Algorithmic justice in AI-driven human resource management: Implications for workplace well-being and affective commitment

Human resource functions are increasingly mediated, and sometimes directly governed, by algorithmic systems, yet little is known about how employees’ fairness perceptions of these systems relate to their workplace well-being and affective commitment. Drawing on organizational justice and social exchange theories and survey data from 307 employees in the Australian financial and insurance sector, we establish algorithmic human resource management (AHRM) justice as a multidimensional construct comprising distributive, procedural, interpersonal, and informational justice. We argue that AHRM does not simply place these dimensions in a new context but reconfigures the social exchange conditions under which justice perceptions form. AHRM justice was positively associated with workplace well-being and, both directly and indirectly through well-being, with affective commitment; informational justice emerged as particularly salient. Self-perceived AI understanding did not moderate these relationships. The findings extend the ensemble view of algorithmic HRM and support a human-centric approach to AI-driven people management.