A COMPREHENSIVE LITERATURE REVIEW OF THE BARRIERS AND FACILITATORS OF ARTIFICIAL INTELLIGENCE ADOPTION IN HUMAN RESOURCE MANAGEMENT: AN EXAMINATION OF ADMINISTRATIVE AND TECHNICAL CONSIDERATIONS

Artificial Intelligence (AI) refers to systems designed to perform tasks requiring human-like intelligence, such as learning, reasoning, decision-making, and language processing. Its integration into Human Resource Management (HRM) has gained significant attention for enhancing efficiency, accuracy, and strategic capabilities. This study defines AI, explores its HRM applications, identifies implementation barriers, and provides evidence-based recommendations. A comprehensive literature review was conducted using recent peer-reviewed articles, academic publications, and industry reports. Findings reveal AI's transformative impact on key HR functions: recruitment (e.g., automated screening), training and development (personalized learning), performance management (objective evaluations), employee engagement (sentiment analysis), and predictive analytics (turnover forecasting). However, challenges include resistance to change, ethical concerns (bias, fairness), limited digital skills, inadequate infrastructure, poor data quality, privacy issues, and high costs. To overcome these, organizations should invest in infrastructure, build HR professionals' AI competencies, establish ethical governance frameworks, and adopt phased, pilot-based implementations. Strategic, responsible AI adoption can significantly boost HR effectiveness, organizational performance, and employee satisfaction