ARTIFICIAL INTELLIGENCE (AI) IN EMPLOYEE PERFORMANCE EVALUATION: A THEMATIC REVIEW

Abstract

The integration of Artificial Intelligence (AI) into employee performance assessment systems is becoming more common and the benefits such as enhanced objectivity, precision in analysis, and faster processing will be the case of comparison with the traditional appraisal methods. Even though the benefits of AI-driven evaluations have been highlighted by previous studies, the very concerns around fairness, transparency, and psychological trust are among the reasons leading to an uncritical adoption of AI. The current empirical and conceptual literature on AI-enabled employee performance evaluation is compiled through this thematic review which is aimed at identifying the dominant themes and the unresolved issues. The analytical accuracy and decision support, the ethical and fairness concerns, the adoption dynamics and organizational resistance, and the contextual variabilities across sectors are the four key themes that emerge from the review. The review critically states that AI-powered performance evaluation is a socio-technical system that disrupts power relations, accountability, and perceptions of organizational justice. Finally, the paper suggests enhancing theory and practice by outlining implications and pointing out future research in applied psychology and management.