{
  "docId": "019dd923-5ca1-7489-b635-564114f9d8e5",
  "docSlug": "6343adff3aaa1ea3",
  "documentTitle": "AI Radar 2025",
  "authorId": "BCG",
  "authorName": "BCG",
  "documentKindSlug": "consulting-deck",
  "documentKindLabel": "Consulting deck",
  "sourceTypeSlug": "strategy_consulting",
  "sourceTypeLabel": "Strategy consulting",
  "presentationDate": null,
  "orientation": "landscape",
  "aspectRatio": 1.91,
  "pageNumber": 25,
  "pageCount": 27,
  "prevPage": 24,
  "nextPage": 26,
  "slideType": "peer_benchmark",
  "function": "compare_peers",
  "density": "balanced",
  "nDataPoints": 11,
  "notes": "The chart uses color coding to distinguish performance tiers relative to the global average.",
  "elementsJson": [
    "headline_text",
    "bar_chart_horizontal",
    "footnote"
  ],
  "metadataConfidence": 1,
  "imagePath": null,
  "slideHref": "/slides/019dd923-5ca1-7489-b635-564114f9d8e5/25",
  "deckHref": "/decks/019dd923-5ca1-7489-b635-564114f9d8e5",
  "deckJsonHref": "/decks/019dd923-5ca1-7489-b635-564114f9d8e5.json",
  "deckAnchorHref": "/decks/019dd923-5ca1-7489-b635-564114f9d8e5#slide-25",
  "components": [
    {
      "bbox": {
        "h": 0.75,
        "w": 0.55,
        "x": 0.4,
        "y": 0.15
      },
      "kind": "chart",
      "text": "Horizontal bar chart showing training percentages by country",
      "attrs": null,
      "subkind": "bar-horizontal",
      "toolName": null,
      "toolSlug": null,
      "confidence": null,
      "componentId": "3a38ca00-3c11-4bb0-b5fd-a98974ed304f",
      "frameworkName": null,
      "frameworkSlug": null
    },
    {
      "bbox": null,
      "kind": "metric",
      "text": "Percentage of companies with >25% workforce trained: 44%",
      "attrs": null,
      "subkind": "primary",
      "toolName": "Quantification",
      "toolSlug": "quantification",
      "confidence": null,
      "componentId": "019dd951-acb8-762a-a741-818ef7fee1c4",
      "frameworkName": null,
      "frameworkSlug": null
    },
    {
      "bbox": {
        "h": 0.05,
        "w": 0.2,
        "x": 0.05,
        "y": 0.9
      },
      "kind": "source-note",
      "text": "Source: BCG AI Radar 2025 Survey (n=1,803).",
      "attrs": null,
      "subkind": null,
      "toolName": null,
      "toolSlug": null,
      "confidence": null,
      "componentId": "0424188a-3fcf-4b24-84fe-e81fb33a3c3d",
      "frameworkName": null,
      "frameworkSlug": null
    },
    {
      "bbox": {
        "h": 0.05,
        "w": 0.5,
        "x": 0.4,
        "y": 0.08
      },
      "kind": "title",
      "text": "Companies with more than one-quarter of their workforce trained on AI/GenAI tools",
      "attrs": null,
      "subkind": "headline",
      "toolName": null,
      "toolSlug": null,
      "confidence": null,
      "componentId": "1bc9c359-6933-4bbc-88e8-e806cd0e300d",
      "frameworkName": null,
      "frameworkSlug": null
    },
    {
      "bbox": {
        "h": 0.4,
        "w": 0.3,
        "x": 0.05,
        "y": 0.2
      },
      "kind": "title",
      "text": "Singapore and Japan lead in AI/GenAI upskilling; Brazil and Italy are falling behind",
      "attrs": null,
      "subkind": "headline",
      "toolName": null,
      "toolSlug": null,
      "confidence": null,
      "componentId": "4e5123e2-53a8-4dfa-8fbb-7f6bf6ca1e4f",
      "frameworkName": null,
      "frameworkSlug": null
    }
  ],
  "metrics": [
    {
      "metricRaw": "Percentage of companies with >25% workforce trained",
      "numberRaw": "44%",
      "numberKind": "percent",
