THE POTENTIAL OF ARTIFICIAL INTELLIGENCE IN HUMAN RESOURCE MANAGEMENT

Loubna BOUHSAIEN; Abdellah AZMANI

doi:10.35784/acs-2024-34

THE POTENTIAL OF ARTIFICIAL INTELLIGENCE IN HUMAN RESOURCE MANAGEMENT

Article Sidebar

Open full text

PDF

Published: Sep 30, 2024

DOI: https://doi.org/10.35784/acs-2024-34

Main Article Content

DOI

https://doi.org/10.35784/acs-2024-34

Authors

Loubna BOUHSAIEN

loubna.bouhsaien@etu.uae.ac.ma

Abdelmalek Essaadi University

https://orcid.org/0009-0003-7216-6667

Abdellah AZMANI

a.azmani@uae.ac.ma

Abdelmalek Essaadi University

https://orcid.org/0000-0003-4975-3807

Abstract

The growth of Artificial Intelligence (AI) technologies is revolutionizing Human Resource (HR) practices, offering new opportunities for organizations to optimize their operations and better support for their workforce in an era defined by technological advancement. In this context, the emergence of industry 5.0 highlights human-centricity, resilience, and sustainability, promoting collaboration between humans and technology. This article conducts a bibliometric analysis to explore the intersection of AI and Human Resources Management (HRM), highlighting trends, research directions, and the evolving landscape of this thematic. Through performance analysis, social structure assessment, and thematic evolution examination, this study identifies key themes, emerging topics, and research trends. The findings underscore the transformative potential of AI in reshaping HRM and organizational dynamics, calling for more research and strategic applications of AI technologies to foster adaptive strategies and informed decision-making in the era of industry 5.0.

Keywords:

Artificial Intelligence, Bibliometric Analysis, Human Resources Management

References

Abdeldayem, M. M., & Aldulaimi, S. H. (2020). Trends and opportunities of Artificial Intelligence in human resource management: Aspirations for public sector in Bahrain. International Journal of Scientific & Technology Research, 9(01), 3867- 3871.

Alcalde-Bezhold, G., Alcázar-Arroyo, R., Angoso-de-Guzmán, M., Arenas, M. D., Arias-Guillén, M., Arribas-Cobo, P., Díaz-Gómez, J. M., García-Maset, R., González-Parra, E., Hernández-Marrero, D., Herrero-Calvo, J. A., Maduell, F., Molina, P., Molina-Núñez, M., Otero-González, A., Pascual, J., Pereira-García, M., Pérez-García, R., Dolores Del Pino Y Pino, M., … De Sequera-Ortiz, P. (2021). Hemodialysis centers guide 2020. Nefrología (English Edition), 41, 1-77. https://doi.org/10.1016/S2013-2514(22)00042-6 DOI: https://doi.org/10.1016/S2013-2514(22)00042-6

Baraibar-Diez, E., Luna, M., Odriozola, M. D., & Llorente, I. (2020). Mapping social impact: A bibliometric analysis. Sustainability, 12(22). 9389. https://doi.org/10.3390/su12229389 DOI: https://doi.org/10.3390/su12229389

Bondarouk, T., & Meijerink, J. (Eds.). (2024). Research handbook on human resource management and disruptive technologies. Edward Elgar Publishing. DOI: https://doi.org/10.4337/9781802209242

Bouhsaien, L. (2024, May 24). Database BA. https://drive.google.com/drive/folders/1sr6nQoMI0Tyy5VEuK1vcMELVpMhlqAzk

Bouhsaien, L., & Azmani, A. (2024). Burnout: A pervasive challenge threatening workplace well-being and organizational success. International Journal of Professional Business Review, 9(4), e04597. https://doi.org/10.26668/businessreview/2024.v9i4.4597 DOI: https://doi.org/10.26668/businessreview/2024.v9i4.4597

