Artificial intelligence in human resource management: A review of applications, algorithms, and ethical challenges

Digital transformation of organizations has enhanced the adoption of Artificial Intelligence in Human Resource Management, which poses both opportunities and threats associated with algorithmic decision-making, ethical AI and workforce analytics. Although machine learning, natural language processing and predictive analytics are increasingly used in HR functions, the literature is still distributed in bits on how they are applied, algorithms, and ethical considerations. To fill this gap, the paper involves a systematic literature review guided by PRISMA on AI-HRM, automation in recruitment, talent analytics, and responsible AI. This paper investigate how smart HR systems, deep learning models, and HR analytics platforms are changing the field of recruitment, performance management, employee experience, and workforce planning. Emerging issues that include algorithmic bias, explainable AI, data privacy, and AI governance are also assessed in the review, which are growing in their effects on organizational adoption. The results show that AI use can improve efficiency, accuracy, and strategic HR decision-making, specifically, predictive analytics, talent intelligence, and digital HR transformation, yet presents the risk associated with transparency, fairness, and accountability. The review shows a revision of the HR technologies oriented on automation to human-AI collaboration, ethical AI systems, and responsible innovation, which body of HR work is changing its role in future of work. The research provides the study as a contribution to the literature by incorporating technological, managerial, and ethical viewpoints in a single AI-HRM research framework, which offers future researchers guidelines to improve the future of workforce analytics, AI governance, and sustainable digital transformation.