      "actionTitle": "Singapore and Japan lead in AI/GenAI upskilling; Brazil and Italy are falling behind",
      "calloutText": null,
      "numberScale": null,
      "numberValue": 44,
      "metricFamily": "survey_sentiment",
      "numberCurrency": null
    }
  ],
  "tools": [
    {
      "name": "Action Titles",
      "slug": "action-titles",
      "agent": "Architect",
      "layer": "slide",
      "matchId": "019dd95a-121f-71e6-8e90-56bc3c6f3445",
      "evidence": "Title names leaders (Singapore, Japan) and laggards (Brazil, Italy).",
      "confidence": 85
    },
    {
      "name": "Annotation",
      "slug": "annotation",
      "agent": "Designer",
      "layer": "slide",
      "matchId": "019dd95a-121f-71e6-8e90-65c10d4e329a",
      "evidence": "'29% globally' annotation marks the benchmark.",
      "confidence": 70
    },
    {
      "name": "Chart Selection Guide",
      "slug": "chart-selection-guide",
      "agent": "Designer",
      "layer": "slide",
      "matchId": "019dd95a-121f-71e6-8e90-58de87883b5b",
      "evidence": "Ranked horizontal bar chart by country.",
      "confidence": 85
    },
    {
      "name": "Color Strategy",
      "slug": "color-strategy",
      "agent": "Designer",
      "layer": "slide",
      "matchId": "019dd95a-121f-71e6-8e90-5f539f3f74f5",
      "evidence": "Greens (leaders), black (mid), grey (laggards) encode ranking.",
      "confidence": 80
    },
    {
      "name": "Slide recipe: the peer-gap chart",
      "slug": "peer-gap-chart-recipe",
      "agent": "designer",
      "layer": "slide",
      "matchId": "044cc31c-064a-4602-b8ca-6f42fac8626e",
      "evidence": "Singapore and Japan lead in AI/GenAI upskilling; Brazil and Italy are falling behind",
      "confidence": 0.6
    },
    {
      "name": "Visual Hierarchy",
      "slug": "visual-hierarchy",
      "agent": "Designer",
      "layer": "slide",
      "matchId": "019dd95a-121f-71e6-8e90-630a909abcca",
      "evidence": "Sorted descending; reference line at 29% global average.",
      "confidence": 70
    }
  ],
  "frameworks": [
    {
      "name": "comparison-frame",
      "slug": null,
      "matchId": "b4c46192-b2c9-40ee-92c6-3441f5968c45",
      "evidence": "Comparing country performance against a global benchmark",
      "confidence": 0.9
    }
  ],
  "arcBeats": [
    {
      "to": 25,
      "from": 14,
      "beatId": "019dd95a-0701-77fe-ae98-33649f64918f",
      "arcName": "The Consultant's Gambit",
      "arcSlug": "consultants-gambit",
      "beatName": "Evidence & Proof",
      "beatSlug": "consultants-gambit-evidence-proof",
      "evidence": "Risk data, agent adoption stats, geographic benchmarks, talent/upskilling proof.",
      "position": 4,
      "confidence": 82,
      "parentBeatName": "Evidence",
      "parentBeatSlug": "evidence"
    }
  ],
  "loops": [
    {
      "to": 25,
      "from": 21,
      "name": "Myth Buster",
      "slug": "12-myth-buster",
      "bestFor": "Rebranding, changing market perception, correcting false assumptions",
      "matchId": "019dd95a-088b-72c8-b7e0-d87146367b86",
      "evidence": "Divider asks 'humans or AI?'; p22-23 show talent complementary, <10% expect cuts; p24-25 upskilling progress.",
      "position": 5,
      "objective": "Bust the AI-replaces-humans myth",
      "structure": "The Common Belief -> The Friction/Failure of that Belief -> The New Truth",
      "confidence": 70,
      "description": "Address a common misconception head-on to clear the room for a new truth"
    }
  ],
  "imagePathAlt": null,
  "thumbSrc": null,
  "thumbSrcAlt": null,
  "locked": true
}