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Generative AI at Work

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  • Erik Brynjolfsson
  • Danielle Li
  • Lindsey R. Raymond

Abstract

New AI tools have the potential to change the way workers perform and learn, but little is known about their impacts on the job. In this paper, we study the staggered introduction of a generative AI-based conversational assistant using data from 5,179 customer support agents. Access to the tool increases productivity, as measured by issues resolved per hour, by 14% on average, including a 34% improvement for novice and low-skilled workers but with minimal impact on experienced and highly skilled workers. We provide suggestive evidence that the AI model disseminates the best practices of more able workers and helps newer workers move down the experience curve. In addition, we find that AI assistance improves customer sentiment, increases employee retention, and may lead to worker learning. Our results suggest that access to generative AI can increase productivity, with large heterogeneity in effects across workers.

Suggested Citation

  • Erik Brynjolfsson & Danielle Li & Lindsey R. Raymond, 2023. "Generative AI at Work," NBER Working Papers 31161, National Bureau of Economic Research, Inc.
    • Handle: RePEc:nbr:nberwo:31161
    Note: CF IO LE LS PR
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    1. Clément de Chaisemartin & Xavier D'Haultfœuille, 2020. "Two-Way Fixed Effects Estimators with Heterogeneous Treatment Effects," American Economic Review, American Economic Association, vol. 110(9), pages 2964-2996, September.
    2. Taniguchi, Hiroya & Yamada, Ken, 2022. "ICT capital–skill complementarity and wage inequality: Evidence from OECD countries," Labour Economics, Elsevier, vol. 76(C).
    3. Chad Syverson, 2011. "What Determines Productivity?," Journal of Economic Literature, American Economic Association, vol. 49(2), pages 326-365, June.
    4. 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.
    5. Ann Bartel & Casey Ichniowski & Kathryn Shaw, 2007. "How Does Information Technology Affect Productivity? Plant-Level Comparisons of Product Innovation, Process Improvement, and Worker Skills," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 122(4), pages 1721-1758.
    6. George P. Baker & Thomas N. Hubbard, 2003. "Make Versus Buy in Trucking: Asset Ownership, Job Design, and Information," American Economic Review, American Economic Association, vol. 93(3), pages 551-572, June.
    7. Luis Garicano, 2000. "Hierarchies and the Organization of Knowledge in Production," Journal of Political Economy, University of Chicago Press, vol. 108(5), pages 874-904, October.
    8. Timothy F. Bresnahan & Erik Brynjolfsson & Lorin M. Hitt, 2002. "Information Technology, Workplace Organization, and the Demand for Skilled Labor: Firm-Level Evidence," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 117(1), pages 339-376.
    9. Goodman-Bacon, Andrew, 2021. "Difference-in-differences with variation in treatment timing," Journal of Econometrics, Elsevier, vol. 225(2), pages 254-277.
    10. 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.
    11. Sun, Liyang & Abraham, Sarah, 2021. "Estimating dynamic treatment effects in event studies with heterogeneous treatment effects," Journal of Econometrics, Elsevier, vol. 225(2), pages 175-199.
    12. Guy Michaels & Ashwini Natraj & John Van Reenen, 2014. "Has ICT Polarized Skill Demand? Evidence from Eleven Countries over Twenty-Five Years," The Review of Economics and Statistics, MIT Press, vol. 96(1), pages 60-77, March.
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    Cited by:

    1. Carvajal, Daniel & Franco, Catalina & Isaksson, Siri, 2024. "Will Artificial Intelligence Get in the Way of Achieving Gender Equality?," Discussion Paper Series in Economics 3/2024, Norwegian School of Economics, Department of Economics.
    2. Elias Bouacida & Renaud Foucart & Maya Jalloul, 2024. "Decreasing Differences in Expert Advice," Working Papers 408394204, Lancaster University Management School, Economics Department.
    3. Gary Charness & Brian Jabarian & John List, 2023. "Generation Next: Experimentation with AI," Artefactual Field Experiments 00777, The Field Experiments Website.
    4. Freund, L. B., 2022. "Superstar Teams: The Micro Origins and Macro Implications of Coworker Complementarities," Cambridge Working Papers in Economics 2276, Faculty of Economics, University of Cambridge.
    5. Morgan Blangeois, 2023. "Generative AI: Revolution or Threat for Digital Service Companies ? [IA générative : révolution ou menace pour les entreprises de services du numérique ?]," Post-Print hal-04355219, HAL.
    6. Qin Chen & Jinfeng Ge & Huaqing Xie & Xingcheng Xu & Yanqing Yang, 2023. "Large Language Models at Work in China's Labor Market," Papers 2308.08776, arXiv.org.
    7. Alexander Cuntz & Carsten Fink & Hansueli Stamm, 2024. "Artificial Intelligence and Intellectual Property : An Economic Perspective," WIPO Economic Research Working Papers 77, World Intellectual Property Organization - Economics and Statistics Division.
    8. Daniel Goller & Christian Gschwendt & Stefan C. Wolter, 2023. ""This time it's different" Generative Artificial Intelligence and Occupational Choice," Economics of Education Working Paper Series 0209, University of Zurich, Department of Business Administration (IBW).
    9. Anil R. Doshi & Oliver P. Hauser, 2023. "Generative artificial intelligence enhances creativity but reduces the diversity of novel content," Papers 2312.00506, arXiv.org, revised Mar 2024.
    10. Walkowiak, Emmanuelle, 2023. "Task-interdependencies between Generative AI and Workers," Economics Letters, Elsevier, vol. 231(C).

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    More about this item

    JEL classification:

    • D8 - Microeconomics - - Information, Knowledge, and Uncertainty
    • J24 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Human Capital; Skills; Occupational Choice; Labor Productivity
    • M15 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Business Administration - - - IT Management
    • M51 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Personnel Economics - - - Firm Employment Decisions; Promotions
    • 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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