{
  "docId": "019dd923-5ca1-7489-b633-746ffdbc9114",
  "docSlug": "6543568fbc47af38",
  "documentTitle": "The age of AI: Banking’s new reality",
  "authorId": "Accenture",
  "authorName": "Accenture",
  "documentKindSlug": "consulting-deck",
  "documentKindLabel": "Consulting deck",
  "sourceTypeSlug": "strategy_consulting",
  "sourceTypeLabel": "Strategy consulting",
  "presentationDate": null,
  "orientation": "landscape",
  "aspectRatio": 1.778,
  "pageNumber": 13,
  "pageCount": 41,
  "prevPage": 12,
  "nextPage": 14,
  "slideType": "section_divider",
  "function": "transition",
  "density": "dense",
  "nDataPoints": 0,
  "notes": "Part of a multi-slide sequence indicated by the footer navigation.",
  "elementsJson": [
    "headline_text",
    "subtitle_text",
    "paragraph",
    "big_number",
    "photo"
  ],
  "metadataConfidence": 1,
  "imagePath": null,
  "slideHref": "/slides/019dd923-5ca1-7489-b633-746ffdbc9114/13",
  "deckHref": "/decks/019dd923-5ca1-7489-b633-746ffdbc9114",
  "deckJsonHref": "/decks/019dd923-5ca1-7489-b633-746ffdbc9114.json",
  "deckAnchorHref": "/decks/019dd923-5ca1-7489-b633-746ffdbc9114#slide-13",
  "components": [
    {
      "bbox": null,
      "kind": "callout",
      "text": "Since there are more potential use cases for generative AI than any bank could possibly explore at any one time (see Figure 2 next page), the big question is not what to do but rather what not to do—and therefore, how to prioritize adoption.",
      "attrs": null,
      "subkind": null,
      "toolName": "Visual emphasis",
      "toolSlug": "visual-emphasis",
      "confidence": null,
      "componentId": "019dd951-9f64-72ba-b40c-dc6f0bc40626",
      "frameworkName": null,
      "frameworkSlug": null
    },
    {
      "bbox": {
        "h": 0.473,
        "w": 0.334,
        "x": 0.666,
        "y": 0.322
      },
      "kind": "image",
      "text": null,
      "attrs": null,
      "subkind": "photo",
      "toolName": null,
      "toolSlug": null,
      "confidence": null,
      "componentId": "4904c3df-3b80-45aa-aab4-82c768a09bcd",
      "frameworkName": null,
      "frameworkSlug": null
    },
    {
      "bbox": {
        "h": 0.04,
        "w": 0.86,
        "x": 0.07,
        "y": 0.92
      },
      "kind": "list",
      "text": "Lead with value | Understand and develop a secure AI-enabled digital core | Reinvent talent and ways of working | Close the gap on responsible AI | Drive continuous reinvention | Measuring the ROI of generative AI",
      "attrs": null,
      "subkind": "bullet",
      "toolName": null,
      "toolSlug": null,
      "confidence": null,
      "componentId": "bb6fb51a-5523-4a82-b966-67881abc0cc3",
      "frameworkName": null,
      "frameworkSlug": null
    },
    {
      "bbox": {
        "h": 0.25,
        "w": 0.16,
        "x": 0.075,
        "y": 0.415
      },
      "kind": "other",
      "text": "1",
      "attrs": null,
      "subkind": "unclassified",
      "toolName": null,
      "toolSlug": null,
      "confidence": null,
      "componentId": "3d30f4e4-a825-44b4-99d8-c4c419daa679",
      "frameworkName": null,
      "frameworkSlug": null
    },
    {
      "bbox": {
        "h": 0.1,
        "w": 0.3,
        "x": 0.358,
        "y": 0.34
      },
      "kind": "paragraph",
      "text": "Since there are more potential use cases for generative AI than any bank could possibly explore at any one time (see Figure 2 next page), the big question is not what to do but rather what not to do—and therefore, how to prioritize adoption.",
      "attrs": null,
      "subkind": "paragraph",
      "toolName": null,
      "toolSlug": null,
      "confidence": null,
      "componentId": "b5a3c1a2-dc62-4f47-8cbc-cf594713a3cc",
      "frameworkName": null,
