{
  "docId": "019dd923-5ca1-7489-b636-1905a2ddbc1f",
  "docSlug": "ad42cfa8e31c0209",
  "documentTitle": "Rise of Agentic AI Report",
  "authorId": "Capgemini",
  "authorName": "Capgemini",
  "documentKindSlug": "consulting-deck",
  "documentKindLabel": "Consulting deck",
  "sourceTypeSlug": "strategy_consulting",
  "sourceTypeLabel": "Strategy consulting",
  "presentationDate": null,
  "orientation": "landscape",
  "aspectRatio": 1.778,
  "pageNumber": 98,
  "pageCount": 116,
  "prevPage": 97,
  "nextPage": 99,
  "slideType": "data_table",
  "function": "quantify_impact",
  "density": "balanced",
  "nDataPoints": 21,
  "notes": "The table uses a step-by-step calculation logic (A through G) to arrive at estimated revenue growth per organization.",
  "elementsJson": [
    "headline_text",
    "paragraph",
    "data_table"
  ],
  "metadataConfidence": 1,
  "imagePath": null,
  "slideHref": "/slides/019dd923-5ca1-7489-b636-1905a2ddbc1f/98",
  "deckHref": "/decks/019dd923-5ca1-7489-b636-1905a2ddbc1f",
  "deckJsonHref": "/decks/019dd923-5ca1-7489-b636-1905a2ddbc1f.json",
  "deckAnchorHref": "/decks/019dd923-5ca1-7489-b636-1905a2ddbc1f#slide-98",
  "components": [
    {
      "bbox": null,
      "kind": "callout",
      "text": "In this approach, we assume that the full value of expected revenue growth and cost savings from agentic AI accrues to all organizations, regardless of their level of scaling.",
      "attrs": null,
      "subkind": null,
      "toolName": "Visual emphasis",
      "toolSlug": "visual-emphasis",
      "confidence": null,
      "componentId": "019dd951-ba89-733e-97f3-ab796a5b475c",
      "frameworkName": null,
      "frameworkSlug": null
    },
    {
      "bbox": null,
      "kind": "metric",
      "text": "Economic value: $3.3 trillion",
      "attrs": null,
      "subkind": "primary",
      "toolName": "Quantification",
      "toolSlug": "quantification",
      "confidence": null,
      "componentId": "019dd951-ba89-733e-97f3-ae0a32375511",
      "frameworkName": null,
      "frameworkSlug": null
    },
    {
      "bbox": {
        "h": 0.03,
        "w": 0.85,
        "x": 0.045,
        "y": 0.28
      },
      "kind": "paragraph",
      "text": "In this approach, we assume that the full value of expected revenue growth and cost savings from agentic AI accrues to all organizations, regardless of their level of scaling.",
      "attrs": null,
      "subkind": "paragraph",
      "toolName": null,
      "toolSlug": null,
      "confidence": null,
      "componentId": "ab987879-28b2-4beb-97b9-e1a2375731c4",
      "frameworkName": null,
      "frameworkSlug": null
    },
    {
      "bbox": {
        "h": 0.55,
        "w": 0.91,
        "x": 0.045,
        "y": 0.33
      },
      "kind": "table",
      "text": "Calculation table showing rows A-G for years 2025, 2026, 2027",
      "attrs": null,
      "subkind": "data",
      "toolName": null,
      "toolSlug": null,
      "confidence": null,
      "componentId": "36a2a0be-cd1b-40af-b2e4-866134ecb3ff",
      "frameworkName": null,
      "frameworkSlug": null
    },
    {
      "bbox": {
        "h": 0.02,
        "w": 0.49,
        "x": 0.045,
        "y": 0.24
      },
      "kind": "title",
      "text": "Approach 2: $3.3 trillion in economic value over the next three years in surveyed countries.",
      "attrs": null,
      "subkind": "headline",
      "toolName": null,
      "toolSlug": null,
      "confidence": null,
      "componentId": "c9fb8559-c66e-4429-8bb9-a8ee3a05c6c4",
      "frameworkName": null,
      "frameworkSlug": null
    }
  ],
  "metrics": [
    {
      "metricRaw": "Economic value",
      "numberRaw": "$3.3 trillion",
      "numberKind": "money",
      "actionTitle": "Approach 2: $3.3 trillion in economic value over the next three years in surveyed countries.",
      "calloutText": "In this approach, we assume that the full value of expected revenue growth and cost savings from agentic AI accrues to all organizations, regardless of their level of scaling.",
      "numberScale": "t",
      "numberValue": 3.3,
      "metricFamily": "market_size",
      "numberCurrency": "$"
    }
  ],
  "tools": [],
  "frameworks": [
    {
      "name": "logical-chain",
      "slug": null,
      "matchId": "324e35c1-0dfb-46b0-b21e-53224000e304",
      "evidence": "The table presents a step-by-step calculation (A*E*F=G) to derive economic impact.",
      "confidence": 0.9
    }
  ],
  "arcBeats": [],
  "loops": [],
  "imagePathAlt": null,
  "thumbSrc": null,
  "thumbSrcAlt": null,
  "locked": true
}