Budhwar, P., Malik, A., De Silva, M. T. T., & Thevisuthan, P. (2022). Artificial intelligence – challenges and opportunities for international HRM: A review and research agenda. The International Journal of Human Resource Management, 33(6), 1065–1097. https://doi.org/10.1080/09585192.2022.2035161 DOI: https://doi.org/10.1080/09585192.2022.2035161

Choudhury, P. (Raj), Foroughi, C., & Larson, B. (2021). Work‐from‐anywhere: The productivity effects of geographic flexibility. Strategic Management Journal, 42(4), 655–683. https://doi.org/10.1002/smj.3251 DOI: https://doi.org/10.1002/smj.3251

Chowdhury, S., Dey, P., Joel-Edgar, S., Bhattacharya, S., Rodriguez-Espindola, O., Abadie, A., & Truong, L. (2023). Unlocking the value of artificial intelligence in human resource management through AI capability framework. Human Resource Management Review, 33(1), 100899. https://doi.org/10.1016/j.hrmr.2022.100899 DOI: https://doi.org/10.1016/j.hrmr.2022.100899

Danvila-del-Valle, I., Estévez-Mendoza, C., & Lara, F. J. (2019). Human resources training: A bibliometric analysis. Journal of Business Research, 101, 627–636. https://doi.org/10.1016/j.jbusres.2019.02.026 DOI: https://doi.org/10.1016/j.jbusres.2019.02.026

Deepa, R., Sekar, S., Malik, A., Kumar, J., & Attri, R. (2024). Impact of AI-focussed technologies on social and technical competencies for HR managers – A systematic review and research agenda. Technological Forecasting and Social Change, 202, 123301. https://doi.org/10.1016/j.techfore.2024.123301 DOI: https://doi.org/10.1016/j.techfore.2024.123301

Derviş, H. (2020). Bibliometric analysis using Bibliometrix an R Package. Journal of Scientometric Research, 8(3), 156–160. https://doi.org/10.5530/jscires.8.3.32 DOI: https://doi.org/10.5530/jscires.8.3.32

Dixon, J., Hong, B., & Wu, L. (2021). The robot revolution: Managerial and employment consequences for firms. Management Science, 67(9), 5586–5605. https://doi.org/10.1287/mnsc.2020.3812 DOI: https://doi.org/10.1287/mnsc.2020.3812

Donthu, N., Kumar, S., Mukherjee, D., Pandey, N., & Lim, W. M. (2021). How to conduct a bibliometric analysis: An overview and guidelines. Journal of Business Research, 133, 285–296. https://doi.org/10.1016/j.jbusres.2021.04.070 DOI: https://doi.org/10.1016/j.jbusres.2021.04.070

Fernandes França, T. J., São Mamede, H., Pereira Barroso, J. M., & Pereira Duarte Dos Santos, V. M. (2023). Artificial intelligence applied to potential assessment and talent identification in an organisational context. Heliyon, 9(4), e14694. https://doi.org/10.1016/j.heliyon.2023.e14694 DOI: https://doi.org/10.1016/j.heliyon.2023.e14694

Foroudi, P., Akarsu, T. N., Marvi, R., & Balakrishnan, J. (2021). Intellectual evolution of social innovation: A bibliometric analysis and avenues for future research trends. Industrial Marketing Management, 93, 446–465. https://doi.org/10.1016/j.indmarman.2020.03.026 DOI: https://doi.org/10.1016/j.indmarman.2020.03.026

Fosso Wamba, S., Bawack, R. E., Guthrie, C., Queiroz, M. M., & Carillo, K. D. A. (2021). Are we preparing for a good AI society? A bibliometric review and research agenda. Technological Forecasting and Social Change, 164, 120482. https://doi.org/10.1016/j.techfore.2020.120482 DOI: https://doi.org/10.1016/j.techfore.2020.120482

