All's well that begins just: organizational justice as precursor of trust in AI-enabled HRM

Abstract

Purpose The integration of AI in HRM practices is increasing and will be inevitable in the coming years. The successful implementation of AI-enabled management in organizations requires stakeholders' trust. This systematic literature review identifies factors influencing trust in AI-enabled HRM systems and their consequences across three stages of AI implementation (ex-ante, in-ante, and post-ante). Design/methodology/approach This study reviews and synthesizes the past literature on AI in HRM to develop a conceptual model. Findings This study identifies the factors that enable organizational justice while implementing AI-enabled HRMS. We explain the positive relationship between organizational justice and employees' trust and moderators of this relationship. Further, this study suggests positive and unintended implications (for employees, teams, and organizations) of trust in AI-enabled HRMS. Originality/value This paper contributes theoretically to the organizational justice framework by expanding it to the domain of AI-enabled HRMS. This paper examines the gap in understanding trust in AI-enabled HRMS across the adoption process of AI in organizations. We also suggest future research directions. The study also outlines practical and societal implications for the responsible implementation of AI-enabled HRMS and identifies directions for future research.

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