When Decisions Are Delegated to Algorithms: A Concise Review of Employee Reactions to AI-Driven Human Resource Management

Abstract

However‚ while many aspects of HRM are delegated to AI and algorithmic systems (e․g․‚ CVscreening‚ performance evaluation‚ platform-based labor coordination)‚ much less is known about how workers and job-seekers make sense of and experience such systems․ This literature has been scattered across different areas and disciplines‚ with limited cross-over․ This review synthesizes research into employees' and job applicants' reactions to AI-enabled HRM across the HR value chain․ It draws on theories of organizational justice‚ technology acceptance and trust‚ algorithm dislike‚ the psychological contract‚ identity threat‚ and technostress to theorize the conditions under which reactions to AI-enabled HRM are positive or negative․ We present an overarching‚ multilevel framework integrating worker experience and perceptions‚ human-AI collaborations‚ and organization design (such as explainability and employee voice)․ Drawing on this framework‚ we highlight the contingent nature of responses‚ tensions within a young evidence base‚ and the need for theory-driven longitudinal research․