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Tracking Firm Use of AI in Real Time: A Snapshot from the Business Trends and Outlook Survey

Author

Listed:
  • Kathryn Bonney
  • Cory Breaux
  • Cathy Buffington
  • Emin Dinlersoz
  • Lucia S. Foster
  • Nathan Goldschlag
  • John C. Haltiwanger
  • Zachary Kroff
  • Keith Savage

Abstract

Timely and accurate measurement of AI use by firms is both challenging and crucial for understanding the impacts of AI on the U.S. economy. We provide new, real-time estimates of current and expected future use of AI for business purposes based on the Business Trends and Outlook Survey for September 2023 to February 2024. During this period, bi-weekly estimates of AI use rate rose from 3.7% to 5.4%, with an expected rate of about 6.6% by early Fall 2024. The fraction of workers at businesses that use AI is higher, especially for large businesses and in the Information sector. AI use is higher in large firms but the relationship between AI use and firm size is non-monotonic. In contrast, AI use is higher in young firms although, on an employment-weighted basis, is U-shaped in firm age. Common uses of AI include marketing automation, virtual agents, and data/text analytics. AI users often utilize AI to substitute for worker tasks and equipment/software, but few report reductions in employment due to AI use. Many firms undergo organizational changes to accommodate AI, particularly by training staff, developing new workflows, and purchasing cloud services/storage. AI users also exhibit better overall performance and higher incidence of employment expansion compared to other businesses. The most common reason for non-adoption is the inapplicability of AI to the business.

Suggested Citation

  • 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.
    • Handle: RePEc:nbr:nberwo:32319
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    Cited by:

    1. Zara Contractor & Germ'an Reyes, 2025. "Generative AI in Higher Education: Evidence from an Elite College," Papers 2508.00717, arXiv.org.
    2. Fabian Kosse & Tim Leffler & Arna Woemmel, 2025. "Digital Skills: Social Disparities and the Impact of Early Mentoring," SOEPpapers on Multidisciplinary Panel Data Research 1222, DIW Berlin, The German Socio-Economic Panel (SOEP).
    3. Alexander Bick & Adam Blandin & David Deming, 2023. "The Rapid Adoption of Generative AI," On the Economy 98843, Federal Reserve Bank of St. Louis.
    4. Lorenzo Bencivelli & Sara Formai & Elena Mattevi & Tullia Padellini, 2025. "Embracing the digital transition: the adoption of cloud computing and AI by Italian firms," Questioni di Economia e Finanza (Occasional Papers) 946, Bank of Italy, Economic Research and International Relations Area.
    5. Lu Fang & Zhe Yuan & Kaifu Zhang & Dante Donati & Miklos Sarvary, 2025. "Generative AI and Firm Productivity: Field Experiments in Online Retail," Papers 2510.12049, arXiv.org, revised Feb 2026.
    6. Bonney, Kathryn & Breaux, Cory & Buffington, Catherine & Dinlersoz, Emin & Foster, Lucia & Goldschlag, Nathan & Haltiwanger, John & Kroff, Zachary & Savage, Keith, 2024. "The impact of AI on the workforce: Tasks versus jobs?," Economics Letters, Elsevier, vol. 244(C).
    7. Benjamin G. Hyman & Benjamin Lahey & Karen Ni & Laura Pilossoph, 2025. "How Retrainable are AI-Exposed Workers?," NBER Working Papers 34174, National Bureau of Economic Research, Inc.
    8. Yoshiki Ando & Emin Dinlersoz & Jeremy Greenwood & Ruben Piazzesi, 2025. "Technifying Ventures," NBER Working Papers 33993, National Bureau of Economic Research, Inc.
    9. Contractor, Zara & Reyes, Germán, 2025. "Generative AI in Higher Education: Evidence from an Elite College," IZA Discussion Papers 18055, Institute of Labor Economics (IZA).
    10. Eleanor W. Dillon & Sonia Jaffe & Nicole Immorlica & Christopher T. Stanton, 2025. "Shifting Work Patterns with Generative AI," NBER Working Papers 33795, National Bureau of Economic Research, Inc.
    11. Anthony R. Harding & Juan Moreno-Cruz, 2024. "Watts and Bots: The Energy Implications of AI Adoption," CESifo Working Paper Series 11360, CESifo.
    12. Thomas Licht & Klaus Wohlrabe, 2024. "AI Adoption Among German Firms," CESifo Working Paper Series 11459, CESifo.
    13. Lu Fang & Zhe Yuan & Kaifu Zhang & Dante Donati & Miklos Sarvary, 2025. "Generative AI and Firm Productivity: Field Experiments in Online Retail," CESifo Working Paper Series 12201, CESifo.
    14. Aldasoro, Iñaki & Gambacorta, Leonardo & Pal, Rozalia & Revoltella, Debora & Weiss, Christoph & Wolski, Marcin, 2026. "AI adoption, productivity and employment: Evidence from European firms," EIB Working Papers 2026-02, European Investment Bank (EIB).
    15. Fabian Kosse & Tim Leffler & Arna Woemmel, 2024. "Digital Skills: Social Disparities and the Impact of Early Mentoring," CESifo Working Paper Series 11570, CESifo.
    16. Jaccoud, Florencia, 2025. "Robots & AI Exposure and Wage Inequality," MERIT Working Papers 2025-013, United Nations University - Maastricht Economic and Social Research Institute on Innovation and Technology (MERIT).

    More about this item

    JEL classification:

    • L23 - Industrial Organization - - Firm Objectives, Organization, and Behavior - - - Organization of Production
    • O31 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Innovation and Invention: Processes and Incentives
    • O33 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Technological Change: Choices and Consequences; Diffusion Processes

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