AI Insight
This study examined how employees' perception of AI replacement risk affects their withdrawal behaviors in the workplace. Using a two-part study design including scale development and a three-wave time-lagged survey, researchers found that perceived AI replacement risk increases withdrawal behavior through three mechanisms: decreased professional identity, reduced work meaningfulness, and heightened job insecurity. However, employees with higher technological self-efficacy showed weaker negative effects, suggesting that confidence in one's technological abilities serves as a protective factor.
Why it matters
These findings provide organizations with actionable insights for managing AI integration in the workplace. By identifying technological self-efficacy as a protective factor and understanding the identity-threat mechanisms at play, employers can develop targeted interventions such as skills training and meaningful work redesign to mitigate employee withdrawal and maintain workforce engagement during AI transitions.
Understand the Science
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.