Understanding AI Anxiety in the Workplace: A Multimethod Investigation Using Fear Acquisition Theory and the Technology Acceptance Model
As artificial intelligence (AI) rapidly diffuses and concerns about job displacement intensify, the psychological mechanisms underlying AI job replacement anxiety remain insufficiently understood. Drawing on Integrated Fear Acquisition Theory and the Technology Acceptance Model, the present research investigates whether AI job replacement anxiety can be elicited through vicarious exposure to narratives emphasizing AI-over-human control, and whether perceived usefulness and perceived ease of use of AI moderate this response. Across two studies, we examine AI job replacement anxiety as a response that emerges through vicarious exposure to narratives emphasizing AI agency and human control loss, rather than through direct personal experience of job displacement. Study 1 employed a randomized experiment (N = 316), demonstrating that such exposure increased AI job replacement anxiety. This effect was moderated by perceived usefulness of AI, but not by perceived ease of use, and remained robust after controlling for core self-evaluations. Study 2 (N = 995) replicated the association between perceived AI-over-human control and job replacement anxiety in an observational design and provided convergent evidence for the moderating role of perceived usefulness, supporting the external validity of the findings. Together, the results provide the first causal evidence that perceptual and vicarious processes can trigger AI job replacement anxiety. By shifting attention from structural labor-market conditions to how AI agency is perceived and communicated, this work offers a mechanism-based account of when and why AI-related job fears arise.