AI Governance: Implications and Research Directions for Organization and Human Resource Management

Abstract

This study examines the theoretical and empirical challenges that AI governance poses for the fields of organization studies and human resource management (HRM) and proposes directions for future research. As AI technologies rapidly diffuse across organizations, AI governance has emerged as a critical managerial concern rather than a peripheral technical issue. Despite its growing importance, systematic engagement with AI governance remains limited in organization and HRM research, with prior work concentrated primarily in engineering, computer science, law, public policy, and management information systems. To identify areas where organization and HRM scholars can make distinctive academic contributions, we conducted a large-scale meta-analysis of approximately 6,000 academic articles on AI governance using the BERTopic topic modeling approach. The analysis reveals that AI governance research has expanded sharply since 2022 and has diversified across disciplinary boundaries, reflecting increasing societal, organizational, and regulatory attention. Building on these findings, this study identifies six research themes through which organization and HRM scholarship can advance the AI governance literature: (1) positioning AI governance within the evolution of organizational theory; (2) examining the relationship between AI governance and organizational performance; (3) analyzing the diffusion of AI governance through institutional isomorphism; (4) investigating decoupling between formal AI governance structures and actual organizational practices; (5) exploring processes through which AI governance is reconfigured within organizations; and (6) clarifying its relationship with high-performance work systems.