Trust, empowerment, and anxiety in the GenAI-enabled workplace: How generative AI in human resource management shapes employee outcomes in an emerging economy

Generative AI (GenAI) is rapidly entering the human resource management (HRM) function, yet how employees psychologically respond to GenAI-enabled HR practices remains poorly understood, especially in emerging economies. Drawing on the Ability-Motivation-Opportunity framework and the Job Demands-Resources model, this study tested a moderated sequential mediation model in which trust in AI and psychological empowerment jointly transmit the effects of GenAI-enabled HRM practices on work engagement, employee wellbeing, job performance, and turnover intention. Algorithmic transparency was theorized to strengthen, and AI anxiety to weaken, the trust-building stage. Using a time-lagged, two-wave survey of 400 employees in medium and large Thai organizations and partial least squares structural equation modeling, all nine hypotheses were supported. Trust in AI and psychological empowerment fully mediated the four outcomes, and the two moderators operated on the same practices-to-trust path, with transparency amplifying and anxiety attenuating it. This single-path, dual-moderator design shows that the same managerial lever can yield markedly different trust returns depending on how transparently GenAI is implemented and how anxious employees feel. The findings position trust and empowerment as the human-centered mechanisms through which workplace GenAI generates value, and extend human-computer interaction research on trust in AI to the GenAI-enabled workplace in an under-represented emerging economy. Conditional indirect effects and the index of moderated mediation confirm that the strength of the sequential pathway itself rises with transparency and falls with AI anxiety. Because the two mediators and the four outcomes were reported in the same survey wave, the estimated pathways are interpreted as associations consistent with the theorised sequence rather than as causal effects.