AI in demand: How expertise shapes its (early) impact on workers - Eduard Storm; Myrielle Gonschor; Marc Justin Schmidt (RWI - Leibniz-Institut für Wirtschaftsforschung, 2025)
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.
Keywords: D22; J23; J24; J31; O33; 330; AI; Online Job Vacancies; Skill Demand; Worker-level Analysis; Employment; Earnings; Expertise