AI-enabled HRM systems in business organizations: effects on workforce outcomes and the roles of trust and privacy
TL;DR
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.
Abstract
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.
