Artificial Intelligence Anxiety and Employee Performance: A Systematic Literature Review of Job Insecurity, Threat–Challenge Appraisal, Coping, Career Resilience, and Organisational Buffers

Abstract

This systematic literature review examines the relationship between artificial intelligence (AI) anxiety and employee performance, with particular attention to job insecurity, threat–challenge appraisal, coping, career resilience, job crafting, leadership, training, organisational support, and human–AI collaboration. The review synthesises publicly accessible scholarly evidence and a supplied research corpus using multiple conceptual search strategies and backward and forward citation searching. The evidence is organised around two complementary pathways. The first is a threat pathway, in which AI-related concerns about job replacement, skill obsolescence, loss of autonomy, and employment continuity may contribute to anxiety, job insecurity, emotional exhaustion, withdrawal, and weaker performance-related outcomes. The second is an opportunity pathway, in which AI is appraised as a manageable challenge and can support learning, job crafting, adaptation, engagement, and performance when appropriate personal and organisational resources are available. The review integrates Cognitive Appraisal Theory, Conservation of Resources Theory, and Job Demands–Resources theory to explain why employee responses to AI differ across contexts. It identifies career resilience, AI self-efficacy, learning ability, training, supportive leadership, organisational support, employee participation, transparency, and human-centred AI governance as important potential buffers. A qualitative thematic synthesis is used because the included studies differ substantially in constructs, occupational settings, countries, research designs, and outcome measures. The review does not claim exhaustive coverage of proprietary bibliographic databases such as Scopus or Web of Science. No new human-participant data were collected. This work is released as a research preprint for open scholarly dissemination and future updating as additional database records become available.