Ethical Challenges and Algorithmic Bias in AI Implementation in HRM

Abstract

This article explores the ethical challenges and algorithmic biases that emerge from the implementation of artificial intelligence (AI) in human resource management (HRM). Through a systematic literature review of recent studies, the analysis reveals that while AI can significantly improve recruitment efficiency, workforce analytics, and strategic HR functions, it also introduces substantial risks, including bias in decision-making, lack of transparency, and ethical concerns around privacy and employee well-being. The findings highlight that algorithmic bias is not only a technical issue but also a reflection of broader social and organizational dynamics, which if left unaddressed can reinforce workplace inequalities. Furthermore, the discussion emphasizes that effective governance, transparency mechanisms, and a human-centered approach are crucial for balancing technological innovation with fairness and inclusivity. Ultimately, the study concludes that responsible AI adoption in HRM requires embedding ethical principles into every stage of design and deployment to ensure that efficiency gains do not come at the expense of employee trust, dignity, and organizational sustainability.