Artificial intelligence adoption and workplace training

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. • AI adoption is associated with a 14% increase in new apprenticeships among training firms. • AI adoption is not significantly linked to the decision whether to offer apprenticeships. • AI adoption leads firms to shift continuing training resources toward higher-skilled employees over time. • Findings support AI’s dual role as both an automation and augmentation innovation regarding skills demand. • Germany’s dual apprenticeship system shows flexibility in adapting to AI-driven skill requirements.

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Publication Details

Journal
Journal of Economic Behavior & Organization
Published
2025-09-01
DOI
https://doi.org/10.1016/j.jebo.2025.107206
Citations
3
Primary Topic
Labor market dynamics and wage inequality
Type
article
Field-Weighted Citation Impact
9.39
Controls
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article

Artificial intelligence adoption and workplace training

Samuel Muehlemann
3 citations
Journal of Economic Behavior & Organization
Labor market dynamics and wage inequality
9.39
article

Artificial intelligence adoption and workplace training

Samuel Muehlemann
article en
3 citations

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. • AI adoption is associated with a 14% increase in new apprenticeships among training firms. • AI adoption is not significantly linked to the decision whether to offer apprenticeships. • AI adoption leads firms to shift continuing training resources toward higher-skilled employees over time. • Findings support AI’s dual role as both an automation and augmentation innovation regarding skills demand. • Germany’s dual apprenticeship system shows flexibility in adapting to AI-driven skill requirements.

Journal of Economic Behavior & OrganizationVol. 238
IZA - Institute of Labor Economics (DE), Maastricht School of Management (NL), LMU Klinikum (DE), Maastricht University (NL), Ludwig-Maximilians-Universität München (DE)
Openalex Percentile: Top 2%
Labor market dynamics and wage inequality
9.39
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