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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
  • Catherine Buffington
  • Emin Dinlersoz
  • Lucia Foster
  • Nathan Goldschlag
  • John 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. 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 & Catherine Buffington & Emin Dinlersoz & Lucia Foster & Nathan Goldschlag & John Haltiwanger & Zachary Kroff & Keith Savage, 2024. "Tracking Firm Use of AI in Real Time: A Snapshot from the Business Trends and Outlook Survey," Working Papers 24-16, Center for Economic Studies, U.S. Census Bureau.
    • Handle: RePEc:cen:wpaper:24-16
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    File URL: https://www2.census.gov/library/working-papers/2024/adrm/ces/CES-WP-24-16.pdf
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    References listed on IDEAS

    as
    1. Daron Acemoglu & Gary Anderson & David Beede & Catherine Buffington & Eric Childress & Emin Dinlersoz & Lucia Foster & Nathan Goldschlag & John Haltiwanger & Zachary Kroff & Pascual Restrepo & Nikolas, 2023. "Advanced Technology Adoption: Selection or Causal Effects?," AEA Papers and Proceedings, American Economic Association, vol. 113, pages 210-214, May.
    2. Tyna Eloundou & Sam Manning & Pamela Mishkin & Daniel Rock, 2023. "GPTs are GPTs: An Early Look at the Labor Market Impact Potential of Large Language Models," Papers 2303.10130, arXiv.org, revised Aug 2023.
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    Cited by:

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    2. Thomas Licht & Klaus Wohlrabe, 2024. "AI Adoption Among German Firms," CESifo Working Paper Series 11459, CESifo.
    3. Alexander Bick & Adam Blandin & David Deming, 2023. "The Rapid Adoption of Generative AI," On the Economy 98843, Federal Reserve Bank of St. Louis.

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    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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