitative chart."
            },
            "tool": null,
            "subkind": {
              "name": "Dot plot",
              "slug": "dot",
              "status": "active",
              "canonId": "019de52d-0235-738b-bd2b-78f8e24d7cb0",
              "version": 1,
              "description": null
            },
            "framework": null
          },
          "subkind": "dot",
          "groupRole": null,
          "confidence": null,
          "extraction": {
            "at": "2026-05-02 18:01:18.059+00",
            "model": "google/gemini-3.1-flash-lite-preview-20260303",
            "runId": null,
            "seconds": null,
            "promptVersion": null
          },
          "componentId": "3b1efae3-4d92-461a-9676-2b231e5f6260",
          "parentComponentId": null
        },
        {
          "bbox": null,
          "kind": "metric",
          "text": "AI augmentation score",
          "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": "2026-04-24 16:10:25+00",
            "model": "or:google/gemini-3.1-flash-lite-preview",
            "runId": null,
            "seconds": null,
            "promptVersion": null
          },
          "componentId": "019dd952-2e36-76f2-aee1-64695162c76c",
          "parentComponentId": null
        },
        {
          "bbox": {
            "h": 0.4,
            "w": 0.55,
            "x": 0.365,
            "y": 0.183
          },
          "kind": "paragraph",
          "text": "Rather than replacing human workers, GenAI will serve as a powerful tool to augment and evolve roles, enhancing the productivity and capabilities of employees across various sectors...",
          "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 18:01:18.059+00",
            "model": "google/gemini-3.1-flash-lite-preview-20260303",
            "runId": null,
            "seconds": null,
            "promptVersion": null
          },
          "componentId": "534ab8a8-da3e-480d-8131-7d5b94372c9e",
          "parentComponentId": null
        },
        {
          "bbox": {
            "h": 0.01,
            "w": 0.1,
            "x": 0.365,
            "y": 0.935
          },
          "kind": "source-note",
          "text": "Source: EY-Parthenon",
          "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 18:01:18.059+00",
            "model": "google/gemini-3.1-flash-lite-preview-20260303",
            "runId": null,
            "seconds": null,
            "promptVersion": null
          },
          "componentId": "1614eabf-a876-4223-a8cb-cabd4e9f97fe",
          "parentComponentId": null
        },
        {
          "bbox": {
            "h": 0.02,
            "w": 0.35,
            "x": 0.365,
            "y": 0.158
          },
          "kind": "title",
          "text": "AI exposure scores vary greatly across sectors",
          "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 18:01:18.059+00",
            "model": "google/gemini-3.1-flash-lite-preview-20260303",
            "runId": null,
            "seconds": null,
            "promptVersion": null
          },
          "componentId": "d767fc00-2569-410f-b86f-6dd9d57d2248",
          "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": "8fcaf46f-74a0-420c-a66d-8956c508554e",
          "evidence": "Chart 4: Median, max and min rescaled AI augmentation scores across 22 US “major occupation groups”",
          "pageRefs": null,
          "priority": null,
          "whenToUse": null,
          "confidence": 0.7,
          "extraction": {
            "at": "2026-07-16 21:49:28.642096+00",
            "model": "or:meta-llama/llama-4-scout",
            "runId": null,
            "seconds": null,
            "promptVersion": null
          },
          "pageNumber": 9,
          "whyItWorks": null,
          "antipattern": null,
          "cardinality": null,
          "narrativePurpose": null
        },
        {
          "tool": {
            "name": "Data Story Arc",
            "slug": "data-story-arc",
            "status": "active",
            "bestFor": null,
            "canonId": "019dd956-9c30-728e-b974-d3fb123dcf5a",
            "version": 1,
            "bodyDocId": null,
            "description": "Context → Conflict → Insight → Implication structure for data narratives",
            "familyLabel": null,
            "categoryName": "Loop",
            "categorySlug": "loop"
          },
          "agent": "Storyteller",
          "layer": "slide",
          "agents": [
            "Storyteller"
          ],
          "matchId": "253453d2-7b53-4fc7-9f22-f2c75590e0fe",
          "evidence": "GenAI is transforming the workforce by enabling workers to delegate routine, data-heavy tasks to GenAI systems, thereby enhancing their focus on areas where human skills like strategic thinking, empathy and crea",
          "pageRefs": null,
          "priority": "Core",
          "whenToUse": null,
          "confidence": 0.7,
          "extraction": {
            "at": "2026-07-16 21:49:28.60637+00",
            "model": "or:meta-llama/llama-4-scout",
            "runId": null,
            "seconds": null,
            "promptVersion": null
          },
          "pageNumber": 9,
          "whyItWorks": null,
          "antipattern": null,
          "cardinality": null,
          "narrativePurpose": null
        }
      ],
      "frameworks": [],
      "arcBeats": [
        {
          "to": 10,
          "arc": {
            "name": "The Consultant's Gambit",
            "slug": "consultants-gambit",
            "status": "active",
            "bestFor": "Business cases, project proposals, strategic recommendations",
            "canonId": "019dd956-5e0a-73c8-b305-81c38c959e9c",
            "version": 1,
            "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49",
            "structure": "Situation & Context -> Problem & Complication -> Solution & Approach -> Evidence & Proof -> Impact & Next Steps",
            "description": null,
            "familyLabel": null
          },
          "from": 6,
          "name": "Evidence & Proof",
          "beatId": "50595e69-1a4c-4b7a-9db4-2a10a64a59c8",
          "matchId": "424d33e4-517f-4ec9-b9d0-2d8a129b071e",
          "beatType": {
            "name": "Evidence & Proof",
            "slug": "consultants-gambit-evidence-proof",
            "status": "active",
            "canonId": "019dd9b8-07b1-7688-8e1e-7637fec3802a",
            "version": 1,
            "description": null
          },
          "evidence": "The data tables and industry trends provide evidence of GenAI's impact on various sectors",
          "position": 2,
          "isPrimaryArc": true,
          "parentBeatType": {
            "name": "Evidence",
            "slug": "evidence",
            "status": "active",
            "canonId": "019dd9b8-03f9-772a-b84a-4f07b415b77a",
            "version": 1,
            "description": "A dedicated proof beat exists in only ~4 arcs (Gambit, Sequoia, AIDA, Monroes). Other arcs embed evidence inline within development."
          },
          "alignedBlockIds": null,
          "matchConfidence": 0.8
        }
      ],
      "loops": [],
      "locked": true
    },
    {
      "page": 10,
      "type": "analysis",
      "title": "The chart is a dot plot showing range (min/max) and median for 10 specific occupation groups.",
      "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": 90,
        "componentCount": 9,
        "textChars": 1631,
        "nDataPoints": 30,
        "notes": "The chart is a dot plot showing range (min/max) and median for 10 specific occupation groups.",
        "elementsJson": [
          "headline_text",
          "paragraph",
          "scatter_plot"
        ],
        "confidence": 1,
        "extraction": {
          "model": "google/gemini-3.1-flash-lite-preview-20260303",
          "runId": null,
          "at": "2026-05-02 18:01:19.191+00",
          "seconds": 3.507,
          "promptVersion": "v2-canon-conditioned"
        }
      },
      "links": {
        "slide": "/slides/019dd923-5e88-73ef-bd59-b7c870c8c8e8/10",
        "deck": "/decks/019dd923-5e88-73ef-bd59-b7c870c8c8e8",
        "deckAnchor": "/decks/019dd923-5e88-73ef-bd59-b7c870c8c8e8#slide-10",
        "deckJson": "/decks/019dd923-5e88-73ef-bd59-b7c870c8c8e8.json"
      },
      "components": [
        {
          "bbox": null,
          "kind": "callout",
          "text": "Although these occupations are significantly exposed to AI, total automation is unlikely as workers remain indispensable for overseeing processes, strategic decision-making and tasks requiring nuanced judgment.",
          "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": "2026-04-24 16:10:26+00",
            "model": "or:google/gemini-3.1-flash-lite-preview",
            "runId": null,
            "seconds": null,
            "promptVersion": null
          },
          "componentId": "019dd952-2e36-76f2-aee1-c6c2e8f2ae15",
          "parentComponentId": null
        },
        {
          "bbox": {
            "h": 0.28,
            "w": 0.55,
            "x": 0.36,
            "y": 0.515
          },
          "kind": "chart",
          "text": "Dot plot showing min, median, and max AI augmentation scores for 10 occupation groups.",
          "attrs": null,
          "canon": {
            "kind": {
              "name": "Chart",
              "slug": "chart",
              "status": "active",
              "canonId": "019de52c-f9a0-76ef-adc6-0b859109d1f8",
              "version": 1,
              "description": "Quantitative chart."
