This study aims to analyze the integration of Artificial Intelligence (AI) in the field of Human Resource Management (HRM) from 2004 to 2024. By measuring productivity, impact, collaboration and research topics, this research tracks the development of the domain. These findings may provide a foundation for future research on the growth of AI-focused HRM research, lead authors, institutions, and emerging themes. Using the Scopus database, 381 relevant documents were identified and analyzed, showing an increase in publications year on year, with significant growth between 2020 and 2023. This shows the transformative impact of AI on HRM. This analysis reveals rapid growth and international collaboration in AI-enabled HRM research, demonstrating significant potential. Future research could explore specific applications of AI, ethical considerations, and long-term impacts on HRM practices.

O. Ellegaard and J. A. Wallin, “The bibliometric analysis of scholarly production: How great is the impact?,” Scientometrics, vol. 105, no. 3, pp. 1809–1831, Dec. 2015, doi: 10.1007/S11192-015-1645-Z/TABLES/9.

R. Rousseau, L. Egghe, and R. Guns, Becoming Metric-Wise: A Bibliometric Guide for Researchers. Elsevier, 2018. doi: 10.1016/C2017-0-01828-1.

I. Passas, “Bibliometric Analysis: The Main Steps,” Encyclopedia 2024, Vol. 4, Pages 1014-1025, vol. 4, no. 2, pp. 1014–1025, Jun. 2024, doi: 10.3390/ENCYCLOPEDIA4020065.

R. Noble and D. Noble, “Artificial Intelligence,” Understanding Living Systems, pp. 99–112, Jun. 2023, doi: 10.1017/9781009277396.009.

Mehak, R. Kumar, and A. Mehta, “Artificial Intelligence,” International Journal of Advanced Research in Science, Communication and Technology (IJARSCT), vol. 3, no. 7, 2023, doi: 10.48175/IJARSCT-9466.

P. S and S. S, “A Study on Role of AI in Modern Recruitment -Opportunities and Challenges for HR Professional,” International Journal Of Scientific Research In Engineering & Technology, pp. 83–90, Mar. 2024, doi: 10.59256/IJSREAT.20240402011.

Z. K. S. Domas and R. Rakhmadi, “Peningkatan Performa Decision Tree dengan AdaBoost untuk Klasifikasi Kekurangtransparanan Informasi Anti-Korupsi,” Applied Information System and Management (AISM), vol. 5, no. 2, pp. 75–82, Sep. 2022, doi: 10.15408/AISM.V5I2.24887.

Z. Tasheva and V. Karpovich, “Transformation of Recruitment Process Through Implementation of AI Solutions,” Journal of Management and Economics, vol. 4, no. 02, pp. 12–17, Feb. 2024, doi: 10.55640/jme-04-02-03.

R. Kaur, “Artificial intelligence in human resource management: The next generation of technology for business excellence,” Embracing Business Sustainability Through Innovation and Creativity in the Service Sector, pp. 237–248, Mar. 2023, doi: 10.4018/978-1-6684-6732-9.ch015.

M. C. Catone, “The role of open data in digital society: The analysis of scientific trending topics through a bibliometric approach,” Frontiers in Sociology, vol. 8, pp. 1–10, Feb. 2023, doi: 10.3389/FSOC.2023.1134518/BIBTEX.

J. Dong, Y. Zhao, and L. Buckingham, “Charting the landscape of data-driven learning using a bibliometric analysis,” ReCALL, vol. 35, no. 3, pp. 339–355, Sep. 2023, doi: 10.1017/S0958344022000222.

Y. Jiang, W. Sun, Q. Ding, and X. Zhang, “Model of disruption management with actors in single machine scheduling,” Jixie Gongcheng Xuebao/Journal of Mechanical Engineering, vol. 49, no. 14, pp. 191–198, Jul. 2013, doi: 10.3901/JME.2013.14.191.

F. Marmier, D. Gourc, and F. Laarz, “A risk oriented model to assess strategic decisions in new product development projects,” Decis Support Syst, vol. 56, no. 1, pp. 74–82, Dec. 2013, doi: 10.1016/J.DSS.2013.05.002.

