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Artificial intelligence adoption and workplace training

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  • Muehlemann, Samuel

Abstract

As artificial intelligence (AI) reshapes business processes, firms must adapt their training strategies to cultivate a skilled workforce. Using German establishment-level panel data from 2019 to 2023, this study analyzes how firms adjust their training strategies following AI adoption. Staggered difference-in-differences analysis shows that sustained AI adoption is associated with a 14% increase in new apprenticeships among training firms (intensive margin), but is not linked to the training decision (extensive margin). AI adoption is also associated with a modest increase in continuing training, with resources shifting toward high-skilled employees. The results align with AI as an automation innovation that reduces demand for simple skills as well as an augmentation innovation that increases demand for more advanced skills. The German dual apprenticeship system appears critical for firms aiming to build a future-ready workforce in the age of AI.

Suggested Citation

  • Muehlemann, Samuel, 2025. "Artificial intelligence adoption and workplace training," Journal of Economic Behavior & Organization, Elsevier, vol. 238(C).
    • Handle: RePEc:eee:jeborg:v:238:y:2025:i:c:s0167268125003257
    DOI: 10.1016/j.jebo.2025.107206
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    JEL classification:

    • J23 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Labor Demand
    • J24 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Human Capital; Skills; Occupational Choice; Labor Productivity
    • M53 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Personnel Economics - - - Training
    • 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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