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Salesforce press release, “Salesforce Announces Einstein GPT, the World’s First Generative AI for CRM”, 7 March 2023.\n8. Workday press release, “Workday Announces Fiscal 2024 Third Quarter Financial Results”, 28 November 2023.\n9. FST Media, “Westpac Buddies Up Engineers with Gen AI Partner”, 11 August 2023.\n10. Accenture, Pulse of Change Survey, 2024.\n11. Accenture, Reinvention by the Numbers, 18 January 2024.\n12. Accenture case study, “Banking on BBVA’s bold new future”, 2023.\n13. Accenture, Pulse of Change Survey, 2023.", "attrs": null, "canon": { "kind": { "name": "List", "slug": "list", "status": "active", "canonId": "019de52c-f94b-779b-a53b-fd4904a5f4d2", "version": 1, "description": "Bullet or numbered list." }, "tool": null, "subkind": { "name": "Numbered list", "slug": "numbered", "status": "active", "canonId": "019de52c-fcc0-7718-a284-a4250c805df2", "version": 1, "description": null }, "framework": null }, "subkind": "numbered", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:49:25.728+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "c1f865bb-d3ab-4944-9667-8161792e0551", "parentComponentId": null }, { "bbox": { "h": 0.6, "w": 0.35, "x": 0.05, "y": 0.18 }, "kind": "list", "text": "1. Accenture Research analysis and estimates on BLS and O*Net data as of December 2022.\n2. Accenture, “Work, Workforce, Workers: Reinvented in the age of generative AI”, 16 January 2024.\n3. Accenture Research analysis and estimates on BLS and O*Net data as of December 2022.\n4. Avanade, “Banks Focus on Efficiency with AI”, 2024.\n5. Microsoft Blog, “Introducing Microsoft 365 Copilot – your copilot for work”, 16 March 2023.\n6. Adobe press release, “Adobe Unveils Firefly, a Family of New Creative Generative AI”, 21 March 2023.", "attrs": null, "canon": { "kind": { "name": "List", "slug": "list", "status": "active", "canonId": "019de52c-f94b-779b-a53b-fd4904a5f4d2", "version": 1, "description": "Bullet or numbered list." }, "tool": null, "subkind": { "name": "Numbered list", "slug": "numbered", "status": "active", "canonId": "019de52c-fcc0-7718-a284-a4250c805df2", "version": 1, "description": null }, "framework": null }, "subkind": "numbered", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:49:25.728+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "ef835ab9-a28a-4c03-9193-c5f2ce25089f", "parentComponentId": null }, { "bbox": { "h": 0.05, "w": 0.15, "x": 0.05, "y": 0.08 }, "kind": "title", "text": "References", "attrs": null, "canon": { "kind": { "name": "Title", "slug": "title", "status": 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"model": "claude-code-default", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "019dd951-9f64-72ba-b40e-d1a45fe109d3", "parentComponentId": null }, { "bbox": null, "kind": "metric", "text": "banking employees analyzed: 2.7 million", "attrs": null, "canon": { "kind": { "name": "Metric", "slug": "metric", "status": "active", "canonId": "019de52c-f923-73bf-8081-d0b1a8c5264d", "version": 1, "description": "Big-number or KPI value." }, "tool": { "name": "Quantification", "slug": "quantification", "status": "active", "bestFor": null, "canonId": "019dd9e1-47ab-72ce-a079-aab1f5299e88", "version": 1, "bodyDocId": null, "description": "Translating a claim into numbers, charts, or tables.", "familyLabel": null }, "subkind": null, "framework": null }, "subkind": "primary", "groupRole": null, "confidence": null, "extraction": { "at": "2026-04-23 22:54:00+00", "model": "claude-code-default", "runId": null, "seconds": null, "promptVersion": null }, "componentId": 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We started by identifying which of the granular tasks require intensive use of language. Then, we assessed in which way the task requires the use of interpersonal or cognitive skills to be resolved. This enabled us to understand whether generative AI could automate a task or augment the employee's skills.", "attrs": null, "canon": { "kind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "5f2affc0-941d-4d07-959d-4bfc1930cea4", "version": 1, "description": "Single prose block in the body of a slide." }, "tool": null, "subkind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "019de52c-fb80-75af-aa5c-a7a4bfac2433", "version": 1, "description": null }, "framework": null }, "subkind": "paragraph", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:49:26.873+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "219013f3-0c3a-4794-a2a7-e8511d4f30ef", "parentComponentId": null }, { "bbox": { "h": 0.35, "w": 0.28, "x": 0.36, "y": 0.15 }, "kind": "paragraph", "text": "We tagged each task and the time employees spend in performing it into one of four categories: High potential for automation, high potential for augmentation, low potential, or no language tasks. We analyzed data for 2.7 million banking employees in the US as well as the 170 roles and 3,500 tasks they perform. 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We used data from the US Bureau of Labor Statistics and the Occupational Information Network to analyze descriptions of 900 occupations across industries in the US, the 19,000 tasks they perform, and the time employees spend on each of those. This allowed us to understand the likely impact of generative AI on labor productivity.", "attrs": null, "canon": { "kind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "5f2affc0-941d-4d07-959d-4bfc1930cea4", "version": 1, "description": "Single prose block in the body of a slide." }, "tool": null, "subkind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "019de52c-fb80-75af-aa5c-a7a4bfac2433", "version": 1, "description": null }, "framework": null }, "subkind": "paragraph", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:49:26.873+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "5c6a1869-628e-4f72-9629-966037ffec44", "parentComponentId": null }, { "bbox": { "h": 0.35, "w": 0.28, "x": 0.67, "y": 0.52 }, "kind": "paragraph", "text": "Our assessment of generative AI's impact on banking staff expenses was based on an analysis of over 200 language-related tasks, using data from the Bureau of Labor statistics. We linked these tasks to various banking roles and evaluated the potential for task automation and augmentation in different occupational categories, leading to insights on possible productivity gains across diverse roles in the banking sector.", "attrs": null, "canon": { "kind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "5f2affc0-941d-4d07-959d-4bfc1930cea4", "version": 1, "description": "Single prose block in the body of a slide." }, "tool": null, "subkind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "019de52c-fb80-75af-aa5c-a7a4bfac2433", "version": 1, "description": null }, "framework": null }, "subkind": "paragraph", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:49:26.873+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "7c40177a-ffd6-4421-9dbf-d2d211d2acaa", "parentComponentId": null }, { "bbox": { "h": 0.35, "w": 0.28, "x": 0.36, "y": 0.52 }, "kind": "paragraph", "text": "Assessing generative AI's impact on banking financials\nTo explore the influence of generative AI in the banking sector, we conducted a comprehensive analysis using financial data from 150 of the largest banks worldwide. This data, sourced from S&P Capital IQ, spanned a 12-month period ending September 2023.", "attrs": null, "canon": { "kind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "5f2affc0-941d-4d07-959d-4bfc1930cea4", "version": 1, "description": "Single prose block in the body of a slide." }, "tool": null, "subkind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "019de52c-fb80-75af-aa5c-a7a4bfac2433", "version": 1, "description": null }, "framework": null }, "subkind": "paragraph", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:49:26.873+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "88d53c3d-9b17-4992-92fa-25ec580a278b", "parentComponentId": null }, { "bbox": { "h": 0.35, "w": 0.28, "x": 0.67, "y": 0.15 }, "kind": "paragraph", "text": "The estimation of generative AI's effects on revenue generation was informed by insights gleaned from expert consultations and relevant case studies. 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