Earticle

초록

영어

This study systematically examines how research on AI-enabled human resource management (AI-enabled HRM) has evolved in terms of its thematic structure within organizational contexts. To this end, we applied BERTopic-based topic modeling to 797 articles on AI-enabled HRM retrieved from the Web of Science database. The analysis identified 20 topics, among which five dominant themes— adoption and effects, efficiency and strategy, managers and professionals, ethics and collaboration, and recruitment—each accounted for more than 5% of the total corpus and collectively defined the core structure of the AI-enabled HRM literature. A synthesis of the topic distributions and their temporal patterns indicates that AI-enabled HRM research has progressed from an initial focus on technological adoption and efficiency toward greater attention to organizational use, managerial interpretation, domain-specific applications, and governance-related concerns. In particular, the results suggest that the effects of AI-enabled HRM do not arise automatically from technological capabilities alone. Rather, they are contingent upon organizational preparedness, the interpretive and decision-making roles of managers and professionals, the characteristics of application domains, and management practices that support accountability and trust. This study provides a data-driven thematic map of AI-enabled HRM research that integrates previously fragmented research streams into a coherent field-level overview. The synthesis suggests that academic discussions of AI-enabled HRM are shaped not only by technological potential but also by organizational and governance conditions. Future research should move beyond general claims of effectiveness by identifying conditions and evaluating which governance arrangements support trustworthy AI-enabled HRM across application domains and stakeholder groups, including employees.

목차

ABSTRACT
I. Introduction
II. Literature Review
2.1 Definition and Scope of AI-Enabled HRM
2.2 Research Streams in AI-Enabled HRM
III. Methodology
IV. Analysis Results
4.1 Keywords
4.2 Topics
4.3 Trends in Early AI-Enabled HRM Research
V. Discussion
VI. Conclusion
References

키워드

저자

• Jaehyun Lee [ Postdoctoral Researcher, Technology Management, Economics and Policy Program, Seoul National University ]
• Junmin Lee [ Assistant Professor, Department of Public Policy and Management, Pusan National University ] Corresponding Author

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  산업혁신연구 [The Journal of Industrial Innovation]

• 간기

  계간

• pISSN

  2005-2936

• eISSN

  2800-0080

• 수록기간

  1985~2026

• 등재여부

  KCI 등재

• 십진분류

  KDC 325 DDC 658