Galán Hernández, J. J., Marín Díaz, G., & Galdón Salvador, J. L. (2024). Artificial Intelligence applied to human resources management: A bibliometric analysis. In Á. Rocha, C. Ferrás, J. Hochstetter Diez, & M. Diéguez Rebolledo (Eds.), Information Technology and Systems (Vol. 932, pp. 269–277). Springer Nature Switzerland. https://doi.org/10.1007/978-3-031-54235-0_25 DOI: https://doi.org/10.1007/978-3-031-54235-0_25

Garg, S., Sinha, S., Kar, A. K., & Mani, M. (2022). A review of machine learning applications in human resource management. International Journal of Productivity and Performance Management, 71(5), 1590–1610. https://doi.org/10.1108/IJPPM-08-2020-0427 DOI: https://doi.org/10.1108/IJPPM-08-2020-0427

Gong, X., De Pessemier, T., Martens, L., & Joseph, W. (2019). Energy- and labor-aware flexible job shop scheduling under dynamic electricity pricing: A many-objective optimization investigation. Journal of Cleaner Production, 209, 1078–1094. https://doi.org/10.1016/j.jclepro.2018.10.289 DOI: https://doi.org/10.1016/j.jclepro.2018.10.289

Guenole, N., & Feinzig, S. (2018). The business case for AI in HR. IBM Smarter Workforce Institute.

Jefroy, N., Azarian, M., & Yu, H. (2022). Moving from Industry 4.0 to Industry 5.0: What are the implications for smart logistics? Logistics, 6(2), 26. https://doi.org/10.3390/logistics6020026 DOI: https://doi.org/10.3390/logistics6020026

Kong, H., Yuan, Y., Baruch, Y., Bu, N., Jiang, X., & Wang, K. (2021). Influences of artificial intelligence (AI) awareness on career competency and job burnout. International Journal of Contemporary Hospitality Management, 33(2), 717–734. https://doi.org/10.1108/IJCHM-07-2020-0789 DOI: https://doi.org/10.1108/IJCHM-07-2020-0789

Laviola, F., Cucari, N., & Novic, H. (2024). Artificial intelligence in personal development from cradle to grave: A comprehensive review of HRD literature. Sinergie Italian Journal of Management, 42(1), 121–163. https://doi.org/10.7433/s123.2024.06 DOI: https://doi.org/10.7433/s123.2024.06

Moral-Muñoz, J. A., Herrera-Viedma, E., Santisteban-Espejo, A., & Cobo, M. J. (2020). Software tools for conducting bibliometric analysis in science: An up-to-date review. El Profesional de La Información, 29(1). https://doi.org/10.3145/epi.2020.ene.03 DOI: https://doi.org/10.3145/epi.2020.ene.03

Morgan, N., & Pritchard, A. (2019). Gender matters in hospitality. International Journal of Hospitality Management, 76, 38–44. https://doi.org/10.1016/j.ijhm.2018.06.008 DOI: https://doi.org/10.1016/j.ijhm.2018.06.008

Mumu, J. R., Tahmid, T., & Azad, Md. A. K. (2021). Job satisfaction and intention to quit: A bibliometric review of work-family conflict and research agenda. Applied Nursing Research, 59, 151334. https://doi.org/10.1016/j.apnr.2020.151334 DOI: https://doi.org/10.1016/j.apnr.2020.151334

Ortega-Cotto, N., Bhuyan, R., LaGrand, C., & Caldwell, C. (2022). Strategic human resource management – distinguishing between the urgent and the important. Business and Management Research, 12(1), 1. https://doi.org/10.5430/bmr.v12n1p1 DOI: https://doi.org/10.5430/bmr.v12n1p1

Palos-Sánchez, P. R., Baena-Luna, P., Badicu, A., & Infante-Moro, J. C. (2022). Artificial Intelligence and human resources management: A bibliometric analysis. Applied Artificial Intelligence, 36(1), 2145631. https://doi.org/10.1080/08839514.2022.2145631 DOI: https://doi.org/10.1080/08839514.2022.2145631