            },
            "tool": null,
            "subkind": {
              "name": "Dot plot",
              "slug": "dot",
              "status": "active",
              "canonId": "019de52d-0235-738b-bd2b-78f8e24d7cb0",
              "version": 1,
              "description": null
            },
            "framework": null
          },
          "subkind": "dot",
          "groupRole": null,
          "confidence": null,
          "extraction": {
            "at": "2026-05-02 18:01:19.191+00",
            "model": "google/gemini-3.1-flash-lite-preview-20260303",
            "runId": null,
            "seconds": null,
            "promptVersion": null
          },
          "componentId": "1a9af0ad-4da8-4e00-b0db-6f8a70161f80",
          "parentComponentId": null
        },
        {
          "bbox": null,
          "kind": "metric",
          "text": "AI augmentation score",
          "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": "2026-04-24 16:10:26+00",
            "model": "or:google/gemini-3.1-flash-lite-preview",
            "runId": null,
            "seconds": null,
            "promptVersion": null
          },
          "componentId": "019dd952-2e36-76f2-aee1-c89d84181204",
          "parentComponentId": null
        },
        {
          "bbox": {
            "h": 0.08,
            "w": 0.55,
            "x": 0.36,
            "y": 0.385
          },
          "kind": "paragraph",
          "text": "Although these occupations are significantly exposed to AI, total automation is unlikely as workers remain indispensable for overseeing processes, strategic decision-making and tasks requiring nuanced judgment. Indeed, the wide dispersion of AI augmentation scores for the top 10 of the 94 minor occupations group illustrates the importance of human intervention.",
          "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 18:01:19.191+00",
            "model": "google/gemini-3.1-flash-lite-preview-20260303",
            "runId": null,
            "seconds": null,
            "promptVersion": null
          },
          "componentId": "04405d4a-1d12-4838-baac-4d4029c15136",
          "parentComponentId": null
        },
        {
          "bbox": {
            "h": 0.08,
            "w": 0.55,
            "x": 0.36,
            "y": 0.183
          },
          "kind": "paragraph",
          "text": "The breakdown across sectors shows that major industries with limited differences in AI augmentation scores can still display a wide range in the augmentation scores across sub-occupations. This is more evident when looking at the top and bottom 10 occupations among the more detailed categorization of 94 minor occupation groups (Chart 5 and Chart 6).",
          "attrs": null,
          "canon": {
            "kind": {
              "name": "Paragraph",
              "slug": "paragraph",
              "status": "active",
              "canonId": "5f2affc0-941d-4d07-959d-4bfc1930cea4",
              "version": 1,
              "description": "Single prose block in the body of a slide."
            },
            "tool": null,
            "subkind": {
              "name": "Paragraph",
              "slug": "paragraph",
              "status": "active",
              "canonId": "019de52c-fb80-75af-aa5c-a7a4bfac2433",
              "version": 1,
              "description": null
            },
            "framework": null
          },
          "subkind": "paragraph",
          "groupRole": null,
          "confidence": null,
          "extraction": {
            "at": "2026-05-02 18:01:19.191+00",
            "model": "google/gemini-3.1-flash-lite-preview-20260303",
            "runId": null,
            "seconds": null,
            "promptVersion": null
          },
          "componentId": "191f571e-c3ed-4219-a620-77486e5d19b0",
          "parentComponentId": null
        },
        {
          "bbox": {
            "h": 0.11,
            "w": 0.55,
            "x": 0.36,
            "y": 0.275
          },
          "kind": "paragraph",
          "text": "Looking at the top 10 occupations with the highest AI augmentation scores, professions like plant and system operators, physical scientists, agricultural workers, drafters, programmers, engineers, and architects involve a high degree of repetitive and data-driven tasks that AI can automate. These include data analysis and monitoring, operations scheduling, document review, design work, and safety inspection processes.",
          "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 18:01:19.191+00",
            "model": "google/gemini-3.1-flash-lite-preview-20260303",
            "runId": null,
            "seconds": null,
            "promptVersion": null
          },
          "componentId": "ae8b1386-546b-4ff6-9489-85a44bf717e9",
          "parentComponentId": null
        },
        {
          "bbox": {
            "h": 0.01,
            "w": 0.1,
            "x": 0.36,
            "y": 0.81
          },
          "kind": "source-note",
          "text": "Source: EY-Parthenon",
          "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 18:01:19.191+00",
            "model": "google/gemini-3.1-flash-lite-preview-20260303",
            "runId": null,
            "seconds": null,
            "promptVersion": null
          },
          "componentId": "c451191a-7715-44ec-ae8b-f9a7f1b887d9",
          "parentComponentId": null
        },
        {
          "bbox": {
            "h": 0.02,
            "w": 0.25,
            "x": 0.36,
            "y": 0.155
          },
          "kind": "title",
          "text": "Most and least exposed occupations",
          "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 18:01:19.191+00",
            "model": "google/gemini-3.1-flash-lite-preview-20260303",
            "runId": null,
            "seconds": null,
            "promptVersion": null
          },
          "componentId": "8b930a97-2721-4318-bad6-12d004ef8d2f",
          "parentComponentId": null
        },
        {
          "bbox": {
            "h": 0.08,
            "w": 0.25,
            "x": 0.07,
            "y": 0.53
          },
          "kind": "title",
          "text": "Chart 5: Median, max and min rescaled AI augmentation scores across US \"minor occupation groups\" - ten highest median scores",
          "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 18:01:19.191+00",
            "model": "google/gemini-3.1-flash-lite-preview-20260303",
            "runId": null,
            "seconds": null,
            "promptVersion": null
          },
          "componentId": "bc0e7654-b8c9-4f49-a280-2ad44379f8c3",
          "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": "2b7e0997-1c78-4bb2-b97f-d5a1922d0461",
          "evidence": "Chart 5: Median, max and min rescaled AI augmentation scores across US \"minor occupation groups\" - ten highest median scores",
          "pageRefs": null,
          "priority": null,
          "whenToUse": null,
          "confidence": 0.7,
          "extraction": {
            "at": "2026-07-16 21:49:28.742363+00",
            "model": "or:meta-llama/llama-4-scout",
            "runId": null,
            "seconds": null,
            "promptVersion": null
          },
          "pageNumber": 10,
          "whyItWorks": null,
          "antipattern": null,
          "cardinality": null,
          "narrativePurpose": null
        },
        {
          "tool": {
            "name": "Data Story Arc",
            "slug": "data-story-arc",
            "status": "active",
            "bestFor": null,
            "canonId": "019dd956-9c30-728e-b974-d3fb123dcf5a",
            "version": 1,
            "bodyDocId": null,
            "description": "Context → Conflict → Insight → Implication structure for data narratives",
            "familyLabel": null,
            "categoryName": "Loop",
            "categorySlug": "loop"
          },
          "agent": "Storyteller",
          "layer": "slide",
          "agents": [
            "Storyteller"
          ],
          "matchId": "a4628bb3-c371-4bd5-aab9-6d3b412b41d6",
          "evidence": "Looking at the top 10 occupations with the highest AI augmentation scores, professions like plant and system operators, physical scientists, agricultural workers, drafters, programmers, engineers, an",
          "pageRefs": null,
          "priority": "Core",
          "whenToUse": null,
          "confidence": 0.7,
          "extraction": {
            "at": "2026-07-16 21:49:28.708065+00",
            "model": "or:meta-llama/llama-4-scout",
            "runId": null,
            "seconds": null,
            "promptVersion": null
          },
          "pageNumber": 10,
          "whyItWorks": null,
          "antipattern": null,
          "cardinality": null,
          "narrativePurpose": null
        }
      ],
      "frameworks": [],
      "arcBeats": [
        {
          "to": 10,
          "arc": {
            "name": "The Consultant's Gambit",
            "slug": "consultants-gambit",
            "status": "active",
            "bestFor": "Business cases, project proposals, strategic recommendations",
            "canonId": "019dd956-5e0a-73c8-b305-81c38c959e9c",
            "version": 1,
            "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49",
            "structure": "Situation & Context -> Problem & Complication -> Solution & Approach -> Evidence & Proof -> Impact & Next Steps",
            "description": null,
            "familyLabel": null
          },
          "from": 6,
          "name": "Evidence & Proof",
          "beatId": "50595e69-1a4c-4b7a-9db4-2a10a64a59c8",
          "matchId": "424d33e4-517f-4ec9-b9d0-2d8a129b071e",
          "beatType": {
            "name": "Evidence & Proof",
            "slug": "consultants-gambit-evidence-proof",
            "status": "active",
            "canonId": "019dd9b8-07b1-7688-8e1e-7637fec3802a",
            "version": 1,
            "description": null
          },
          "evidence": "The data tables and industry trends provide evidence of GenAI's impact on various sectors",
          "position": 2,
          "isPrimaryArc": true,
          "parentBeatType": {
            "name": "Evidence",
            "slug": "evidence",
            "status": "active",
            "canonId": "019dd9b8-03f9-772a-b84a-4f07b415b77a",
            "version": 1,
            "description": "A dedicated proof beat exists in only ~4 arcs (Gambit, Sequoia, AIDA, Monroes). Other arcs embed evidence inline within development."
