{
  "docId": "019dd923-5e88-73ef-bd5d-5e6879c28d6f",
  "docSlug": "150df15aa170c402",
  "documentTitle": "2025 Executive Perspectives Unlocking the Value Potential of AI",
  "authorId": "BCG",
  "authorName": "BCG",
  "documentKindSlug": "consulting-deck",
  "documentKindLabel": "Consulting deck",
  "sourceTypeSlug": "strategy_consulting",
  "sourceTypeLabel": "Strategy consulting",
  "presentationDate": null,
  "orientation": "landscape",
  "aspectRatio": 1.778,
  "pageNumber": 6,
  "pageCount": 22,
  "prevPage": 5,
  "nextPage": 7,
  "slideType": "industry_trends",
  "function": "establish_context",
  "density": "overcrowded",
  "nDataPoints": 5,
  "notes": "The slide uses a numbered list structure to present three distinct technological pillars.",
  "elementsJson": [
    "headline_text",
    "line_chart",
    "photo",
    "process_diagram",
    "paragraph"
  ],
  "metadataConfidence": 1,
  "imagePath": null,
  "slideHref": "/slides/019dd923-5e88-73ef-bd5d-5e6879c28d6f/6",
  "deckHref": "/decks/019dd923-5e88-73ef-bd5d-5e6879c28d6f",
  "deckJsonHref": "/decks/019dd923-5e88-73ef-bd5d-5e6879c28d6f.json",
  "deckAnchorHref": "/decks/019dd923-5e88-73ef-bd5d-5e6879c28d6f#slide-6",
  "components": [
    {
      "bbox": {
        "h": 0.4,
        "w": 0.3,
        "x": 0.05,
        "y": 0.35
      },
      "kind": "chart",
      "text": "AI compute power (TFLOPS) vs Moore's law",
      "attrs": null,
      "subkind": "line",
      "toolName": null,
      "toolSlug": null,
      "confidence": null,
      "componentId": "f6fc6b9a-ac1b-4d6b-afb0-c1d688b5186e",
      "frameworkName": null,
      "frameworkSlug": null
    },
    {
      "bbox": {
        "h": 0.4,
        "w": 0.28,
        "x": 0.68,
        "y": 0.35
      },
      "kind": "diagram",
      "text": "Vision-language action model (VLA) workflow",
      "attrs": null,
      "subkind": "process",
      "toolName": null,
      "toolSlug": null,
      "confidence": null,
      "componentId": "691274d3-2e1e-46a0-9547-ef0cffd55e1d",
      "frameworkName": null,
      "frameworkSlug": null
    },
    {
      "bbox": {
        "h": 0.4,
        "w": 0.25,
        "x": 0.38,
        "y": 0.35
      },
      "kind": "image",
      "text": "Simulation vs Real world comparison",
      "attrs": null,
      "subkind": "photo",
      "toolName": null,
      "toolSlug": null,
      "confidence": null,
      "componentId": "7d42bfaf-8ea6-4855-a237-5d49241edda9",
      "frameworkName": null,
      "frameworkSlug": null
    },
    {
      "bbox": {
        "h": 0.1,
        "w": 0.9,
        "x": 0.05,
        "y": 0.2
      },
      "kind": "list",
      "text": "1. Acceleration of computing power\n2. Narrowing of simulation to reality gap\n3. Development of foundation models",
      "attrs": null,
      "subkind": "numbered",
      "toolName": null,
      "toolSlug": null,
      "confidence": null,
      "componentId": "f95f1c4b-dbe4-47da-941c-a900b5ab6371",
      "frameworkName": null,
      "frameworkSlug": null
    },
    {
      "bbox": null,
      "kind": "metric",
      "text": "AI compute power (TFLOPS): 26",
      "attrs": null,
      "subkind": "primary",
      "toolName": "Quantification",
      "toolSlug": "quantification",
      "confidence": null,
      "componentId": "019dd952-47c6-7671-8876-87fe52a08b6a",
      "frameworkName": null,
      "frameworkSlug": null
    },
    {
      "bbox": {
        "h": 0.1,
        "w": 0.28,
        "x": 0.68,
        "y": 0.8
      },
      "kind": "paragraph",
      "text": "Enables AI systems that learn from surroundings to perform a wide range of tasks, even in unfamiliar environments",
      "attrs": null,
      "subkind": "paragraph",
      "toolName": null,
      "toolSlug": null,
      "confidence": null,
      "componentId": "22705f7c-5eda-4ff0-8000-e94a306d5d28",
      "frameworkName": null,
      "frameworkSlug": null
    },
    {
      "bbox": {
        "h": 0.1,
        "w": 0.28,
        "x": 0.05,
        "y": 0.8
      },
      "kind": "paragraph",