Pedraja-Rejas, L., Rodríguez-Ponce, E., & Muñoz-Fritis, C. (2022). Human resource management and performance in Ibero-America: Bibliometric analysis of scientific production. Cuadernos de Gestión, 22(2), 123–137. https://doi.org/10.5295/cdg.211569lp DOI: https://doi.org/10.5295/cdg.211569lp

Pejic-Bach, M., Bertoncel, T., Meško, M., & Krstić, Ž. (2020). Text mining of industry 4.0 job advertisements. International Journal of Information Management, 50, 416–431. https://doi.org/10.1016/j.ijinfomgt.2019.07.014 DOI: https://doi.org/10.1016/j.ijinfomgt.2019.07.014

Ryu, J., Seo, J., Jebelli, H., & Lee, S. (2019). Automated action recognition using an accelerometer-embedded wristband-type activity Tracker. Journal of Construction Engineering and Management, 145(1), 04018114. https://doi.org/10.1061/(ASCE)CO.1943-7862.0001579 DOI: https://doi.org/10.1061/(ASCE)CO.1943-7862.0001579

Tambe, P., Cappelli, P., & Yakubovich, V. (2019). Artificial Intelligence in human resources management: challenges and a path forward. California Management Review, 61(4), 15–42. https://doi.org/10.1177/0008125619867910 DOI: https://doi.org/10.1177/0008125619867910

Tong, S., Jia, N., Luo, X., & Fang, Z. (2021). The Janus face of Artificial Intelligence feedback: Deployment versus disclosure effects on employee performance. Strategic Management Journal, 42(9), 1600–1631. https://doi.org/10.1002/smj.3322 DOI: https://doi.org/10.1002/smj.3322

Torres-Salazar, E., Cruzado-Yesquén, K., Alvarez-Vasquez, H., Saavedra-Ruíz, J., Castañeda-Hipólito, M., Gastiaburú-Morales, S., Barandiarán-Gamarra, J., Vásquez-Coronado, M., & Alviz-Meza, A. (2024). A bibliometric study with statistical patterns of industry 4.0 on business management in the decade. Journal of Physics: Conference Series, 2726(1), 012009. https://doi.org/10.1088/1742-6596/2726/1/012009 DOI: https://doi.org/10.1088/1742-6596/2726/1/012009

Toumia, O., & Zouari, F. (2024). Artificial Intelligence and venture capital decision-making: In R. Sharma, K. Mehta, & P. Yu (Eds.), Advances in Business Strategy and Competitive Advantage (pp. 16–38). IGI Global. https://doi.org/10.4018/979-8-3693-1326-8.ch002 DOI: https://doi.org/10.4018/979-8-3693-1326-8.ch002

Vlačić, B., Corbo, L., Costa E Silva, S., & Dabić, M. (2021). The evolving role of Artificial Intelligence in marketing: A review and research agenda. Journal of Business Research, 128, 187–203. https://doi.org/10.1016/j.jbusres.2021.01.055 DOI: https://doi.org/10.1016/j.jbusres.2021.01.055

Vrontis, D., Christofi, M., Pereira, V., Tarba, S., Makrides, A., & Trichina, E. (2022). Artificial intelligence, robotics, advanced technologies and human resource management: A systematic review. The International Journal of Human Resource Management, 33(6), 1237–1266. https://doi.org/10.1080/09585192.2020.1871398 DOI: https://doi.org/10.1080/09585192.2020.1871398

Article Details

BOUHSAIEN, L., & AZMANI, A. (2024). THE POTENTIAL OF ARTIFICIAL INTELLIGENCE IN HUMAN RESOURCE MANAGEMENT. Applied Computer Science, 20(3), 153–170. https://doi.org/10.35784/acs-2024-34

ACM
ACS
APA
ABNT
Chicago
Harvard
IEEE
MLA
Turabian
Vancouver

Endnote/Zotero/Mendeley (RIS)
BibTeX

Abstract views: 781

License

This work is licensed under a Creative Commons Attribution 4.0 International License.

All articles published in Applied Computer Science are open-access and distributed under the terms of the Creative Commons Attribution 4.0 International License.