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The Sum of All (Workplace) Fears: How Managers Mediate the Fear of AI Job Displacement

Christos Makridis and Christos A. Makridis

No 12678, CESifo Working Paper Series from CESifo

Abstract: AI is transforming work, but workers’ responses to these technologies depend not only on exposure to AI, but also on how organizations, especially managers, oversee the transition. Using longitudinal data from the Gallup Workforce Panel from 2023-2026, I examine whether managers and workplace practices shape employees’ fears that AI will eliminate their jobs. Across survey waves, roughly 3-4 percent of workers say their job is very likely to be eliminated within five years because of new technology, automation, robots, or artificial intelligence, while about 14-19 percent say it is somewhat or very likely. Concern is substantially higher among frequent AI users. Stronger workplace practices are associated with lower displacement fear: a one-standard-deviation increase in workplace quality is associated with 13-24 percent lower odds of reporting greater displacement risk, and workers reporting the highest level of organizational wellbeing support are 6-6.8 percentage points less likely to say their job is somewhat or very likely to be displaced in cross-sectional specifications. Frequent AI use is positively associated with perceived displacement risk, with estimates ranging from about 3-12.9 percentage points across the main specifications and reaching 6 percentage points in the most saturated respect model. However, this association is weaker in higher-quality workplace environments: among workers reporting the highest level of organizational wellbeing support, the frequent-AI-use premium is reduced by up to 9.0 percentage points. In short, managers play a central role in shaping how workers interpret AI adoption.

Keywords: artificial intelligence; job displacement; managers; workplace practices; worker expectations; technological change; organizational capital (search for similar items in EconPapers)
JEL-codes: D23 J24 J28 M12 O33 (search for similar items in EconPapers)
Date: 2026
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