      "text": "Massive increases in compute power enable next-level analytics and simulation at lower costs",
      "attrs": null,
      "subkind": "paragraph",
      "toolName": null,
      "toolSlug": null,
      "confidence": null,
      "componentId": "68acc2e2-f2a9-4975-9c02-5ca6c67b2639",
      "frameworkName": null,
      "frameworkSlug": null
    },
    {
      "bbox": {
        "h": 0.1,
        "w": 0.28,
        "x": 0.38,
        "y": 0.8
      },
      "kind": "paragraph",
      "text": "Allows for accurate training of AI models for wide varieties of applications, even when real data is scarce",
      "attrs": null,
      "subkind": "paragraph",
      "toolName": null,
      "toolSlug": null,
      "confidence": null,
      "componentId": "b3595651-8fd7-42d8-8583-d2b1a849bf02",
      "frameworkName": null,
      "frameworkSlug": null
    },
    {
      "bbox": {
        "h": 0.08,
        "w": 0.9,
        "x": 0.05,
        "y": 0.05
      },
      "kind": "title",
      "text": "Why now? Three foundational technologies are redefining what's possible",
      "attrs": null,
      "subkind": "headline",
      "toolName": null,
      "toolSlug": null,
      "confidence": null,
      "componentId": "62802bee-07d0-4e82-997b-aa349c37578e",
      "frameworkName": null,
      "frameworkSlug": null
    }
  ],
  "metrics": [],
  "tools": [
    {
      "name": "Curiosity Gap",
      "slug": "curiosity-gap",
      "agent": "Storyteller",
      "layer": "block",
      "matchId": "019dd95a-121f-71e6-8e8c-986417ac8843",
      "evidence": "Question framing creates information gap to be filled",
      "confidence": 65
    },
    {
      "name": "The Rule of Three",
      "slug": "the-rule-of-three",
      "agent": "Storyteller",
      "layer": "block",
      "matchId": "019dd95a-121f-71e6-8e8c-92d6aa47d174",
      "evidence": "Three numbered enabling technologies in parallel columns",
      "confidence": 88
    },
    {
      "name": "Action Titles",
      "slug": "action-titles",
      "agent": "Architect",
      "layer": "slide",
      "matchId": "019dd95a-121f-71e6-8e8c-8b93b3b0f6ab",
      "evidence": "Title asks and answers: 'Why now? Three foundational technologies'",
      "confidence": 92
    },
    {
      "name": "Concrete Language",
      "slug": "concrete-language",
      "agent": "Storyteller",
      "layer": "slide",
      "matchId": "019dd95a-121f-71e6-8e8c-95688c6d4b44",
      "evidence": "TFLOPS chart, x1000 in 8 years, x25 vs Moore's law",
      "confidence": 80
    },
    {
      "name": "Opening Hooks",
      "slug": "opening-hooks",
      "agent": "Storyteller",
      "layer": "slide",
      "matchId": "019dd95a-121f-71e6-8e8c-8e7926039220",
      "evidence": "Provocative question 'Why now?' opens the section",
      "confidence": 80
    }
  ],
  "frameworks": [],
  "arcBeats": [
    {
      "to": 6,
      "from": 3,
      "beatId": "019dd95a-0701-77fe-ae97-c52481d035ed",
      "arcName": "The Consultant's Gambit",
      "arcSlug": "consultants-gambit",
      "beatName": "Problem & Complication",
      "beatSlug": "consultants-gambit-problem-complication",
      "evidence": "Cost competitiveness, labor shortages; 'why now' technology triggers",
      "position": 2,
      "confidence": 88,
      "parentBeatName": "Complication",
      "parentBeatSlug": "complication"
    }
  ],
  "loops": [
    {
      "to": 6,
      "from": 4,
      "name": "Why Now",
      "slug": "15-why-now",
      "bestFor": "Sales pitches, fundraising, requesting immediate budget approval",
      "matchId": "019dd95a-088b-72c8-b7e0-8c3011c03117",
      "evidence": "p6 explicitly titled 'Why now? Three foundational technologies'",
      "position": 1,
      "objective": "Establish urgency via tech triggers",
      "structure": "The Context (Trends) -> The Trigger Event -> The Window of Opportunity",
      "confidence": 90,
      "description": "Create temporal urgency by proving that the window of opportunity is opening or closing"
    }
  ],
  "imagePathAlt": null,
  "thumbSrc": null,
  "thumbSrcAlt": null,
  "locked": true
}