The interdisciplinary nature of AI and human resource management: A bibliometric analysis

Abstract

BACKGROUND: This study investigates the evolving relationship between artificial intelligence [AI] and human resource management [HRM] over the past two decades through a comprehensive analysis of 392 articles published between 2012 and 2023. OBJECTIVE: The study aims to provide a systematic understanding of this relationship by employing a rigorous three-stage methodology involving RStudio, VOSviewer, and Excel. METHODS: The methodology encompasses overall performance assessment, citation analysis, and network and content analysis to identify evolving research priorities, influential authors and publications, and underlying connections within the academic literature. RESULTS: The systematic approach reveals clusters of future research trends, including leveraging AI and big data for HRM advancements, enhancing employee engagement through machine learning, and investigating neural networks and procedural justice in HRM. IMPLICATIONS: This research agenda offers a roadmap for academics and HR professionals, identifying key areas for future exploration to ensure continued understanding of the dynamic interplay between AI and HRM.