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The Rapid Adoption of Generative AI

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Abstract

An analysis suggests that generative AI has been quickly and widely adopted at home and in the workplace, with about 40% of the U.S. population ages 18 to 64 using it to some degree.

Suggested Citation

  • Alexander Bick & Adam Blandin & David Deming, 2023. "The Rapid Adoption of Generative AI," On the Economy 98843, Federal Reserve Bank of St. Louis.
    • Handle: RePEc:fip:l00001:98843
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    File URL: https://www.stlouisfed.org/on-the-economy/2024/sep/rapid-adoption-generative-ai
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    References listed on IDEAS

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    1. David Autor, 2024. "Applying AI to Rebuild Middle Class Jobs," NBER Working Papers 32140, National Bureau of Economic Research, Inc.
    2. Daron Acemoglu & David Autor & Jonathon Hazell & Pascual Restrepo, 2022. "Artificial Intelligence and Jobs: Evidence from Online Vacancies," Journal of Labor Economics, University of Chicago Press, vol. 40(S1), pages 293-340.
    3. Alexander Bick & Adam Blandin, 2023. "Employer Reallocation During the COVID-19 Pandemic: Validation and Application of a Do-It-Yourself CPS," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 49, pages 58-76, July.
    4. Alexander Bick & Adam Blandin & Karel Mertens, 2023. "Work from Home before and after the COVID-19 Outbreak," American Economic Journal: Macroeconomics, American Economic Association, vol. 15(4), pages 1-39, October.
    5. David H. Autor & Frank Levy & Richard J. Murnane, 2003. "The skill content of recent technological change: an empirical exploration," Proceedings, Federal Reserve Bank of San Francisco, issue Nov.
    6. Paul Beaudry & Mark Doms & Ethan Lewis, 2010. "Should the Personal Computer Be Considered a Technological Revolution? Evidence from U.S. Metropolitan Areas," Journal of Political Economy, University of Chicago Press, vol. 118(5), pages 988-1036.
    7. Diego Comin & Martí Mestieri, 2018. "If Technology Has Arrived Everywhere, Why Has Income Diverged?," American Economic Journal: Macroeconomics, American Economic Association, vol. 10(3), pages 137-178, July.
    8. 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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    Citations

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    Cited by:

    1. Masayuki MORIKAWA, 2024. "Macroeconomic Impact of Artificial Intelligence on Productivity: An estimate from a survey," Discussion papers 24084, Research Institute of Economy, Trade and Industry (RIETI).
    2. Otis, Nicholas G. & Cranney, Katelyn & Delecourt, Solene & Koning, Rembrand, 2024. "Global Evidence on Gender Gaps and Generative AI," OSF Preprints h6a7c_v1, Center for Open Science.
    3. James Bono & Alec Xu, 2024. "Randomized Controlled Trials for Security Copilot for IT Administrators," Papers 2411.01067, arXiv.org, revised Nov 2024.
    4. Henry A. Thompson, 2024. "AI and the law," Papers 2412.05090, arXiv.org.
    5. Fabian Kosse & Tim Leffler & Arna Woemmel, 2024. "Digital Skills: Social Disparities and the Impact of Early Mentoring," CESifo Working Paper Series 11570, CESifo.

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    More about this item

    Keywords

    generative artificial intelligence (AI); labor productivity; technology adoption;
    All these keywords.

    JEL classification:

    • J24 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Human Capital; Skills; Occupational Choice; Labor Productivity
    • 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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