AI in Demand: How Expertise Shapes its (Early) Impact on Workers

Storm, Eduard; Gonschor, Myrielle and Schmidt, Marc Justin (November 2025) AI in Demand: How Expertise Shapes its (Early) Impact on Workers. IHS Working Paper Series 61, 46 p.

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Abstract

We study how artificial intelligence (AI) affects workers’ earnings and employment stability, combining German job vacancy data with administrative records from 2017–2023. Identification comes from changes in workers’ exposure to local AI skill demand over time, instrumented with national demand trends. We find no meaningful displacement or productivity effects on average, but notable skill heterogeneity: expert workers with deep domain knowledge gain while non-experts often lose, with returns shaped by occupational task structures. We also document AI-driven reinstatement effects toward analytic and interactive tasks that raise earnings. Overall, our results imply distributional concerns but also job-augmenting potential of early AI technologies.

Item Type: IHS Series
Additional Information (public): This paper uses confidential data from the Research Data Centre (FDZ) of the German Federal Employment Agency (BA) at the Institute for Employment Research (IAB) (project number fdz2436). Details on applying for the dataset and possibilities for data processing can be found on the FDZ homepage.
Keywords: AI, Online Job Vacancies, Skill Demand, Worker-level Analysis, Employment, Earnings, Expertise
Funders: DFG
Classification Codes (e.g. JEL): D22, J23, J24, J31, O33
Research Units: Skill Demand during Structural Change
Date Deposited: 18 Nov 2025 10:27
Last Modified: 20 Nov 2025 08:22
URI: https://irihs.ihs.ac.at/id/eprint/7345

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