AI-enabled HRM systems in business organizations: effects on workforce outcomes and the roles of trust and privacy

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Introduction The rapid expansion of artificial intelligence (AI) in human resource management has substantially reshaped how organizations attract, recruit, develop, evaluate, and retain their workforce. Research examining the combined employee-level effects of AI-enabled digital HRM (AI-DHRM)—through psychological mediating processes and under technology-related boundary conditions—remains sparse, particularly in emerging economies. Drawing on Social Exchange Theory, the Job Demands-Resources model, and UTAUT2, this study conceptualizes AI-DHRM as a reflective higher-order construct comprising four functionally distinct sub-dimensions, specifies a dual mediation model integrating an affective-relational pathway (person-organization [P-O] fit perception) and a motivational-agentic pathway (psychological empowerment), and identifies technology trust and privacy concern as critical boundary conditions. Methods A time-lagged, two-wave survey was administered to full-time employees of 61 AI-HRM-adopting organizations in Bangladesh, yielding 487 matched responses. AI-DHRM practices, mediators, moderators, and controls were measured at Time 1; all five outcomes were measured five weeks later at Time 2. Data were analyzed in IBM AMOS 26.0 using a two-stage structural equation modeling approach, with bias-corrected bootstrapped mediation ( n = 5,000 resamples), the index of moderated mediation, and Johnson-Neyman analysis. Results AI-DHRM practices exerted significant positive effects on job satisfaction (β = 0.41, 95% CI [0.29, 0.53]), work engagement (β = 0.38, 95% CI [0.26, 0.50]), job performance (β = 0.35, 95% CI [0.25, 0.45]), and employee wellbeing (β = 0.33, 95% CI [0.21, 0.45]), and significantly reduced turnover intention (β = −0.29, 95% CI [−0.41, −0.17]). Both P-O fit perception and psychological empowerment partially mediated these relationships across all five outcomes. Technology trust strengthened, and privacy concern attenuated—but did not reverse—the AI-DHRM-mediator pathways. Moderated mediation was confirmed across all ten conditional indirect effects. Discussion The findings establish AI-DHRM as an integrated system that employees experience as a coherent organizational investment, transmitted through two complementary psychological channels and conditional on trust and privacy perceptions. Organizations should design AI-HRM as a coherent bundle and treat trust-building and privacy-by-design as prerequisites to deployment. Findings rest on self-report data from a single country and warrant replication.

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