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Generative AI at Work

Author

Listed:
  • Brynjolfsson, Erik

    (Stanford U)

  • Li, Danielle

    (MIT)

  • Raymond, Lindsey R.

    (MIT)

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

  • Brynjolfsson, Erik & Li, Danielle & Raymond, Lindsey R., 2023. "Generative AI at Work," Research Papers 4141, Stanford University, Graduate School of Business.
    • Handle: RePEc:ecl:stabus:4141
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    File URL: https://www.gsb.stanford.edu/faculty-research/working-papers/generative-ai-work
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    Citations

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    Cited by:

    1. 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.
    2. Gary Charness & Brian Jabarian & John A. List, 2023. "Generation Next: Experimentation with AI," NBER Working Papers 31679, National Bureau of Economic Research, Inc.
    3. 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.
    4. 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.
    5. Freund, L. B., 2022. "Superstar Teams: The Micro Origins and Macro Implications of Coworker Complementarities," Janeway Institute Working Papers 2235, Faculty of Economics, University of Cambridge.

    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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