          },
          "alignedBlockIds": null,
          "matchConfidence": 0.8
        }
      ],
      "loops": [],
      "locked": true
    },
    {
      "page": 11,
      "type": "analysis",
      "title": "The chart uses a dot plot format to show the range (min, median, max) of AI augmentation scores for specific occupations.",
      "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": 58,
        "componentCount": 6,
        "textChars": 659,
        "nDataPoints": 30,
        "notes": "The chart uses a dot plot format to show the range (min, median, max) of AI augmentation scores for specific occupations.",
        "elementsJson": [
          "paragraph",
          "scatter_plot",
          "footnote"
        ],
        "confidence": 1,
        "extraction": {
          "model": "google/gemini-3.1-flash-lite-preview-20260303",
          "runId": null,
          "at": "2026-05-02 18:01:18.58+00",
          "seconds": 2.817,
          "promptVersion": "v2-canon-conditioned"
        }
      },
      "links": {
        "slide": "/slides/019dd923-5e88-73ef-bd59-b7c870c8c8e8/11",
        "deck": "/decks/019dd923-5e88-73ef-bd59-b7c870c8c8e8",
        "deckAnchor": "/decks/019dd923-5e88-73ef-bd59-b7c870c8c8e8#slide-11",
        "deckJson": "/decks/019dd923-5e88-73ef-bd59-b7c870c8c8e8.json"
      },
      "components": [
        {
          "bbox": null,
          "kind": "callout",
          "text": "Consequently, these roles, which require human interaction, decision-making, physical intervention and personalization, face lower risk from AI exposure at first.",
          "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": "2026-04-24 16:10:25+00",
            "model": "or:google/gemini-3.1-flash-lite-preview",
            "runId": null,
            "seconds": null,
            "promptVersion": null
          },
          "componentId": "019dd952-2e36-76f2-aee1-94d8073f62e6",
          "parentComponentId": null
        },
        {
          "bbox": {
            "h": 0.35,
            "w": 0.55,
            "x": 0.36,
            "y": 0.47
          },
          "kind": "chart",
          "text": "Dot plot showing min, median, and max AI augmentation scores for 10 occupations.",
          "attrs": null,
          "canon": {
            "kind": {
              "name": "Chart",
              "slug": "chart",
              "status": "active",
              "canonId": "019de52c-f9a0-76ef-adc6-0b859109d1f8",
              "version": 1,
              "description": "Quantitative chart."
            },
            "tool": null,
            "subkind": {
              "name": "Dot plot",
              "slug": "dot",
              "status": "active",
              "canonId": "019de52d-0235-738b-bd2b-78f8e24d7cb0",
              "version": 1,
              "description": null
            },
            "framework": null
          },
          "subkind": "dot",
          "groupRole": null,
          "confidence": null,
          "extraction": {
            "at": "2026-05-02 18:01:18.58+00",
            "model": "google/gemini-3.1-flash-lite-preview-20260303",
            "runId": null,
            "seconds": null,
            "promptVersion": null
          },
          "componentId": "433a9db5-35f9-45ef-9dd6-60e100615d17",
          "parentComponentId": null
        },
        {
          "bbox": null,
          "kind": "metric",
          "text": "AI augmentation score",
          "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": "2026-04-24 16:10:25+00",
            "model": "or:google/gemini-3.1-flash-lite-preview",
            "runId": null,
            "seconds": null,
            "promptVersion": null
          },
          "componentId": "019dd952-2e36-76f2-aee1-99cec89b6b9e",
          "parentComponentId": null
        },
        {
          "bbox": {
            "h": 0.35,
            "w": 0.55,
            "x": 0.36,
            "y": 0.15
          },
          "kind": "paragraph",
          "text": "The 10 minor occupations with the lowest AI augmentation scores (Chart 6) have the highest intrinsic human elements needed for their functions. For example, roles like postsecondary teachers require human interaction and ability to customize learning...",
          "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 18:01:18.58+00",
            "model": "google/gemini-3.1-flash-lite-preview-20260303",
            "runId": null,
            "seconds": null,
            "promptVersion": null
          },
          "componentId": "482e78dc-7add-4393-ba15-aaaad76e4940",
          "parentComponentId": null
        },
        {
          "bbox": {
            "h": 0.02,
            "w": 0.1,
            "x": 0.36,
            "y": 0.8
          },
          "kind": "source-note",
          "text": "Source: EY-Parthenon",
          "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 18:01:18.58+00",
            "model": "google/gemini-3.1-flash-lite-preview-20260303",
            "runId": null,
            "seconds": null,
            "promptVersion": null
          },
          "componentId": "f009d264-eb64-4149-8d93-b1467c3986c5",
          "parentComponentId": null
        },
        {
          "bbox": {
            "h": 0.05,
            "w": 0.25,
            "x": 0.07,
            "y": 0.48
          },
          "kind": "title",
          "text": "Chart 6: Median, max and min rescaled AI augmentation scores across US \"minor occupation groups\" - ten lowest median scores",
          "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 18:01:18.58+00",
            "model": "google/gemini-3.1-flash-lite-preview-20260303",
            "runId": null,
            "seconds": null,
            "promptVersion": null
          },
          "componentId": "07f963cc-313d-49e9-bf1f-eea849509197",
          "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": "f1a149ee-3b09-48a3-8b47-c99d412b090c",
          "evidence": "Chart 6: Median, max and min rescaled AI augmentation scores across US \"minor occupation groups\" - ten lowest median scores",
          "pageRefs": null,
          "priority": null,
          "whenToUse": null,
          "confidence": 0.7,
          "extraction": {
            "at": "2026-07-16 21:49:28.810223+00",
            "model": "or:meta-llama/llama-4-scout",
            "runId": null,
            "seconds": null,
            "promptVersion": null
          },
          "pageNumber": 11,
          "whyItWorks": null,
          "antipattern": null,
          "cardinality": null,
          "narrativePurpose": null
        }
      ],
      "frameworks": [],
      "arcBeats": [],
      "loops": [],
      "locked": true
    },
    {
      "page": 12,
      "type": "analysis",
      "title": "The slide discusses NAICS-based sector analysis and provides examples like healthcare (radiologists vs nurses) to nuance the correlation.",
      "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": 1752,
        "nDataPoints": 0,
        "notes": "The slide discusses NAICS-based sector analysis and provides examples like healthcare (radiologists vs nurses) to nuance the correlation.",
        "elementsJson": [
          "paragraph",
          "photo"
        ],
        "confidence": 1,
        "extraction": {
          "model": "google/gemini-3.1-flash-lite-preview-20260303",
          "runId": null,
          "at": "2026-05-02 18:01:23.582+00",
          "seconds": 7.795,
          "promptVersion": "v2-canon-conditioned"
        }
      },
      "links": {
        "slide": "/slides/019dd923-5e88-73ef-bd59-b7c870c8c8e8/12",
        "deck": "/decks/019dd923-5e88-73ef-bd59-b7c870c8c8e8",
        "deckAnchor": "/decks/019dd923-5e88-73ef-bd59-b7c870c8c8e8#slide-12",
        "deckJson": "/decks/019dd923-5e88-73ef-bd59-b7c870c8c8e8.json"
      },
      "components": [
        {
          "bbox": null,
          "kind": "callout",
          "text": "The relationship between GenAI exposure and wage levels in various occupations appears to exhibit a slight positive correlation, albeit with some nuances.",
          "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": "2026-04-24 16:10:25+00",
            "model": "or:google/gemini-3.1-flash-lite-preview",
            "runId": null,
            "seconds": null,
            "promptVersion": null
          },
          "componentId": "019dd952-2e36-76f2-aee1-488a14405c4b",
          "parentComponentId": null
        },
        {
          "bbox": {
            "h": 0.367,
            "w": 1,
            "x": 0,
            "y": 0.633
          },
          "kind": "image",
          "text": null,
          "attrs": null,
          "canon": {
            "kind": {
              "name": "Image",
              "slug": "image",
              "status": "active",
              "canonId": "019de52c-f978-701f-a720-51d029d769e7",
              "version": 1,
              "description": "Photo, illustration, screenshot or icon."
