Mapping the Research Landscape of Artificial Intelligence in Human Resource Management: A Bibliometric Analysis

Abstract

Artificial intelligence (AI) is increasingly integrated into human resource management (HRM) functions as organizations accelerate their digital transformation. However, comprehensive studies mapping the intellectual development, thematic evolution, and emerging directions of AI-HRM research remain limited. This study aims to examine the growth, research trends, and future directions of AI applications in HRM through bibliometric analysis. A quantitative bibliometric approach was employed using literature retrieved from the Scopus database based on predefined search terms and screening criteria. Bibliometric performance and thematic analyses were conducted using Biblioshiny within the bibliometrix package, while bibliometric networks were visualized using VOSviewer. The analysis identified 856 publications indexed between 1991 and 2027 across 358 publication sources, involving 2,452 authors and an international collaboration rate of 33.18%. The field has experienced substantial growth, particularly since 2019. Keyword analysis identified artificial intelligence, human resource management, and machine learning as the dominant research themes, while thematic evolution revealed a shift toward increasingly specialized topics, including generative AI, large language models, and digital transformation. These findings demonstrate that AI-HRM research is evolving in parallel with technological advances and the expanding integration of AI into HRM practices. This study contributes a comprehensive mapping of the field’s intellectual and thematic development and provides a foundation for researchers to identify emerging topics, underexplored areas, and future research opportunities in AI-enabled HRM.