Beyond AI Adoption: Performance expectancy, status loss, and identity threat at work

Workplace artificial intelligence (AI) implementation is often evaluated through adoption and use, yet behavioural engagement may not capture whether employees experience AI as threatening to their professional identity. Integrating the Unified Theory of Acceptance and Use of Technology with identity-threat theory, this study examines whether AI performance expectancy, a core driver of technology adoption, is also associated with AI identity threat, and whether this association operates through perceived loss of status position. Survey data from 202 employed adults across multiple sectors, including both AI users and non-users, were analysed using structural equation modelling with latent variables. AI performance expectancy was positively associated with AI use and negatively associated with AI identity threat. This negative association was both direct and indirect through lower perceived loss of status position; a serial pathway through AI use and status loss was also significant. AI use was associated with lower perceived status loss but was not directly associated with lower AI identity threat. Organisational AI training was associated with higher performance expectancy and AI use, but not with status-loss or identity-threat appraisals. These findings suggest that performance expectancy may carry identity-relevant meaning beyond its conventional role as a utilitarian adoption belief. They also indicate that managing AI identity threat may require attention to how employees interpret AI’s implications for professional status and contribution, not only whether they use AI or receive training. Given the cross-sectional design, results should be interpreted as patterns of association rather than causal effects.