Loso Judijanto

Artificial Intelligence in HRM: A Scientometric Review of Global Publications

Introduction

Artificial intelligence in hrm: a scientometric review of global publications. Explore a scientometric review of global research on Artificial Intelligence in Human Resource Management (HRM). Discover key themes, collaborations, and emerging trends.

Abstract

The integration of Artificial Intelligence (AI) into Human Resource Management (HRM) has triggered a significant transformation in how organizations attract, manage, and retain talent. This study aims to map the intellectual structure, thematic trends, and collaborative patterns of global research on AI in HRM using a scientometric approach. Drawing data from the Scopus database and utilizing VOSviewer software, the analysis covers co-authorship networks, institutional collaborations, keyword co-occurrences, temporal trends, and density distributions. The results reveal that core themes revolve around AI-enabled decision-making, employee engagement, job satisfaction, and performance enhancement, while strategic topics such as innovation, technology adoption, and sustainable development are gaining momentum. India, the United States, and Malaysia emerge as leading contributors, highlighting strong regional clusters and international partnerships. This study provides actionable insights for practitioners, outlines theoretical pathways for scholars, and identifies emerging areas that merit further investigation. It serves as a foundational reference for understanding the evolving intersection between AI technologies and HRM practices in the digital age.

Review

This scientometric review offers a timely and comprehensive analysis of the global research landscape concerning Artificial Intelligence (AI) in Human Resource Management (HRM). By leveraging data from the Scopus database and employing VOSviewer software, the study meticulously maps the intellectual structure, thematic evolution, and collaborative networks within this rapidly expanding interdisciplinary field. The chosen methodology, encompassing co-authorship analysis, keyword co-occurrence, and temporal trends, provides a robust framework for understanding the academic trajectory and current state of AI-HRM research. This foundational work addresses a critical gap in synthesizing the fragmented knowledge base, making it highly relevant to both academics and practitioners navigating the digital transformation of HR. The study's findings illuminate several crucial aspects of the AI-HRM discourse. It successfully identifies core research themes such as AI-enabled decision-making, employee engagement, job satisfaction, and performance enhancement, while also signaling the growing importance of strategic topics like innovation, technology adoption, and sustainable development. The revelation of leading contributing countries—India, the United States, and Malaysia—underscores the emergence of significant regional research clusters and the dynamics of international collaboration. These insights not only provide a clear snapshot of current scholarly priorities but also offer valuable guidance for researchers seeking to identify promising avenues for future inquiry and for practitioners looking to understand the empirically supported applications and challenges of AI in their HR strategies. While the review provides an excellent overview, its reliance solely on the Scopus database, though extensive, might subtly bias the findings towards journals indexed there, potentially overlooking significant contributions from other reputable databases or regional publications not fully represented. Future iterations could explore the qualitative aspects of the identified themes in greater depth or delve into the methodologies predominant within these themes to provide a more nuanced understanding of research approaches. Nevertheless, this scientometric review stands as a highly valuable contribution, serving as an indispensable baseline for scholars and practitioners alike. It effectively outlines theoretical pathways, offers actionable insights, and critically identifies emerging research frontiers, solidifying its role as a pivotal reference in the ongoing dialogue concerning the evolving intersection of AI and HRM.

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