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AI-Driven Revolution in Human Resource Management: A Bibliometric Analysis of Its Integration and Transformative Impact

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  • Zhu, Liuxi
  • Shen, Lei

Abstract

Purpose: This study explores the integration of Artificial Intelligence (AI) in Human Resource Management (HRM) and its impact on organizational structures, labor relations, and management practices, providing insights and recommendations for organizations undergoing digital transformation. Design/Methodology/Approach: Utilizing HistCite and CiteSpace analytical platforms, this study conducts systematic bibliographic assessment and scientometric investigation to examine the current state of AI in HRM, with particular emphasis on its evolution from theoretical discussions to practical applications. Findings: The study finds that AI is increasingly integrated into HRM functions like recruitment, performance monitoring, and employee experience enhancement. It also highlights the cognitive and behavioral effects of AI adoption, including employee substitution, integration, and collaboration, concurrently exerting a substantial influence on workforce productivity and institutional effectiveness. Originality: This study offers an extensive analysis of the utilization of AI within HRM and identifies emerging research trends and areas for further exploration. Practical Implications: The findings offer actionable insights for organizations adopting AI in HRM, emphasizing AI's potential to streamline functions, improve employee experience, and address challenges such as employee attitudes and job displacement.

Suggested Citation

  • Zhu, Liuxi & Shen, Lei, 2025. "AI-Driven Revolution in Human Resource Management: A Bibliometric Analysis of Its Integration and Transformative Impact," GBP Proceedings Series, Scientific Open Access Publishing, vol. 13, pages 14-32.
    • Handle: RePEc:axf:gbppsa:v:13:y:2025:i::p:14-32
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