      "frameworkSlug": null
    },
    {
      "bbox": {
        "h": 0.035,
        "w": 0.235,
        "x": 0.358,
        "y": 0.255
      },
      "kind": "title",
      "text": "Lead with value",
      "attrs": null,
      "subkind": "action-title",
      "toolName": null,
      "toolSlug": null,
      "confidence": null,
      "componentId": "5232076f-02a6-453d-ad8a-a4c03eafebd6",
      "frameworkName": null,
      "frameworkSlug": null
    },
    {
      "bbox": {
        "h": 0.02,
        "w": 0.215,
        "x": 0.358,
        "y": 0.16
      },
      "kind": "title",
      "text": "IMPERATIVE ONE",
      "attrs": null,
      "subkind": "headline",
      "toolName": null,
      "toolSlug": null,
      "confidence": null,
      "componentId": "6c8774a9-6887-40ea-bb3b-5d7949fd6731",
      "frameworkName": null,
      "frameworkSlug": null
    }
  ],
  "metrics": [],
  "tools": [
    {
      "name": "Callback",
      "slug": "callback",
      "agent": "Storyteller",
      "layer": "loop",
      "matchId": "019dd95a-0f08-73d3-987a-1fc16d8eefd8",
      "evidence": "Header text repeats imperative 01 from p.12 to anchor the section",
      "confidence": 65
    },
    {
      "name": "The Turn",
      "slug": "the-turn",
      "agent": "Storyteller",
      "layer": "loop",
      "matchId": "019dd95a-0f08-73d3-987a-1bc49fd28f67",
      "evidence": "Section divider 'Lead with value' opens the first imperative deep dive",
      "confidence": 70
    },
    {
      "name": "Action Titles",
      "slug": "action-titles",
      "agent": "Architect",
      "layer": "slide",
      "matchId": "3134a2e8-b5e4-44cd-9f62-fc04bc1a7e30",
      "evidence": "title/action-title: Lead with value",
      "confidence": 0.7
    },
    {
      "name": "Section divider",
      "slug": "section-divider",
      "agent": null,
      "layer": "slide",
      "matchId": "44e62287-c9f7-4dce-ab6e-f02b16046e7b",
      "evidence": "type: section_divider",
      "confidence": 0.7
    }
  ],
  "frameworks": [],
  "arcBeats": [
    {
      "to": 34,
      "from": 13,
      "beatId": "019dd95a-0682-776c-8e32-635915b6754b",
      "arcName": "The Consultant's Gambit",
      "arcSlug": "consultants-gambit",
      "beatName": "Evidence & Proof",
      "beatSlug": "consultants-gambit-evidence-proof",
      "evidence": "Each imperative built out with figure, recommendation, named bank case study, and actions",
      "position": 4,
      "confidence": 92,
      "parentBeatName": "Evidence",
      "parentBeatSlug": "evidence"
    },
    {
      "to": 36,
      "from": 13,
      "beatId": "019dd95a-0682-776c-8e32-728a04f7c9a1",
      "arcName": "The Triple Take",
      "arcSlug": "triple-take",
      "beatName": "The Action (Now What)",
      "beatSlug": "triple-take-the-action-now-what",
      "evidence": "Per-imperative actions, case studies and ROI playbook",
      "position": 3,
      "confidence": 65,
      "parentBeatName": "Resolution",
      "parentBeatSlug": "resolution"
    }
  ],
  "loops": [
    {
      "to": 18,
      "from": 13,
      "name": "Zoom In",
      "slug": "06-zoom-in",
      "bestFor": "Technical deep-dives, case studies, detailed analysis",
      "matchId": "019dd95a-07fe-70ce-8d3a-205e8cf6e3eb",
      "evidence": "Divider -> heatmap of 50+ use cases -> recommendation -> European bank case -> action list",
      "position": 5,
      "objective": "Prove imperative 1 (Lead with value) end-to-end",
      "structure": "The Big Picture -> Key Area of Focus -> Specific Detail -> Implication",
      "confidence": 80,
      "description": "Start broad, then progressively focus on specific details that prove your point"
    }
  ],
  "imagePathAlt": null,
  "thumbSrc": null,
  "thumbSrcAlt": null,
  "locked": true
}