How AI-Augmented Training Improves Worker Productivity

Didier Fouarge (), Marie-Christine Fregin (), Simon Janssen, Mark Levels (), Raymond Montizaan (), Pelin Özgül (), Nicholas Rounding () and Michael Stops ()
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Didier Fouarge: ROA, Maastricht University
Marie-Christine Fregin: Maastricht University
Mark Levels: Maastricht University
Raymond Montizaan: ROA, Maastricht University
Pelin Özgül: Maastricht University
Nicholas Rounding: Maastricht University
Michael Stops: Institute for Employment Research (IAB), Nuremberg

No 18224, IZA Discussion Papers from Institute of Labor Economics (IZA)

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.

Keywords: performance feedback; training; artificial intelligence; employee productivity (search for similar items in EconPapers)
JEL-codes: J24 O31 O33 (search for similar items in EconPapers)
Date: 2025-10
New Economics Papers: this item is included in nep-ain, nep-bec, nep-eff, nep-hrm and nep-lma
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