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