REINVITING HUMAN RESOURCE MANAGEMENT IN THE AGE OF ARTIFICIAL INTELLIGENCE
DOI:
https://doi.org/10.30997/jvs.v11i2.22285Keywords:
Artificial Intelligence, Bibliometric Analysis, Human Resource Management, Machine Learning, Systematic Literature Review.Abstract
This study conducts a systematic literature review and bibliometric analysis to map the intellectual structure and thematic evolution of Artificial Intelligence (AI) and Machine Learning (ML) in Human Resource Management (HRM), with a focus on sustainability implications in business. Using PRISMA 2020, 62 articles were selected from Scopus-indexed publications. Bibliometric analysis via VOS viewer reveals three dominant thematic clusters: technical foundations of AI/ML, HRM-oriented applications, and data-driven decision-support systems. Key findings identify India, China, Malaysia, and the United States as leading contributors, with strong South–South collaborations especially between India and Malaysia highlighting emerging innovation pathways in plural economies. The results demonstrate that AI–HRM synergy significantly enhances business sustainability by enabling data-driven strategic decisions, optimizing resource allocation, and supporting personalized and inclusive HR practices. However, ethical risks such as algorithmic bias pose challenges to sustainable implementation. The study recommends transparent AI governance, regular algorithmic audits, and Human-in-the-Loop (HITL) protocols to ensure that AI integration strengthens rather than undermines human-centric and sustainable HRM. These insights provide a foundation for policymakers and organizations pursuing responsible digital transformation in dynamic regions such as Southeast Asia.
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