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The Microstructure of AI Diffusion: Evidence From Firms, Business Functions, and Worker Tasks

Author

Listed:
  • Kathryn Bonney
  • Cory Breaux
  • Emin Dinlersoz
  • Lucia Foster
  • John Haltiwanger
  • Aditya Pande

Abstract

Using novel, nationally representative data from the 2026 AI supplement to the U.S. Census Bureau’s Business Trends and Outlook Survey (BTOS), we characterize AI diffusion across three interconnected layers: overall firm use, deployment across business functions, and worker-task use. This multi-layered approach provides a nuanced picture of business AI adoption. During the supplement reference period (Nov 2025-Jan 2026), 18% of firms used AI in a business function, rising to 32% on an employment-weighted basis; adoption is expected to reach 22% within six months. AI use is substantially higher in large firms and knowledge-intensive sectors, with use rates reaching 50%-60% (60%-70%, employment-weighted) for very large firms in the Information, Professional Services, and Finance sectors. Among adopting firms, the scope of use remains limited: 57% of users integrate AI in three or fewer business functions, most commonly Sales and Marketing (52%), Strategy and Business Development (45%), and IT (41%). In 23% (41%, employment-weighted) of firms, workers use AI in work-related tasks. Writing, document analysis, and information search are the leading Generative AI use in tasks, though 65% of firms limit use to three or fewer tasks. The evidence points to both top-down and bottom-up diffusion channels: worker task use sometimes occurs without formal firm-level adoption, and firm-level adoption sometimes occurs without worker task use. Most users (66%) rely on AI solely to augment tasks, while AI-related employment decreases are rare, occurring in only 2% of firms. Regression analysis shows a robust positive correlation between firm commercial performance and the breadth of AI integration, including functional deployment, task-level use, and operational investment. A distinct divergence emerges, however, with respect to labor outcomes. Functional breadth and operational investment are positively associated with employment decreases, whereas worker-task integration shows no significant link to headcount reduction once functional integration and operational investment are taken into account.

Suggested Citation

  • Kathryn Bonney & Cory Breaux & Emin Dinlersoz & Lucia Foster & John Haltiwanger & Aditya Pande, 2026. "The Microstructure of AI Diffusion: Evidence From Firms, Business Functions, and Worker Tasks," Working Papers 26-25, Center for Economic Studies, U.S. Census Bureau.
  • Handle: RePEc:cen:wpaper:26-25
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    File URL: https://www2.census.gov/library/working-papers/2026/adrm/ces/CES-WP-26-25.pdf
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    References listed on IDEAS

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    4. Kathryn Bonney & Cory Breaux & Cathy Buffington & Emin Dinlersoz & Lucia S. Foster & Nathan Goldschlag & John C. Haltiwanger & Zachary Kroff & Keith Savage, 2024. "Tracking Firm Use of AI in Real Time: A Snapshot from the Business Trends and Outlook Survey," NBER Working Papers 32319, National Bureau of Economic Research, Inc.
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