Perception of AI-induced occupational replacement risk and withdrawal behavior: an identity threat perspective in the workplace
- 1Faculty of Education, East China Normal University, Shanghai, China
Abstract
As artificial intelligence (AI) becomes increasingly integrated into the workplace, the risk that occupations will be replaced by AI has received widespread attention. Nevertheless, the underlying mechanisms linking AI-induced occupational replacement risk perception to individual withdrawal behaviors remain underexplored. Taking identity threat as an explanatory lens, this study integrates Identity Threat Theory (ITT) and Technology Threat Avoidance Theory (TTAT) to investigate the effect of occupational replacement risk perception on employee withdrawal behavior, with professional identity, work meaningfulness, and job insecurity serving as mediators and technological self-efficacy as a moderator. Two studies were conducted to test the theoretical model developed in this research. Study 1 developed and validated the AI-induced occupational replacement risk perception scale. Study 2 employed a three-wave time-lagged survey design to test the hypotheses. The results show that occupational replacement risk perception is positively associated with withdrawal behavior through decreased professional identity and work meaningfulness as well as increased job insecurity. Furthermore, these indirect effects are weaker among employees with higher technological self-efficacy. By illuminating the identity-threat mechanism that links AI-induced occupational replacement risk perception to employee behavior, this study opens the black box of how AI shapes employee responses, and it concludes with a discussion of the theoretical contributions and practical implications of these findings.
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BibTeX
@article{yang2026perception,
title = {{Perception of AI-induced occupational replacement risk and withdrawal behavior: an identity threat perspective in the workplace}},
author = {Hui Yang},
journal = {Frontiers in Psychology},
year = {2026},
month = oct,
doi = {10.3389/fpsyg.2026.1922666},
url = {https://doi.org/10.3389/fpsyg.2026.1922666},
note = {CC BY 4.0},
}
RIS
TY - JOUR
TI - Perception of AI-induced occupational replacement risk and withdrawal behavior: an identity threat perspective in the workplace
AU - Hui Yang
PY - 2026
DA - 2026/10/13
JO - Frontiers in Psychology
DO - 10.3389/fpsyg.2026.1922666
UR - https://doi.org/10.3389/fpsyg.2026.1922666
AB - As artificial intelligence (AI) becomes increasingly integrated into the workplace, the risk that occupations will be replaced by AI has received widespread attention. Nevertheless, the underlying mechanisms linking AI-induced occupational replacement risk perception to individual withdrawal behaviors remain underexplored. Taking identity threat as an explanatory lens, this study integrates Identity Threat Theory (ITT) and Technology Threat Avoidance Theory (TTAT) to investigate the effect of occupational replacement risk perception on employee withdrawal behavior, with professional identity, work meaningfulness, and job insecurity serving as mediators and technological self-efficacy as a moderator. Two studies were conducted to test the theoretical model developed in this research. Study 1 developed and validated the AI-induced occupational replacement risk perception scale. Study 2 employed a three-wave time-lagged survey design to test the hypotheses. The results show that occupational replacement risk perception is positively associated with withdrawal behavior through decreased professional identity and work meaningfulness as well as increased job insecurity. Furthermore, these indirect effects are weaker among employees with higher technological self-efficacy. By illuminating the identity-threat mechanism that links AI-induced occupational replacement risk perception to employee behavior, this study opens the black box of how AI shapes employee responses, and it concludes with a discussion of the theoretical contributions and practical implications of these findings.
SN - 1664-1078
ER -