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How AI-Augmented Training Improves Worker Productivity

Author

Listed:
  • Fouarge, Didier

    (ROA, Maastricht University)

  • Fregin, Marie-Christine

    (Maastricht University)

  • Janssen, Simon

    (Institute for Employment Research (IAB), Nuremberg)

  • Levels, Mark

    (Maastricht University)

  • Montizaan, Raymond

    (ROA, Maastricht University)

  • Özgül, Pelin

    (Maastricht University)

  • Rounding, Nicholas

    (Maastricht University)

  • Stops, Michael

    (Institute for Employment Research (IAB), Nuremberg)

Abstract

We analyze the impact of AI-augmented training on worker productivity in a financial services company. The company introduced an AI tool that provides performance feedback on call center agents to guide their training. To estimate causal effects, we exploit the staggered roll out of the AI-tool. The AI-augmented training reduces call handling time by 10 percent. We find larger effects for short-tenured workers because they spend less time putting clients on hold. But the AI-augmented training also improves communication style with relatively stronger effects for long-tenured agents, and we find slightly positive effects on customer satisfaction.

Suggested Citation

  • Fouarge, Didier & Fregin, Marie-Christine & Janssen, Simon & Levels, Mark & Montizaan, Raymond & Özgül, Pelin & Rounding, Nicholas & Stops, Michael, 2025. "How AI-Augmented Training Improves Worker Productivity," IZA Discussion Papers 18224, Institute of Labor Economics (IZA).
    • Handle: RePEc:iza:izadps:dp18224
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    References listed on IDEAS

    as
    1. Espinosa, Miguel & Stanton, Christopher T., 2022. "Training, Communications Patterns, and Spillovers Inside Organizations," CEPR Discussion Papers 17460, C.E.P.R. Discussion Papers.
    2. David H. Autor & Frank Levy & Richard J. Murnane, 2003. "The Skill Content of Recent Technological Change: An Empirical Exploration," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 118(4), pages 1279-1333.
    3. Jan Sauermann, 2023. "Performance measures and worker productivity," IZA World of Labor, Institute of Labor Economics (IZA), pages 260-260, April.
    4. Eleanor Wiske Dillon & Sonia Jaffe & Nicole Immorlica & Christopher T. Stanton, 2025. "Shifting Work Patterns with Generative AI," Papers 2504.11436, arXiv.org, revised Nov 2025.
    5. Nikhil Agarwal & Alex Moehring & Pranav Rajpurkar & Tobias Salz, 2023. "Combining Human Expertise with Artificial Intelligence: Experimental Evidence from Radiology," NBER Working Papers 31422, National Bureau of Economic Research, Inc.
    6. 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.
    Full references (including those not matched with items on IDEAS)

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    Keywords

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    JEL classification:

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