{
  "docId": "019dd923-5ca1-7489-b636-83d9001ae71a",
  "docSlug": "1f4828d675dd67cf",
  "documentTitle": "Insights from the leading edge of generative AI adoption",
  "authorId": "Deloitte",
  "authorName": "Deloitte",
  "documentKindSlug": "consulting-deck",
  "documentKindLabel": "Consulting deck",
  "sourceTypeSlug": "strategy_consulting",
  "sourceTypeLabel": "Strategy consulting",
  "presentationDate": null,
  "orientation": "landscape",
  "aspectRatio": 1.778,
  "pageNumber": 15,
  "pageCount": 34,
  "prevPage": 14,
  "nextPage": 16,
  "slideType": "key_takeaways",
  "function": "summarize",
  "density": "overcrowded",
  "nDataPoints": 4,
  "notes": "The slide contrasts current tactical adoption with future potential for strategic, differentiated use cases.",
  "elementsJson": [
    "headline_text",
    "action_title",
    "paragraph",
    "callout_box",
    "big_number"
  ],
  "metadataConfidence": 1,
  "imagePath": null,
  "slideHref": "/slides/019dd923-5ca1-7489-b636-83d9001ae71a/15",
  "deckHref": "/decks/019dd923-5ca1-7489-b636-83d9001ae71a",
  "deckJsonHref": "/decks/019dd923-5ca1-7489-b636-83d9001ae71a.json",
  "deckAnchorHref": "/decks/019dd923-5ca1-7489-b636-83d9001ae71a#slide-15",
  "components": [
    {
      "bbox": {
        "h": 0.06,
        "w": 0.25,
        "x": 0.64,
        "y": 0.245
      },
      "kind": "callout",
      "text": "Where off-the-shelf generative AI is used most",
      "attrs": null,
      "subkind": "primary",
      "toolName": null,
      "toolSlug": null,
      "confidence": null,
      "componentId": "a371ce0d-159e-413b-a51e-30d9f7beaced",
      "frameworkName": null,
      "frameworkSlug": null
    },
    {
      "bbox": null,
      "kind": "callout",
      "text": "In line with their current emphasis on tactical benefits from generative AI, the vast majority of respondents were currently relying on off-the-shelf solutions.",
      "attrs": null,
      "subkind": null,
      "toolName": "Visual emphasis",
      "toolSlug": "visual-emphasis",
      "confidence": null,
      "componentId": "019dd951-ba8c-7422-8543-252bd9383cc4",
      "frameworkName": null,
      "frameworkSlug": null
    },
    {
      "bbox": {
        "h": 0.05,
        "w": 0.25,
        "x": 0.64,
        "y": 0.66
      },
      "kind": "metric",
      "text": "56% Public LLMs",
      "attrs": null,
      "subkind": "big-number",
      "toolName": null,
      "toolSlug": null,
      "confidence": null,
      "componentId": "28eeeb1e-df36-4645-9bd6-de5f18f50dfa",
      "frameworkName": null,
      "frameworkSlug": null
    },
    {
      "bbox": {
        "h": 0.05,
        "w": 0.25,
        "x": 0.64,
        "y": 0.36
      },
      "kind": "metric",
      "text": "71% Productivity applications",
      "attrs": null,
      "subkind": "big-number",
      "toolName": null,
      "toolSlug": null,
      "confidence": null,
      "componentId": "94d3203f-779f-4b4d-8118-e4a7b36cf877",
      "frameworkName": null,
      "frameworkSlug": null
    },
    {
      "bbox": {
        "h": 0.05,
        "w": 0.25,
        "x": 0.64,
        "y": 0.46
      },
      "kind": "metric",
      "text": "68% Standard applications",
      "attrs": null,
      "subkind": "big-number",
      "toolName": null,
      "toolSlug": null,
      "confidence": null,
      "componentId": "b3fd705f-d89e-4b30-a6e6-23dfac8a5375",
      "frameworkName": null,
      "frameworkSlug": null
    },
    {
      "bbox": {
        "h": 0.05,
        "w": 0.25,
        "x": 0.64,
        "y": 0.56
      },
      "kind": "metric",
      "text": "61% Enterprise platforms",
      "attrs": null,
      "subkind": "big-number",
      "toolName": null,
      "toolSlug": null,
      "confidence": null,
      "componentId": "eed9908d-c760-498d-99c1-8947687d5883",
      "frameworkName": null,
      "frameworkSlug": null
    },
    {
      "bbox": null,
      "kind": "metric",
      "text": "Adoption rate: 71%",
      "attrs": null,
      "subkind": "primary",
      "toolName": "Quantification",
      "toolSlug": "quantification",
      "confidence": null,
      "componentId": "019dd951-ba8c-7422-8543-28e85f587910",
      "frameworkName": null,
      "frameworkSlug": null
    },
    {
      "bbox": {
        "h": 0.18,
        "w": 0.5,
        "x": 0.06,
        "y": 0.71
      },
      "kind": "paragraph",
      "text": "When will we see complex, high-value use cases that are truly differentiated and tailored to the specialized needs of specific companies, functions and industries? How will organizations combine internal and external resources to create customized generative AI tools that enable such strategic differentiation? In particular, will we see off-the-shelf technology offerings be supplemented by private or hybrid public/private development approaches and technology infrastructures capable of delivering and supporting those differentiated solutions?",
      "attrs": null,
      "subkind": "paragraph",
      "toolName": null,
      "toolSlug": null,
      "confidence": null,
      "componentId": "0d192142-a517-4546-90a0-f0aefd3c5ca3",
      "frameworkName": null,
      "frameworkSlug": null
    },
    {
      "bbox": {
        "h": 0.15,
        "w": 0.5,
        "x": 0.06,
        "y": 0.27
      },
      "kind": "paragraph",
