THE ALGORITHMIC AUDITOR: A FRAMEWORK FOR HR TO GOVERN AI IN TALENT MANAGEMENT SYSTEMS

Abstract

This study examines the growing integration of artificial intelligence (AI) in human resource (HR) management and its implications for governance, ethics, and organizational accountability. As HR functions increasingly rely on data-driven systems for recruitment, performance evaluation, and employee retention, new challenges emerge related to algorithmic bias, transparency, and decision-making responsibility. Using a narrative review approach, this article synthesizes existing literature on AI adoption in HR, highlighting key risks and the limitations of current oversight mechanisms. The findings indicate that while AI enhances efficiency and predictive capabilities, it also introduces ethical concerns that traditional HR frameworks are not equipped to address. In response, the study explores the emergence of the algorithmic auditor role as a critical function in ensuring fairness and accountability in AI systems. The article proposes the need for a comprehensive governance framework that integrates ethical principles, interdisciplinary collaboration, and continuous monitoring. Ultimately, this research contributes to the development of responsible AI practices in HR by emphasizing the importance of balancing technological advancement with human-centered values.