E. Kamar, Y. Gal, and B. J. Grosz, “Modeling information exchange opportunities for effective human-computer teamwork,” Artif Intell, vol. 195, pp. 528–550, 2013, doi: 10.1016/J.ARTINT.2012.11.007.

F. Ricca et al., “Team-building with answer set programming in the Gioia-Tauro seaport,” Theory and Practice of Logic Programming, vol. 12, no. 3, pp. 361–381, May 2012, doi: 10.1017/S147106841100007X.

H. Ruel and E. Njoku, “AI redefining the hospitality industry,” Journal of Tourism Futures, vol. 7, no. 1, pp. 53–66, 2020, doi: 10.1108/JTF-03-2020-0032.

N. Kshetri, “Evolving uses of artificial intelligence in human resource management in emerging economies in the global South: some preliminary evidence,” Management Research Review, vol. 44, no. 7, pp. 970–990, 2020, doi: 10.1108/MRR-03-2020-0168.

F. S. De Kock, F. Lievens, and M. Ph. Born, “The profile of the ‘Good Judge’ in HRM: A systematic review and agenda for future research,” Human Resource Management Review, vol. 30, no. 2, p. 100667, Jun. 2020, doi: 10.1016/j.hrmr.2018.09.003.

P. K. Jain, M. Jain, and R. Pamula, “Explaining and predicting employees’ attrition: a machine learning approach,” Springer Nature Applied Sciences, vol. 2, no. 4, Apr. 2020, doi: 10.1007/S42452-020-2519-4.

V. Graf, D. Teichmann, J. Horinka, and M. Dorda, “Dynamic Model for Scheduling Crew Shifts,” Math Probl Eng, vol. 2020, 2020, doi: 10.1155/2020/5372567.

N. Pourkhodabakhsh, M. M. Mamoudan, and A. Bozorgi-Amiri, “Effective machine learning, Meta-heuristic algorithms and multi-criteria decision making to minimizing human resource turnover,” Applied Intelligence, vol. 53, no. 12, pp. 16309–16331, Jun. 2023, doi: 10.1007/S10489-022-04294-6.

M. Rath, N. Mishra, and J. G. Jayasuria, “A Smart Human Resource Approach using Artificial Intelligence with Improved Employee Satisfaction for Better Sustainability in Organisation,” Evergreen, vol. 10, no. 4, pp. 2476–2482, Dec. 2023, doi: 10.5109/7162009.

D. E. Matytsin, V. A. Dzedik, G. A. Markeeva, and S. B. Boldyreva, “‘Smart’ outsourcing in support of the humanization of entrepreneurship in the artificial intelligence economy,” Humanit Soc Sci Commun, vol. 10, no. 1, p. 13, Jan. 2023, doi: 10.1057/s41599-022-01493-x.

Y. Suh, “Machine learning based customer churn prediction in home appliance rental business,” J Big Data, vol. 10, no. 1, p. 41, Apr. 2023, doi: 10.1186/s40537-023-00721-8.

E. B. Zavyalova, V. A. Volokhina, M. A. Troyanskaya, and Y. I. Dubova, “A humanistic model of corporate social responsibility in e-commerce with high-tech support in the artificial intelligence economy,” Humanit Soc Sci Commun, vol. 10, no. 1, Dec. 2023, doi: 10.1057/S41599-023-01764-1.

T. Jacob Fernandes França, H. São Mamede, J. M. Pereira Barroso, and V. M. Pereira Duarte dos Santos, “Artificial intelligence applied to potential assessment and talent identification in an organisational context,” Heliyon, vol. 9, no. 4, p. e14694, Apr. 2023, doi: 10.1016/j.heliyon.2023.e14694.

M. Zhang, S. Chen, X. Zhao, and Z. Yang, “Research on Construction Workers’ Activity Recognition Based on Smartphone,” Sensors, vol. 18, no. 8, p. 2667, Aug. 2018, doi: 10.3390/s18082667.

V. Prikshat, A. Malik, and P. Budhwar, “AI-augmented HRM: Antecedents, assimilation and multilevel consequences,” Human Resource Management Review, vol. 33, no. 1, p. 100860, Mar. 2023, doi: 10.1016/j.hrmr.2021.100860.