            },
            "tool": null,
            "subkind": {
              "name": "Photo",
              "slug": "photo",
              "status": "active",
              "canonId": "019de52c-fd37-757f-b4a8-ca26d4888875",
              "version": 1,
              "description": null
            },
            "framework": null
          },
          "subkind": "photo",
          "groupRole": null,
          "confidence": null,
          "extraction": {
            "at": "2026-05-02 18:01:23.582+00",
            "model": "google/gemini-3.1-flash-lite-preview-20260303",
            "runId": null,
            "seconds": null,
            "promptVersion": null
          },
          "componentId": "cdf070a9-6b0c-4391-9749-12850ab40350",
          "parentComponentId": null
        },
        {
          "bbox": {
            "h": 0.606,
            "w": 0.926,
            "x": 0.343,
            "y": 0.507
          },
          "kind": "paragraph",
          "text": "Still, it's important to stress the widespread diffusion of occupations across these major sector groupings both in terms of AI exposure and salaries. Health care is a prime example where both high-skill/high-salary functions and low-skill/low-salary functions have high AI exposure. For instance, a radiologist (higher skill/higher salary) is highly exposed to AI for detection and diagnostics, just like a nurse (lower skill/lower salary) is for administrative tasks.",
          "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 18:01:23.582+00",
            "model": "google/gemini-3.1-flash-lite-preview-20260303",
            "runId": null,
            "seconds": null,
            "promptVersion": null
          },
          "componentId": "1d18c083-7ea8-4681-aaca-d75a049e9502",
          "parentComponentId": null
        },
        {
          "bbox": {
            "h": 0.355,
            "w": 0.926,
            "x": 0.343,
            "y": 0.272
          },
          "kind": "paragraph",
          "text": "The relationship between GenAI exposure and wage levels in various occupations appears to exhibit a slight positive correlation, albeit with some nuances. An analysis of the 20 major industry sectors based on two-digit North American Industry Classification System (NAICS) structure and their respective average wages shows that higher AI exposure scores are generally correlated with higher wages (Chart 7 and Chart 8).",
          "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 18:01:23.582+00",
            "model": "google/gemini-3.1-flash-lite-preview-20260303",
            "runId": null,
            "seconds": null,
            "promptVersion": null
          },
          "componentId": "b74f2ae4-92e0-47cb-b028-99111336df52",
          "parentComponentId": null
        },
        {
          "bbox": {
            "h": 0.498,
            "w": 0.926,
            "x": 0.343,
            "y": 0.382
          },
          "kind": "paragraph",
          "text": "Sectors such as information; finance and insurance; utilities; and professional, scientific and technical services report higher yearly wages (in the range of $85,000 to $92,000) and show slightly higher AI exposure scores. This could suggest that sectors requiring more advanced skills and therefore having higher salaries have greater exposure to AI. On the other hand, sectors like retail trade, accommodation and food services, and arts and entertainment report lower yearly wages (in the range of $35,000 to $50,000) and are associated with lower GenAI exposure scores.",
          "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 18:01:23.582+00",
            "model": "google/gemini-3.1-flash-lite-preview-20260303",
            "runId": null,
            "seconds": null,
            "promptVersion": null
          },
          "componentId": "efaff86e-ff91-43b4-99bd-c0c01481cc4f",
          "parentComponentId": null
        },
        {
          "bbox": {
            "h": 0.253,
            "w": 0.926,
            "x": 0.343,
            "y": 0.221
          },
          "kind": "title",
          "text": "Do jobs that necessitate more advanced skills and pay larger salaries have higher exposure to 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": "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 18:01:23.582+00",
            "model": "google/gemini-3.1-flash-lite-preview-20260303",
            "runId": null,
            "seconds": null,
            "promptVersion": null
          },
          "componentId": "37ad9f5a-f1b6-495b-942f-34d77c633926",
          "parentComponentId": null
        },
        {
          "bbox": {
            "h": 0.193,
            "w": 0.926,
            "x": 0.343,
            "y": 0.158
          },
          "kind": "title",
          "text": "3. Al's influence across wage brackets",
          "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 18:01:23.582+00",
            "model": "google/gemini-3.1-flash-lite-preview-20260303",
            "runId": null,
            "seconds": null,
            "promptVersion": null
          },
          "componentId": "de0993b2-8db6-4633-90a7-9b29d960e7d1",
          "parentComponentId": null
        }
      ],
      "metrics": [],
      "tools": [],
      "frameworks": [],
      "arcBeats": [],
      "loops": [],
      "locked": true
    },
    {
      "page": 13,
      "type": "analysis",
      "title": "Chart 7 is a bubble chart showing occupation share by augmentation score. Chart 8 is a scatter plot showing industry-level data with a legend.",
      "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": 59,
        "componentCount": 8,
        "textChars": 292,
        "nDataPoints": 25,
        "notes": "Chart 7 is a bubble chart showing occupation share by augmentation score. Chart 8 is a scatter plot showing industry-level data with a legend.",
        "elementsJson": [
          "bubble_chart",
          "scatter_plot"
        ],
        "confidence": 1,
        "extraction": {
          "model": "google/gemini-3.1-flash-lite-preview-20260303",
          "runId": null,
          "at": "2026-05-02 18:01:19.061+00",
          "seconds": 3.157,
          "promptVersion": "v2-canon-conditioned"
        }
      },
      "links": {
        "slide": "/slides/019dd923-5e88-73ef-bd59-b7c870c8c8e8/13",
        "deck": "/decks/019dd923-5e88-73ef-bd59-b7c870c8c8e8",
        "deckAnchor": "/decks/019dd923-5e88-73ef-bd59-b7c870c8c8e8#slide-13",
        "deckJson": "/decks/019dd923-5e88-73ef-bd59-b7c870c8c8e8.json"
      },
      "components": [
        {
          "bbox": {
            "h": 0.4,
            "w": 0.5,
            "x": 0.34,
            "y": 0.16
          },
          "kind": "chart",
          "text": "Chart 7 bubble chart",
          "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": "Bubble chart",
              "slug": "bubble",
              "status": "active",
              "canonId": "019de52d-00a4-756f-8978-8d5e48905dbc",
              "version": 1,
              "description": null
            },
            "framework": null
          },
          "subkind": "bubble",
          "groupRole": null,
          "confidence": null,
          "extraction": {
            "at": "2026-05-02 18:01:19.061+00",
            "model": "google/gemini-3.1-flash-lite-preview-20260303",
            "runId": null,
            "seconds": null,
            "promptVersion": null
          },
          "componentId": "1745ebbc-d265-4a33-8fb4-cebffce31a7c",
          "parentComponentId": null
        },
        {
          "bbox": {
            "h": 0.35,
            "w": 0.5,
            "x": 0.34,
            "y": 0.55
          },
          "kind": "chart",
          "text": "Chart 8 scatter plot",
          "attrs": null,
          "canon": {
            "kind": {
              "name": "Chart",
              "slug": "chart",
              "status": "active",
              "canonId": "019de52c-f9a0-76ef-adc6-0b859109d1f8",
              "version": 1,
              "description": "Quantitative chart."
