THE POTENTIAL OF ARTIFICIAL INTELLIGENCE IN HUMAN RESOURCE MANAGEMENT
Loubna BOUHSAIEN
loubna.bouhsaien@etu.uae.ac.maAbdelmalek Essaadi University (Morocco)
https://orcid.org/0009-0003-7216-6667
Abdellah AZMANI
Abdelmalek Essaadi University (Morocco)
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 ManagementReferences
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.
Google Scholar
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
Google Scholar
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
Google Scholar
Bondarouk, T., & Meijerink, J. (Eds.). (2024). Research handbook on human resource management and disruptive technologies. Edward Elgar Publishing.
Google Scholar
Bouhsaien, L. (2024, May 24). Database BA. https://drive.google.com/drive/folders/1sr6nQoMI0Tyy5VEuK1vcMELVpMhlqAzk
Google Scholar
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
Google Scholar
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
Google Scholar
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
Google Scholar
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
Google Scholar
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
Google Scholar
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
Google Scholar
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
Google Scholar
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
Google Scholar
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
Google Scholar
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
Google Scholar
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
Google Scholar
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
Google Scholar
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
Google Scholar
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
Google Scholar
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
Google Scholar
Guenole, N., & Feinzig, S. (2018). The business case for AI in HR. IBM Smarter Workforce Institute.
Google Scholar
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
Google Scholar
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
Google Scholar
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
Google Scholar
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
Google Scholar
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
Google Scholar
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
Google Scholar
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
Google Scholar
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
Google Scholar
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
Google Scholar
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
Google Scholar
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
Google Scholar
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
Google Scholar
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
Google Scholar
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
Google Scholar
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
Google Scholar
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
Google Scholar
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
Google Scholar
Authors
Loubna BOUHSAIENloubna.bouhsaien@etu.uae.ac.ma
Abdelmalek Essaadi University Morocco
https://orcid.org/0009-0003-7216-6667
Statistics
Abstract views: 150PDF downloads: 59
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.
Similar Articles
- Hawkar ASAAD, Shavan ASKAR, Ahmed KAKAMIN, Nayla FAIQ, EXPLORING THE IMPACT OF ARTIFICIAL INTELLIGENCE ON HUMANROBOT COOPERATION IN THE CONTEXT OF INDUSTRY 4.0 , Applied Computer Science: Vol. 20 No. 2 (2024)
- Eduardo Sánchez-García, Javier Martínez-Falcó, Bartolomé Marco-Lajara, Jolanta Słoniec, ANALYZING THE ROLE OF COMPUTER SCIENCE IN SHAPING MODERN ECONOMIC AND MANAGEMENT PRACTICES. BIBLIOMETRIC ANALYSIS , Applied Computer Science: Vol. 20 No. 1 (2024)
- Bartosz CIEŚLA, Grzegorz GUNIA, DEVELOPMENT OF INTEGRATED MANAGEMENT INFORMATION SYSTEMS IN THE CONTEXT OF INDUSTRY 4.0 , Applied Computer Science: Vol. 15 No. 4 (2019)
- Dilek AYDOGAN-KILIC, Deniz Kenan KILIC, Izabela Ewa NIELSEN, EXAMINATION OF SUMMARIZED MEDICAL RECORDS FOR ICD CODE CLASSIFICATION VIA BERT , Applied Computer Science: Vol. 20 No. 2 (2024)
- Siti ROHAJAWATI, Hutanti SETYODEWI, Ferryansyah Muji Agustian TRESNANTO, Debora MARIANTHI, Maruli Tua Baja SIHOTANG , KNOWLEDGE MANAGEMENT APPROACH IN COMPARATIVE STUDY OF AIR POLLUTION PREDICTION MODEL , Applied Computer Science: Vol. 20 No. 1 (2024)
- Monika KULISZ, Aigerim DUISENBEKOVA, Justyna KUJAWSKA, Danira KALDYBAYEVA, Bibigul ISSAYEVA, Piotr LICHOGRAJ, Wojciech CEL, IMPLICATIONS OF NEURAL NETWORK AS A DECISION-MAKING TOOL IN MANAGING KAZAKHSTAN’S AGRICULTURAL ECONOMY , Applied Computer Science: Vol. 19 No. 4 (2023)
- Monika KULISZ, Justyna KUJAWSKA, Zulfiya AUBAKIROVA, Gulnaz ZHAIRBAEVA, Tomasz WAROWNY, PREDICTION OF THE COMPRESSIVE STRENGTH OF ENVIRONMENTALLY FRIENDLY CONCRETE USING ARTIFICIAL NEURAL NETWORK , Applied Computer Science: Vol. 18 No. 4 (2022)
- Paweł PIEŚKO, Magdalena ZAWADA-MICHAŁOWSKA, USEFULNESS OF MODAL ANALYSIS FOR EVALUATION OF MILLING PROCESS STABILITY , Applied Computer Science: Vol. 13 No. 1 (2017)
- Aneta KARASEK, IT TOOLS SUPPORTING EMPLOYEE MANAGEMENT IN A HIGH-TECH ENTERPRISE , Applied Computer Science: Vol. 15 No. 1 (2019)
- KK Praneeth Tellakula, Saravana Kumar R, Sanjoy Deb, A SURVEY OF AI IMAGING TECHNIQUES FOR COVID-19 DIAGNOSIS AND PROGNOSIS , Applied Computer Science: Vol. 17 No. 2 (2021)
You may also start an advanced similarity search for this article.