Mapping Artificial Intelligence Trends and Challenges in Human Resource Management Practice: A Bibliometric Analysis Of Recent Literature

Research Aims: This research aims to map the evolving trends and challenges in the application of Artificial Intelligence (AI) to human resource management (HRM) practices through a bibliometric analysis approach with current literature, hoping to provide a comprehensive understanding of the current landscape and its implications for academics and practitioners. Design/methodology/approach: The method used in this study is a bibliometric approach by analyzing scientific articles from databases such as Scopus and Web of Science. The data analysis technique was then processed and visualized using VOSviewer software to identify patterns and thematic relationships between research topics. Research Findings: The results show that the application of AI in HR management has a significant impact on key HR functions such as HR analytics, recruitment processes, and strategic decision-making, but on the other hand also faces challenges such as algorithm bias, data privacy, ethics, technology adoption barriers, and the limitations of comprehensive bibliometric analysis to address these issues holistically. Theoretical Contribution/Originality: This study makes a theoretical contribution through a comprehensive map of AI trends and challenges in HR management, enriching the literature with insights into the dynamics of the technology and its implications for HR management theory. The study also proposes a conceptual framework to address the ethical and practical challenges of AI implementation in organizations. Keywords: Artificial Intelligence, Human Resource Management, Bibliometric Analysis, HR Analytics, Machine Learning, Ethics