            },
            "tool": null,
            "subkind": {
              "name": "Scatter plot",
              "slug": "scatter",
              "status": "active",
              "canonId": "019de52d-007d-72ec-8689-c79fb78e21a2",
              "version": 1,
              "description": null
            },
            "framework": null
          },
          "subkind": "scatter",
          "groupRole": null,
          "confidence": null,
          "extraction": {
            "at": "2026-05-02 18:01:19.061+00",
            "model": "google/gemini-3.1-flash-lite-preview-20260303",
            "runId": null,
            "seconds": null,
            "promptVersion": null
          },
          "componentId": "7f538499-9fbc-4c60-a612-6f7228a86b21",
          "parentComponentId": null
        },
        {
          "bbox": null,
          "kind": "metric",
          "text": "AI augmentation score",
          "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": "2026-04-24 16:10:26+00",
            "model": "or:google/gemini-3.1-flash-lite-preview",
            "runId": null,
            "seconds": null,
            "promptVersion": null
          },
          "componentId": "019dd952-2e36-76f2-aee1-b26cadf18681",
          "parentComponentId": null
        },
        {
          "bbox": {
            "h": 0.01,
            "w": 0.1,
            "x": 0.34,
            "y": 0.0091
          },
          "kind": "source-note",
          "text": "Source: EY-Parthenon",
          "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 18:01:19.061+00",
            "model": "google/gemini-3.1-flash-lite-preview-20260303",
            "runId": null,
            "seconds": null,
            "promptVersion": null
          },
          "componentId": "54121e3c-dad1-4b0a-8750-602cbacb1347",
          "parentComponentId": null
        },
        {
          "bbox": {
            "h": 0.01,
            "w": 0.1,
            "x": 0.34,
            "y": 0.0048
          },
          "kind": "source-note",
          "text": "Source: EY-Parthenon",
          "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 18:01:19.061+00",
            "model": "google/gemini-3.1-flash-lite-preview-20260303",
            "runId": null,
            "seconds": null,
            "promptVersion": null
          },
          "componentId": "f7b8ed11-b864-4c1b-ad4e-4f599b537d64",
          "parentComponentId": null
        },
        {
          "bbox": {
            "h": 0.04,
            "w": 0.25,
            "x": 0.07,
            "y": 0.0017
          },
          "kind": "title",
          "text": "Chart 7: US annual wages and occupation share by AI augmentation score",
          "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 18:01:19.061+00",
            "model": "google/gemini-3.1-flash-lite-preview-20260303",
            "runId": null,
            "seconds": null,
            "promptVersion": null
          },
          "componentId": "14146c96-2711-4bd2-be47-b174a4b1741e",
          "parentComponentId": null
        },
        {
          "bbox": {
            "h": 0.02,
            "w": 0.33,
            "x": 0.07,
            "y": 0.04
          },
          "kind": "title",
          "text": "The impact of GenAI on the labor 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 18:01:19.061+00",
            "model": "google/gemini-3.1-flash-lite-preview-20260303",
            "runId": null,
            "seconds": null,
            "promptVersion": null
          },
          "componentId": "c2275713-fde1-4132-9a6e-0af39a5f0058",
          "parentComponentId": null
        },
        {
          "bbox": {
            "h": 0.04,
            "w": 0.25,
            "x": 0.07,
            "y": 0.0056
          },
          "kind": "title",
          "text": "Chart 8: US weighted average annual wages and rescaled AI augmentation by industry",
          "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 18:01:19.061+00",
            "model": "google/gemini-3.1-flash-lite-preview-20260303",
            "runId": null,
            "seconds": null,
            "promptVersion": null
          },
          "componentId": "c2c0240c-30d8-4141-8692-d9e5aee991ef",
          "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": "9f3c0678-91ee-4ce6-bce0-c7db92823b04",
          "evidence": "Chart 7: US annual wages and occupation share by AI augmentation score",
          "pageRefs": null,
          "priority": null,
          "whenToUse": null,
          "confidence": 0.7,
          "extraction": {
            "at": "2026-07-16 21:49:28.911512+00",
            "model": "or:meta-llama/llama-4-scout",
            "runId": null,
            "seconds": null,
            "promptVersion": null
          },
          "pageNumber": 13,
          "whyItWorks": null,
          "antipattern": null,
          "cardinality": null,
          "narrativePurpose": null
        }
      ],
      "frameworks": [],
      "arcBeats": [],
      "loops": [],
      "locked": true
    },
    {
      "page": 14,
      "type": "setup",
      "function": "transition",
      "rawType": "transition",
      "block": null,
      "metadata": {
        "slideType": "transition",
        "slideTypeCanon": {
          "name": "Transition",
          "slug": "transition",
          "status": "active",
          "canonId": "019de52d-0693-7766-9f05-887f41f8e41e",
          "version": 1,
          "description": null
        },
        "function": "transition",
        "functionCanon": {
          "name": "Transition",
          "slug": "transition",
          "status": "active",
          "canonId": "019de52d-1365-7149-92aa-66df859e75fd",
          "version": 1,
          "description": null
        },
        "density": "dense",
        "densityScore": 50,
        "componentCount": 5,
        "textChars": 1113,
        "nDataPoints": 0,
        "notes": null,
        "elementsJson": [
          "headline_text",
          "paragraph",
          "photo"
        ],
        "confidence": 0.9,
        "extraction": {
          "model": "google/gemini-3.1-flash-lite-preview-20260303",
          "runId": null,
          "at": "2026-05-02 18:01:18.89+00",
          "seconds": 2.929,
          "promptVersion": "v2-canon-conditioned"
        }
      },
      "links": {
        "slide": "/slides/019dd923-5e88-73ef-bd59-b7c870c8c8e8/14",
        "deck": "/decks/019dd923-5e88-73ef-bd59-b7c870c8c8e8",
        "deckAnchor": "/decks/019dd923-5e88-73ef-bd59-b7c870c8c8e8#slide-14",
        "deckJson": "/decks/019dd923-5e88-73ef-bd59-b7c870c8c8e8.json"
      },
      "components": [
        {
          "bbox": null,
          "kind": "callout",
          "text": "Business leaders can effectively implement GenAI in a manner that not only aligns with their immediate operational needs but also positions their organizations at the forefront of technological advancement.",
          "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": "2026-04-24 16:10:27+00",
            "model": "or:google/gemini-3.1-flash-lite-preview",
            "runId": null,
            "seconds": null,
            "promptVersion": null
          },
          "componentId": "019dd952-2e36-76f2-aee2-064158d23766",
          "parentComponentId": null
        },
        {
          "bbox": {
            "h": 0.5,
            "w": 1,
            "x": 0,
            "y": 0.5
          },
          "kind": "image",
          "text": null,
          "attrs": null,
          "canon": {
            "kind": {
              "name": "Image",
              "slug": "image",
              "status": "active",
              "canonId": "019de52c-f978-701f-a720-51d029d769e7",
              "version": 1,
              "description": "Photo, illustration, screenshot or icon."
