From AI-driven HRM to engaged employees: the critical role of perceived organizational justice

Abstract

Purpose This study investigates how artificial intelligence (AI) shapes employees’ workplace experiences. Specifically, it examines the direct effect of AI-driven human resource management (AI-HRM) on employee engagement (EE) and further explores its indirect effect through perceived organizational justice (POJ). Design/methodology/approach A quantitative, cross-sectional design was employed in this study. Data were collected from banking sector employees who use AI-enabled HRM applications. Using a snowball sampling method, 374 valid responses were obtained. Structural equation modeling (SEM) was conducted to examine the proposed direct and mediating relationships. Findings The findings reveal that AI-HRM practices have a significant positive impact on EE and POJ. Furthermore, POJ partially mediates the relationship between AI-HRM and job engagement, highlighting the role of justice perceptions in shaping employees’ responses to AI-supported HRM systems. Practical implications The results provide actionable insights for senior managers, HR professionals and artificial intelligence system developers in the banking sector. Effective implementation of AI-HRM can enhance employee engagement, promote AI readiness, improve performance outcomes and support continuous skill development. Originality/value This study extends social exchange theory, sociotechnical systems theory and organizational justice theory within the context of artificial intelligence. It demonstrates how AI-driven HRM practices influence employee engagement through fairness perceptions, integrates technological systems into social exchange mechanisms and conceptualizes AI-HRM as a sociotechnical structure that shapes employee attitudes and behaviors.

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