AI Adoption, Employee Well-being and Job Performance
The Mediating Role of Well-being and the Moderating Role of AI Anxiety
DOI:
https://doi.org/10.68379/sbzf3x83Keywords:
artificial intelligence adoption; employee well-being; job performance; AI anxiety; job demands–resources theory; conservation of resources theory; moderated mediationAbstract
Drawing on job demands–resources (JD-R) and conservation of resources (COR) theories, this study tested whether employee well-being mediates the association between artificial intelligence (AI) adoption and job performance and whether AI anxiety moderates the first stage. A three-wave, time-lagged study paired employee reports with supervisor-rated job performance (N = 400 complete matched cases). Regression, bootstrapped conditional indirect effects, confirmatory factor analysis and robustness checks were applied. The retained five-factor model fit well (CFI = .992, RMSEA = .017, SRMR = .033); however, the proposed four dimensions of AI anxiety were not empirically separable in this sample. Well-being was positively associated with subsequent job performance (b = 0.24, p < .001). AI adoption did not show a statistically significant adjusted association with well-being at mean anxiety (b = 0.03, p = .50), and neither the conditional indirect effect (95% CI [−0.014, 0.027]) nor the AI adoption × AI anxiety interaction (b = −0.04, p = .12) was statistically significant. AI adoption had a positive direct association with job performance (b = 0.23, p < .001), while AI anxiety was negatively associated with both well-being and job performance. An exploratory inverted-U pattern varied across specifications. The findings do not support the proposed mediation or moderation, but suggest that technology use, anxiety and well-being warrant separate attention. The observational design does not establish causal effects.
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