Artificial Intelligence in Human Resource Management: Global Research Landscape, Collaboration Networks, and Emerging Themes

Abstract

This study presents a comprehensive bibliometric analysis of research on Artificial Intelligence in Human Resource Management (AI–HRM) published between 2015 and 2025. Using data retrieved from the Scopus database and analyzed through VOSviewer (version 1.6.20), the study identifies publication trends, key contributors, collaboration networks, and thematic clusters shaping the field. A total of 160 peer-reviewed journal articles were analyzed to visualize co-authorship, citation patterns, and keyword co-occurrence networks. Results indicate an exponential growth of AI–HRM research after 2020, reflecting the increasing integration of intelligent technologies in workforce management. Four dominant research themes emerged: AI-driven recruitment, HR analytics, employee well-being, and ethical governance. The findings highlight a paradigm shift from efficiency-focused applications toward human-centered and ethically aligned AI practices. This study provides an updated intellectual map of AI–HRM research, offering scholars and practitioners a foundation for future inquiry and strategic development.