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

Kathryn Bonney, Cory L. Breaux, Emin Dinlersoz, Lucia Foster, John Haltiwanger and Aditya A. Pande

No 35141, NBER Working Papers from National Bureau of Economic Research, Inc

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 layers: firm-wide adoption, business-function deployment, and worker-task use. During Nov 2025–Jan 2026, 18% of firms used AI in at least one function (32%, employment-weighted), with adoption expected to reach 22% within six months. Use is concentrated in large firms and knowledge-intensive sectors, reaching 50%–60% (60%–70%, employment-weighted) among very large firms in Information, Professional Services, and Finance. Among adopters, scope remains limited: 57% use AI in three or fewer functions, most often Sales and Marketing (52%), Strategy (45%), and IT (41%). Worker-level use appears in 23% (41%, employment-weighted) of firms, primarily for writing, document analysis, and information search; 65% restrict use to three or fewer tasks. Evidence suggests both top-down and bottom-up diffusion: worker use can occur without firm adoption, and vice versa. Most firms (66%) use AI for task augmentation, while employment reductions are rare (2%). Regression results show a positive relationship between firm performance and AI integration breadth. However, functional deployment and operational investment are associated with employment declines, while worker-task use is not once these factors are controlled for.

JEL-codes: L23 O33 (search for similar items in EconPapers)
Date: 2026-04
Note: EFG PR
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