      "text": "In line with their current emphasis on tactical benefits from generative AI, the vast majority of respondents were currently relying on off-the-shelf solutions. These included productivity applications with integrated generative AI (71%); enterprise platforms with integrated generative AI (61%); standard generative AI applications (68%); and publicly available large language models (LLMs) (56%), such as ChatGPT.",
      "attrs": null,
      "subkind": "paragraph",
      "toolName": null,
      "toolSlug": null,
      "confidence": null,
      "componentId": "26793f23-7732-4807-b9ba-2233e8256887",
      "frameworkName": null,
      "frameworkSlug": null
    },
    {
      "bbox": {
        "h": 0.12,
        "w": 0.5,
        "x": 0.06,
        "y": 0.56
      },
      "kind": "paragraph",
      "text": "Reliance on standard, off-the-shelf solutions is consistent with the current early phase of generative AI adoption, which is primarily focused on improving the efficiency and productivity of existing activities. However, as use cases for generative AI become more specialized, differentiated and strategic, the associated development approaches and technology infrastructure will likely follow suit.",
      "attrs": null,
      "subkind": "paragraph",
      "toolName": null,
      "toolSlug": null,
      "confidence": null,
      "componentId": "a4a46af8-f19b-4621-a558-c4aef38aebc8",
      "frameworkName": null,
      "frameworkSlug": null
    },
    {
      "bbox": {
        "h": 0.08,
        "w": 0.5,
        "x": 0.06,
        "y": 0.45
      },
      "kind": "paragraph",
      "text": "Relatively few reported using more narrowly focused and differentiated generative AI solutions, such as industry-specific software applications (23%), private LLMs (32%), and/or open-source LLMs (customized to their business) (25%).",
      "attrs": null,
      "subkind": "paragraph",
      "toolName": null,
      "toolSlug": null,
      "confidence": null,
      "componentId": "daaaa2fd-c17f-4c3c-ad53-f8037971d2c4",
      "frameworkName": null,
      "frameworkSlug": null
    },
    {
      "bbox": {
        "h": 0.08,
        "w": 0.5,
        "x": 0.06,
        "y": 0.15
      },
      "kind": "title",
      "text": "Most organizations are primarily relying on off-the-shelf generative AI solutions.",
      "attrs": null,
      "subkind": "headline",
      "toolName": null,
      "toolSlug": null,
      "confidence": null,
      "componentId": "4496db00-d9df-4bf4-9934-864ab1e77b68",
      "frameworkName": null,
      "frameworkSlug": null
    }
  ],
  "metrics": [
    {
      "metricRaw": "Adoption rate",
      "numberRaw": "71%",
      "numberKind": "percent",
      "actionTitle": "Most organizations are primarily relying on off-the-shelf generative AI solutions.",
      "calloutText": "In line with their current emphasis on tactical benefits from generative AI, the vast majority of respondents were currently relying on off-the-shelf solutions.",
      "numberScale": null,
      "numberValue": 71,
      "metricFamily": "share_penetration",
      "numberCurrency": null
    }
  ],
  "tools": [
    {
      "name": "Audience Persona",
      "slug": "audience-persona",
      "agent": "Storyteller",
      "layer": "slide",
      "matchId": "1027de73-d818-4554-9601-7d0776ee2bf0",
      "evidence": "In line with their current emphasis on tactical benefits from generative AI, the vast majority of respondents were currently relying on off-the-shelf solutions.",
      "confidence": 0.6
    }
  ],
  "frameworks": [],
  "arcBeats": [
    {
      "to": 20,
      "from": 13,
      "beatId": "1a670dc9-17c6-4a45-80e7-2c0b658fed5b",
      "arcName": "The Consultant's Gambit",
      "arcSlug": "consultants-gambit",
      "beatName": "Evidence & Proof",
      "beatSlug": "consultants-gambit-evidence-proof",
      "evidence": "Data tables, industry trends, and risk register",
      "position": 2,
      "confidence": 0.8,
      "parentBeatName": "Evidence",
      "parentBeatSlug": "evidence"
    }
  ],
  "loops": [
    {
      "to": 22,
      "from": 11,
      "name": "Cost Of Inaction",
      "slug": "27-cost-of-inaction",
      "bestFor": "Urgent budget requests, compliance, risk mitigation",
      "matchId": "8dd0f86a-2675-4c7a-b842-0728e098e8e2",
      "evidence": "Slides discussing current efforts, societal impacts, and leader concerns",
      "position": 0,
      "objective": "Highlighting the risks of not adopting generative AI",
      "structure": "The Status Quo -> The Hidden Costs Accumulating -> The Future State of Inaction -> The Tipping Point",
      "confidence": 0.6,
      "description": "Quantify what happens if the audience does nothing"
    },
    {
      "to": 20,
      "from": 14,
      "name": "Ladder Abstraction",
      "slug": "28-ladder-abstraction",
      "bestFor": "Training, thought leadership, making complex ideas accessible",
      "matchId": "a8072f27-eff0-49bb-9470-efca58d935fc",
      "evidence": "Slides on off-the-shelf solutions, talent, governance, and risk",
      "position": 1,
      "objective": "Showing the complexity of generative AI adoption",
      "structure": "The Concrete Example -> The Pattern It Represents -> The Universal Principle -> Back to Specific Application",
      "confidence": 0.6,
      "description": "Move between concrete examples and abstract principles to make ideas stick"
    }
  ],
  "imagePathAlt": null,
  "thumbSrc": null,
  "thumbSrcAlt": null,
  "locked": true
}