            },
            "tool": null,
            "subkind": {
              "name": "Photo",
              "slug": "photo",
              "status": "active",
              "canonId": "019de52c-fd37-757f-b4a8-ca26d4888875",
              "version": 1,
              "description": null
            },
            "framework": null
          },
          "subkind": "photo",
          "groupRole": null,
          "confidence": null,
          "extraction": {
            "at": "2026-05-02 18:01:18.89+00",
            "model": "google/gemini-3.1-flash-lite-preview-20260303",
            "runId": null,
            "seconds": null,
            "promptVersion": null
          },
          "componentId": "8fed9aee-3b4f-4a7c-898c-4fc4ecd2ba3c",
          "parentComponentId": null
        },
        {
          "bbox": {
            "h": 0.06,
            "w": 0.55,
            "x": 0.343,
            "y": 0.22
          },
          "kind": "paragraph",
          "text": "Finally, we outline how to execute a customized GenAI strategy for long-term growth by following the guidance of two pillars.",
          "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 18:01:18.89+00",
            "model": "google/gemini-3.1-flash-lite-preview-20260303",
            "runId": null,
            "seconds": null,
            "promptVersion": null
          },
          "componentId": "93123347-4062-458d-ba0d-cbcf0068b81d",
          "parentComponentId": null
        },
        {
          "bbox": {
            "h": 0.15,
            "w": 0.55,
            "x": 0.343,
            "y": 0.295
          },
          "kind": "paragraph",
          "text": "Business leaders can effectively implement GenAI in a manner that not only aligns with their immediate operational needs but also positions their organizations at the forefront of technological advancement. Using a proactive approach helps ensure that AI serves as a catalyst for workforce enhancement, operational optimization and sustainable growth, preparing the organization for the challenges and opportunities of an AI-driven future.prime example where both high-skill/high-salary functions and low-skill/low-salary functions have high AI exposure. For instance, a radiologist (higher skill/higher salary) is highly exposed to AI for detection and diagnostics, just like a nurse (lower skill/lower salary) is for administrative tasks.",
          "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 18:01:18.89+00",
            "model": "google/gemini-3.1-flash-lite-preview-20260303",
            "runId": null,
            "seconds": null,
            "promptVersion": null
          },
          "componentId": "e14f196a-8697-4fc3-bf00-fb6c751d56c6",
          "parentComponentId": null
        },
        {
          "bbox": {
            "h": 0.025,
            "w": 0.315,
            "x": 0.343,
            "y": 0.165
          },
          "kind": "title",
          "text": "4. Business implications of AI integration",
          "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 18:01:18.89+00",
            "model": "google/gemini-3.1-flash-lite-preview-20260303",
            "runId": null,
            "seconds": null,
            "promptVersion": null
          },
          "componentId": "2c222295-1454-42b7-8a3a-62392b31adbc",
          "parentComponentId": null
        }
      ],
      "metrics": [],
      "tools": [],
      "frameworks": [],
      "arcBeats": [
        {
          "to": 15,
          "arc": {
            "name": "The Consultant's Gambit",
            "slug": "consultants-gambit",
            "status": "active",
            "bestFor": "Business cases, project proposals, strategic recommendations",
            "canonId": "019dd956-5e0a-73c8-b305-81c38c959e9c",
            "version": 1,
            "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49",
            "structure": "Situation & Context -> Problem & Complication -> Solution & Approach -> Evidence & Proof -> Impact & Next Steps",
            "description": null,
            "familyLabel": null
          },
          "from": 14,
          "name": "Impact & Next Steps",
          "beatId": "9b3c4797-5730-4279-a276-4e3a6b90e40b",
          "matchId": "424d33e4-517f-4ec9-b9d0-2d8a129b071e",
          "beatType": {
            "name": "Impact & Next Steps",
            "slug": "consultants-gambit-impact-next-steps",
            "status": "active",
            "canonId": "019dd9b8-0849-7728-9ee9-fd1609c4c655",
            "version": 1,
            "description": null
          },
          "evidence": "The business implications and recommendation provide guidance for businesses",
          "position": 3,
          "isPrimaryArc": true,
          "parentBeatType": {
            "name": "Resolution",
            "slug": "resolution",
            "status": "active",
            "canonId": "019dd9b8-045d-703b-8dd7-e92aba3ba91b",
            "version": 1,
            "description": "How the deck ends. Required in 19/20 arcs. The exception (Sparkline) ends with new bliss which is functionally a resolution."
          },
          "alignedBlockIds": null,
          "matchConfidence": 0.8
        }
      ],
      "loops": [
        {
          "to": 15,
          "from": 14,
          "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": "673cd046-6dde-4d2b-a046-feb6d0c92238",
          "evidence": "The business implications and recommendation highlight the importance of adapting to GenAI",
          "position": 1,
          "objective": "What are the business implications of not adapting to GenAI?",
          "confidence": 0.6,
          "extraction": {
            "at": "2026-07-16 21:19:48.55105+00",
            "model": "or:meta-llama/llama-4-scout",
            "runId": null,
            "seconds": null,
            "promptVersion": "doc-narrative-v1"
          }
        }
      ],
      "locked": true
    },
    {
      "page": 15,
      "type": "resolution",
      "title": "The slide provides strategic guidance on AI adoption, focusing on workforce analysis, customization, and resource investment.",
      "function": "recommend",
      "rawType": "recommendation",
      "block": null,
      "metadata": {
        "slideType": "recommendation",
        "slideTypeCanon": {
          "name": "Recommendation",
          "slug": "recommendation",
          "status": "active",
          "canonId": "019de52d-0c35-718b-8bbb-772a56a31ecd",
          "version": 1,
          "description": null
        },
        "function": "recommend",
        "functionCanon": {
          "name": "Recommend",
          "slug": "recommend",
          "status": "active",
          "canonId": "019de52d-1609-764f-9882-9ef3ede71d8b",
          "version": 1,
          "description": null
        },
        "density": "overcrowded",
        "densityScore": 78,
        "componentCount": 8,
        "textChars": 2468,
        "nDataPoints": 0,
        "notes": "The slide provides strategic guidance on AI adoption, focusing on workforce analysis, customization, and resource investment.",
        "elementsJson": [
          "bullet_list",
          "photo"
        ],
        "confidence": 0.9,
        "extraction": {
          "model": "google/gemini-3.1-flash-lite-preview-20260303",
          "runId": null,
          "at": "2026-05-02 18:01:20.21+00",
          "seconds": 4.13,
          "promptVersion": "v2-canon-conditioned"
        }
      },
      "links": {
        "slide": "/slides/019dd923-5e88-73ef-bd59-b7c870c8c8e8/15",
        "deck": "/decks/019dd923-5e88-73ef-bd59-b7c870c8c8e8",
        "deckAnchor": "/decks/019dd923-5e88-73ef-bd59-b7c870c8c8e8#slide-15",
        "deckJson": "/decks/019dd923-5e88-73ef-bd59-b7c870c8c8e8.json"
      },
      "components": [
        {
          "bbox": null,
          "kind": "callout",
          "text": "The objective is to harness AI's capabilities to bolster job performance, allowing employees to shift their focus to aspects of their roles that necessitate human insight, creativity and decision-making.",
          "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": "2026-04-24 16:10:26+00",
            "model": "or:google/gemini-3.1-flash-lite-preview",
            "runId": null,
            "seconds": null,
            "promptVersion": null
          },
          "componentId": "019dd952-2e36-76f2-aee1-e17bb70a371f",
          "parentComponentId": null
        },
        {
          "bbox": {
            "h": 0.128,
            "w": 0.854,
            "x": 0.073,
            "y": 0.784
          },
          "kind": "image",
          "text": "Group of professionals in a meeting",
          "attrs": null,
          "canon": {
            "kind": {
              "name": "Image",
              "slug": "image",
              "status": "active",
              "canonId": "019de52c-f978-701f-a720-51d029d769e7",
              "version": 1,
              "description": "Photo, illustration, screenshot or icon."
            },
            "tool": null,
            "subkind": {
              "name": "Photo",
              "slug": "photo",
              "status": "active",
              "canonId": "019de52c-fd37-757f-b4a8-ca26d4888875",
              "version": 1,
              "description": null
            },
            "framework": null
          },
          "subkind": "photo",
          "groupRole": null,
          "confidence": null,
          "extraction": {
            "at": "2026-05-02 18:01:20.21+00",
            "model": "google/gemini-3.1-flash-lite-preview-20260303",
            "runId": null,
            "seconds": null,
            "promptVersion": null
          },
          "componentId": "ec91069d-485c-4a66-a3a5-6ee88c126c8b",
          "parentComponentId": null
        },
        {
          "bbox": {
            "h": 0.22,
            "w": 0.53,
            "x": 0.342,
            "y": 0.525
          },
          "kind": "list",
          "text": "Strategic planning for AI evolution: Develop a forward-thinking strategy for the adoption and ongoing evolution of AI within your organization. This strategy should be agile, capable of adapting to rapid technological advancements, shifts in company operations and the evolving landscape of AI. It's about creating an ecosystem where AI and human intelligence coalesce to drive innovation and efficiency.\nInvestment in resources and expertise: Commit to investing in the essential resources and knowledge required for effective AI integration. This commitment extends beyond financial investment; it encompasses dedicating time and effort to developing and training AI models, procuring the latest software and hardware, and establishing a robust infrastructure. This infrastructure should include advanced computational power, as well as secure data centers and comprehensive support services, to help make sure that the AI experience is seamless.",
          "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 18:01:20.21+00",
            "model": "google/gemini-3.1-flash-lite-preview-20260303",
            "runId": null,
            "seconds": null,
            "promptVersion": null
          },
          "componentId": "6d74d70c-fe37-4288-9326-4e3e241d74c6",
          "parentComponentId": null
        },
        {
          "bbox": {
            "h": 0.27,
            "w": 0.53,
            "x": 0.342,
            "y": 0.208
          },
          "kind": "list",
          "text": "Understand labor composition and tasks: Initiate a detailed analysis of your workforce, mapping out the various roles and responsibilities across all departments. This granular understanding is vital for pinpointing areas where AI can bring about transformative changes, help optimize operations and enhance task efficiency.\nCustomize AI application: Recognize the diversity in AI applicability. AI deployment is not a one-size-fits-all solution; it varies drastically across different industries and even within the same business sector. A meticulously crafted AI strategy, therefore, should be rooted in a comprehensive understanding of your organization's specific workforce dynamics and how various AI tools can be leveraged to streamline and enhance these unique operational aspects.\nFocus on enhancement, not replacement: Aim to integrate AI in a way that complements and elevates human work. The objective is to harness AI's capabilities to bolster job performance, allowing employees to shift their focus to aspects of their roles that necessitate human insight, creativity and decision-making.",
          "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 18:01:20.21+00",
            "model": "google/gemini-3.1-flash-lite-preview-20260303",
            "runId": null,
            "seconds": null,
            "promptVersion": null
          },
          "componentId": "f7350d85-0f76-4462-b9c1-794f51d44013",
          "parentComponentId": null
        },
        {
          "bbox": {
            "h": 0.045,
            "w": 0.2,
            "x": 0.09,
            "y": 0.197
          },
          "kind": "paragraph",
          "text": "Gregory Daco\nEY-Parthenon Chief Economist\nNew York, NY",
          "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 18:01:20.21+00",
            "model": "google/gemini-3.1-flash-lite-preview-20260303",
            "runId": null,
            "seconds": null,
            "promptVersion": null
          },
          "componentId": "762b2df9-6075-4ecc-b561-591c4654a3d6",
          "parentComponentId": null
        },
        {
          "bbox": {
            "h": 0.04,
            "w": 0.53,
            "x": 0.342,
            "y": 0.157
          },
          "kind": "title",
          "text": "Pillar 1: Developing a tailored AI utilization and deployment plan",
          "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 18:01:20.21+00",
            "model": "google/gemini-3.1-flash-lite-preview-20260303",
            "runId": null,
            "seconds": null,
            "promptVersion": null
          },
          "componentId": "0fd8df71-19f0-490c-9aa6-ab8dafb5f585",
          "parentComponentId": null
        },
        {
          "bbox": {
            "h": 0.018,
            "w": 0.115,
            "x": 0.09,
            "y": 0.163
          },
          "kind": "title",
          "text": "Key contact",
          "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 18:01:20.21+00",
            "model": "google/gemini-3.1-flash-lite-preview-20260303",
            "runId": null,
            "seconds": null,
            "promptVersion": null
          },
          "componentId": "5d67c76e-0c81-4433-81ef-469f69b4d2c3",
          "parentComponentId": null
        },
        {
          "bbox": {
            "h": 0.02,
            "w": 0.45,
            "x": 0.342,
            "y": 0.498
          },
          "kind": "title",
          "text": "Pillar 2: Developing and maintaining AI resources",
          "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 18:01:20.21+00",
            "model": "google/gemini-3.1-flash-lite-preview-20260303",
            "runId": null,
            "seconds": null,
            "promptVersion": null
          },
          "componentId": "b7708b5a-873b-4494-9564-2b9d53d74df6",
          "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": "3a181e78-d9a6-48e5-a888-d50d3b01a8fe",
          "evidence": "The slide uses a list/bullet format to present information.",
          "pageRefs": null,
          "priority": null,
          "whenToUse": null,
          "confidence": 0.7,
          "extraction": {
            "at": "2026-07-16 21:49:24.181101+00",
            "model": "or:meta-llama/llama-4-scout",
            "runId": null,
            "seconds": null,
            "promptVersion": null
          },
          "pageNumber": 15,
          "whyItWorks": null,
          "antipattern": null,
          "cardinality": "common",
          "narrativePurpose": null
        },
        {
          "tool": {
            "name": "Three Pillars",
            "slug": "three-pillars",
            "status": "active",
            "bestFor": null,
            "canonId": "019dd956-81ef-7455-a365-b234d95a6bbb",
            "version": 1,
            "bodyDocId": null,
            "description": "Three major supporting arguments that are MECE and address key concerns",
            "familyLabel": null,
            "categoryName": "Block",
            "categorySlug": "block"
          },
          "agent": "Architect",
          "layer": "slide",
          "agents": [
            "Architect"
          ],
          "matchId": "abf14298-5e9b-4e02-904d-7bc1c0588575",
          "evidence": "The slide presents three pillars for developing a tailored AI utilization and deployment plan.",
          "pageRefs": null,
          "priority": "Core",
          "whenToUse": null,
          "confidence": 0.7,
          "extraction": {
            "at": "2026-07-16 21:49:24.14577+00",
            "model": "or:meta-llama/llama-4-scout",
            "runId": null,
            "seconds": null,
            "promptVersion": null
          },
          "pageNumber": 15,
          "whyItWorks": null,
          "antipattern": null,
          "cardinality": null,
          "narrativePurpose": null
        }
      ],
      "frameworks": [],
      "arcBeats": [
        {
          "to": 15,
          "arc": {
            "name": "The Consultant's Gambit",
            "slug": "consultants-gambit",
            "status": "active",
            "bestFor": "Business cases, project proposals, strategic recommendations",
            "canonId": "019dd956-5e0a-73c8-b305-81c38c959e9c",
            "version": 1,
            "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49",
            "structure": "Situation & Context -> Problem & Complication -> Solution & Approach -> Evidence & Proof -> Impact & Next Steps",
            "description": null,
            "familyLabel": null
          },
          "from": 14,
          "name": "Impact & Next Steps",
          "beatId": "9b3c4797-5730-4279-a276-4e3a6b90e40b",
          "matchId": "424d33e4-517f-4ec9-b9d0-2d8a129b071e",
          "beatType": {
            "name": "Impact & Next Steps",
            "slug": "consultants-gambit-impact-next-steps",
            "status": "active",
            "canonId": "019dd9b8-0849-7728-9ee9-fd1609c4c655",
            "version": 1,
            "description": null
          },
          "evidence": "The business implications and recommendation provide guidance for businesses",
          "position": 3,
          "isPrimaryArc": true,
          "parentBeatType": {
            "name": "Resolution",
            "slug": "resolution",
            "status": "active",
            "canonId": "019dd9b8-045d-703b-8dd7-e92aba3ba91b",
            "version": 1,
            "description": "How the deck ends. Required in 19/20 arcs. The exception (Sparkline) ends with new bliss which is functionally a resolution."
          },
          "alignedBlockIds": null,
          "matchConfidence": 0.8
        }
      ],
      "loops": [
        {
          "to": 15,
          "from": 14,
          "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": "673cd046-6dde-4d2b-a046-feb6d0c92238",
          "evidence": "The business implications and recommendation highlight the importance of adapting to GenAI",
          "position": 1,
          "objective": "What are the business implications of not adapting to GenAI?",
          "confidence": 0.6,
          "extraction": {
            "at": "2026-07-16 21:19:48.55105+00",
            "model": "or:meta-llama/llama-4-scout",
            "runId": null,
            "seconds": null,
            "promptVersion": "doc-narrative-v1"
          }
        }
      ],
      "locked": true
    },
    {
      "page": 16,
      "type": "setup",
      "function": "summarize",
      "rawType": "disclaimer",
      "block": null,
      "metadata": {
        "slideType": "disclaimer",
        "slideTypeCanon": {
          "name": "Disclaimer",
          "slug": "disclaimer",
          "status": "active",
          "canonId": "019de52d-0801-727b-b98a-5ed095aeee78",
          "version": 1,
          "description": null
        },
        "function": "summarize",
        "functionCanon": {
          "name": "Summarize",
          "slug": "summarize",
          "status": "active",
          "canonId": "019de52d-1541-704f-b86f-bf7b75056373",
          "version": 1,
          "description": null
        },
        "density": "overcrowded",
        "densityScore": 82,
        "componentCount": 10,
        "textChars": 1309,
        "nDataPoints": 0,
        "notes": null,
        "elementsJson": [
          "paragraph",
          "logo_grid"
        ],
        "confidence": 1,
        "extraction": {
          "model": "google/gemini-3.1-flash-lite-preview-20260303",
          "runId": null,
          "at": "2026-05-02 18:01:20.127+00",
          "seconds": 3.555,
          "promptVersion": "v2-canon-conditioned"
        }
      },
      "links": {
        "slide": "/slides/019dd923-5e88-73ef-bd59-b7c870c8c8e8/16",
        "deck": "/decks/019dd923-5e88-73ef-bd59-b7c870c8c8e8",
        "deckAnchor": "/decks/019dd923-5e88-73ef-bd59-b7c870c8c8e8#slide-16",
        "deckJson": "/decks/019dd923-5e88-73ef-bd59-b7c870c8c8e8.json"
      },
      "components": [
        {
          "bbox": {
            "h": 0.08,
            "w": 0.4,
            "x": 0.05,
            "y": 0.31
          },
          "kind": "disclaimer",
          "text": "EY refers to the global organization, and may refer to one or more, of the member firms of Ernst & Young Global Limited, each of which is a separate legal entity.",
          "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 18:01:20.127+00",
            "model": "google/gemini-3.1-flash-lite-preview-20260303",
            "runId": null,
            "seconds": null,
            "promptVersion": null
          },
          "componentId": "1527c78e-a4e7-40bd-8fc7-058ca38b452c",
          "parentComponentId": null
        },
        {
          "bbox": {
            "h": 0.08,
            "w": 0.2,
            "x": 0.5,
            "y": 0.31
          },
          "kind": "disclaimer",
          "text": "© 2024 Ernst & Young LLP. All Rights Reserved. US SCORE no. 22415-241US 2311-4376751 ED None",
          "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 18:01:20.127+00",
            "model": "google/gemini-3.1-flash-lite-preview-20260303",
            "runId": null,
            "seconds": null,
            "promptVersion": null
          },
          "componentId": "9c2c7631-f231-447c-a1b3-8a5dff42b5e7",
          "parentComponentId": null
        },
        {
          "bbox": {
            "h": 0.04,
            "w": 0.4,
            "x": 0.5,
            "y": 0.4
          },
          "kind": "disclaimer",
          "text": "This material has been prepared for general informational purposes only and is not intended to be relied upon as accounting, tax, legal or other professional advice.",
          "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 18:01:20.127+00",
            "model": "google/gemini-3.1-flash-lite-preview-20260303",
            "runId": null,
            "seconds": null,
            "promptVersion": null
          },
          "componentId": "e0304472-a492-4314-9c8b-df8bc5362c49",
          "parentComponentId": null
        },
        {
          "bbox": {
            "h": 0.06,
            "w": 0.4,
            "x": 0.5,
            "y": 0.11
          },
          "kind": "paragraph",
          "text": "EY-Parthenon teams work with clients to navigate complexity by helping them to reimagine their ecosystems, reshape their portfolios and reinvent themselves for a better future.",
          "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 18:01:20.127+00",
            "model": "google/gemini-3.1-flash-lite-preview-20260303",
            "runId": null,
            "seconds": null,
            "promptVersion": null
          },
          "componentId": "6e1d760a-0864-448b-aa63-90c13b63fbe7",
          "parentComponentId": null
        },
        {
          "bbox": {
            "h": 0.06,
            "w": 0.4,
            "x": 0.05,
            "y": 0.16
          },
          "kind": "paragraph",
          "text": "Enabled by data and technology, diverse EY teams in over 150 countries provide trust through assurance and help clients grow, transform and operate.",
          "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 18:01:20.127+00",
            "model": "google/gemini-3.1-flash-lite-preview-20260303",
            "runId": null,
            "seconds": null,
            "promptVersion": null
          },
          "componentId": "91ebd902-fa0d-4f46-a3c2-80293b431b18",
          "parentComponentId": null
        },
        {
          "bbox": {
            "h": 0.06,
            "w": 0.4,
            "x": 0.05,
            "y": 0.09
          },
          "kind": "paragraph",
          "text": "EY exists to build a better working world, helping to create long-term value for clients, people and society and build trust in the capital 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 18:01:20.127+00",
            "model": "google/gemini-3.1-flash-lite-preview-20260303",
            "runId": null,
            "seconds": null,
            "promptVersion": null
          },
          "componentId": "b4696e0e-0465-4b20-803f-19d3950ebb89",
          "parentComponentId": null
        },
        {
          "bbox": {
            "h": 0.06,
            "w": 0.4,
            "x": 0.05,
            "y": 0.23
          },
          "kind": "paragraph",
          "text": "Working across assurance, consulting, law, strategy, tax and transactions, EY teams ask better questions to find new answers for the complex issues facing our world today.",
          "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 18:01:20.127+00",
            "model": "google/gemini-3.1-flash-lite-preview-20260303",
            "runId": null,
            "seconds": null,
            "promptVersion": null
          },
          "componentId": "d7edee78-a97c-4e3a-af13-36df39387a4c",
          "parentComponentId": null
        },
        {
          "bbox": {
            "h": 0.08,
            "w": 0.4,
            "x": 0.5,
            "y": 0.18
          },
          "kind": "paragraph",
          "text": "EY-Parthenon teams focus on Strategy Realized – helping CEOs design and deliver strategies to better manage challenges while maximizing opportunities as they look to transform their businesses.",
          "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 18:01:20.127+00",
            "model": "google/gemini-3.1-flash-lite-preview-20260303",
            "runId": null,
            "seconds": null,
            "promptVersion": null
          },
          "componentId": "e3cf54c8-0ba1-4671-b75f-3125f24bda45",
          "parentComponentId": null
        },
        {
          "bbox": {
            "h": 0.02,
            "w": 0.2,
            "x": 0.5,
            "y": 0.08
          },
          "kind": "title",
          "text": "About EY-Parthenon",
          "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 18:01:20.127+00",
            "model": "google/gemini-3.1-flash-lite-preview-20260303",
            "runId": null,
            "seconds": null,
            "promptVersion": null
          },
          "componentId": "2ad36c03-c5d2-4f70-93cf-50eeee9b6b5b",
          "parentComponentId": null
        },
        {
          "bbox": {
            "h": 0.03,
            "w": 0.35,
            "x": 0.05,
            "y": 0.05
          },
          "kind": "title",
          "text": "EY | Building a better working world",
          "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 18:01:20.127+00",
            "model": "google/gemini-3.1-flash-lite-preview-20260303",
            "runId": null,
            "seconds": null,
            "promptVersion": null
          },
          "componentId": "ad6d761c-11ec-476c-aa77-1961baa595ce",
          "parentComponentId": null
        }
      ],
      "metrics": [],
      "tools": [
        {
          "tool": {
            "name": "Executive summary",
            "slug": "executive-summary",
            "status": "active",
            "bestFor": null,
            "canonId": "019dd9e1-4b63-72d5-9734-da757d91ca61",
            "version": 1,
            "bodyDocId": null,
            "description": "A condensed view of the entire argument on a single slide / block.",
            "familyLabel": null,
            "categoryName": null,
            "categorySlug": null
          },
          "agent": null,
          "layer": "slide",
          "agents": null,
          "matchId": "b8b93fb9-933e-4785-80ea-83d4b82244d7",
          "evidence": "The slide provides a brief overview of EY-Parthenon's focus and approach.",
          "pageRefs": null,
          "priority": null,
          "whenToUse": null,
          "confidence": 0.7,
          "extraction": {
            "at": "2026-07-16 21:49:24.248541+00",
            "model": "or:meta-llama/llama-4-scout",
            "runId": null,
            "seconds": null,
            "promptVersion": null
          },
          "pageNumber": 16,
          "whyItWorks": null,
          "antipattern": null,
          "cardinality": "common",
          "narrativePurpose": null
        }
      ],
      "frameworks": [],
      "arcBeats": [],
      "loops": [],
      "locked": true
    }
  ],
  "arcBeats": [
    {
      "from": 1,
      "to": 2,
      "label": "Situation & Context",
      "description": "The cover and executive summary provide an overview of the topic"
    },
    {
      "from": 3,
      "to": 5,
      "label": "Problem & Complication",
      "description": "The key takeaways and data tables highlight the complex effects of GenAI on the labor market"
    },
    {
      "from": 6,
      "to": 10,
      "label": "Evidence & Proof",
      "description": "The data tables and industry trends provide evidence of GenAI's impact on various sectors"
    },
    {
      "from": 14,
      "to": 15,
      "label": "Impact & Next Steps",
      "description": "The business implications and recommendation provide guidance for businesses"
    }
  ],
  "loops": [
    {
      "from": 3,
      "to": 5,
      "label": "Logic Chain",
      "description": "What are the key findings of GenAI's potential impact on the labor market?"
    },
    {
      "from": 14,
      "to": 15,
      "label": "Cost Of Inaction",
      "description": "What are the business implications of not adapting to GenAI?"
    }
  ]
}