1University of Kelaniya, Western Province, Sri Lanka
Creative Commons Non Commercial CC BY-NC: This article is distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 License (http://www.creativecommons.org/licenses/by-nc/4.0/) which permits non-Commercial use, reproduction and distribution of the work without further permission provided the original work is attributed.
The technologies of artificial intelligence (AI) and virtual reality (VR) are reshaping human resource management (HRM). This chapter pays attention to the convergence of these cutting-edge technologies to change human resource (HR) practices like recruitment, training and employee engagement. Algorithms that are AI-driven can analyse vast datasets to recognise the best candidates, while VR simulations provide immersive environments for the performance evaluation of employees. AI and VR escalate the training and onboarding processes, contributing to the offering of personalised, interactive learning experiences that ameliorate retention and performance. Moreover, these emerging technologies can promote comparatively more inclusive and fair workplaces by reducing the biases that would arise with promotions and hiring. The unification of AI and VR in HRM gives birth to novel opportunities for data-driven decision-making by giving real-time feedback and bestowing better employee productivity levels and satisfaction. Challenges and provocations such as data privacy and ethical considerations are too inscribed to clinch on transparency and accountability about the usage of AI and VR. Thus, it concludes with the intuitions into the potential of these technologies in HRM and their influence on organisational success aspects. By welcoming AI and VR, HR departments can create more efficient, just and engaged work environments for their employees.
Artificial intelligence, virtual reality, human resource management, ethical considerations, human resource practices
Al-Ansi, A. M., Jaboob, M., Garad, A., & Al-Ansi, A. (2023). Analyzing augmented reality (AR) and virtual reality (VR) recent development in Education. Social Sciences & Humanities Open, 8(1), 100532. https://doi.org/10.1016/j.ssaho.2023.
100532
Atanasoff, L., & Venable, M. A. (2017). Technostress: Implications for adults in the workforce. The Career Development Quarterly, 65(4), 326–338. https://doi.org/10.1002/cdq.12111
Ayd
n, Ö., & Karaarslan, E. (2023). Artificial intelligence, VR, AR and metaverse technologies for human resources management. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.4480626
Bastian, R. (2021). Using virtual reality to make diversity training more effective. LinkedIn. https://www.linkedin.com/pulse/using-virtual-reality-make-diversity-training-more-rebekah-bastian/
Bharadiya, J. (2023). Machine learning and AI in business intelligence: Trends and opportunities. International Journal of Computer (IJC), 48(1), 123–134.
Cheong, L., & Chang, V. (2007). The need for data governance: A case study. ACIS 2007 Proceedings—18th Australasian Conference on Information Systems.
Dutta, D., Mishra, S. K., & Tyagi, D. (2022). Augmented employee voice and employee engagement using artificial intelligence-enabled Chatbots: A field study. The International Journal of Human Resource Management, 34(12), 2451–2480. https://doi.org/10.1080/09585192.2022.2085525
Dwivedi, Y. K., Hughes, L., Baabdullah, A. M., Ribeiro-Navarrete, S., Giannakis, M., Al-Debei, M. M., Dennehy, D., Metri, B., Buhalis, D., Cheung, C. M. K., Conboy, K., Doyle, R., Dubey, R., Dutot, V., Felix, R., Goyal, D. P., Gustafsson, A., Hinsch, C., Jebabli, I., … & Wamba, S. F. (2022). Metaverse beyond the hype: Multidisciplinary perspectives on emerging challenges, opportunities, and agenda for research, practice and policy. International Journal of Information Management, 66, 102542. https://doi.org/10.1016/j.ijinfomgt.2022.102542
Gayathri, K., & Jes Bella, K. M. (2024). The Determinants of Artificial Intelligence in HRM of IT Sector with Reference to KTCC Zone. Educational Administration: Theory and Practice, 30(5), 9503–9508. https://doi.org/10.53555/kuey.v30i5.3863
Holuša, V., Van
k, M., Beneš, F., Švub, J., & Staša, P. (2023). Virtual reality as a tool for sustainable training and education of employees in industrial enterprises. Sustainability, 15(17), 12886. https://doi.org/10.3390/su151712886
Ili
, B.,
uri
, Z., & Ostoji
, B. (2023). The role of artificial intelligence in human resource management.
Jalagat, R. (2016). The impact of change and change management in achieving corporate goals and objectives: Organizational perspective. International Journal of Science and Research (IJSR), 5, 1233–1239.
Jia, N., Luo, X., Fang, Z., & Liao, C. (2024). When and how artificial intelligence augments employee creativity. Academy of Management Journal, 67(1), 5–32. https://doi.org/10.5465/amj.2022.0426
Loutfi-Hipchen, E. (2024, February 29). Revolutionizing learning: The power of AI and VR in employee development. Chief Learning Officer—CLO Media. https://www.chieflearningofficer.com/2024/02/29/revolutionizing-learning-the-power-of-ai-and-vr-in-employee-development/
Madhani, P. M. (2010). Resource based view (RBV) of competitive advantage: An overview. Pankaj M Madhani.
Malik, N., Tripathi, S. N., Kar, A. K., & Gupta, S. (2021, June 18). Impact of artificial intelligence on employees working in Industry 4.0 led organizations. International Journal of Manpower. https://www.emerald.com/insight/content/doi/10.1108/IJM-03-2021-0173/full/html
Mugo, D., Njagi, K., Chemwei, B., & Motanya, J. (2017). The technology acceptance model (TAM) and its application to the utilization of mobile learning technologies. British Journal of Mathematics & Computer Science, 20(4), 1–8. https://doi.org/10.9734/bjmcs/2017/29015
Murugesan, U., Subramanian, P., Srivastava, S., & Dwivedi, A. (2023). A study of artificial intelligence impacts on human resource digitalization in Industry 4.0. Decision Analytics Journal, 7, 100249. https://doi.org/10.1016/j.dajour.2023.100249
Natarajan, S., Korapu, S., Paul, D., Kumar, J., & Rajalakshmi, M. (2024). AI-powered strategies for talent management optimization. Journal of Informatics Education and Research, 4, 854–860.
Nyathani, R. (2023). AI-driven HR analytics: Unleashing the power of HR data management. Journal of Technology and Systems, 5(2), 15–26. https://doi.org/10.47941/jts.1513
Osasona, F., Amoo, O. O., Atadoga, A., Abrahams, T. O., Farayola, O. A., & Ayinla, B. S. (2024). Reviewing the ethical implications of AI in decision making processes. International Journal of Management & Entrepreneurship Research, 6(2), 322–335. https://doi.org/10.51594/ijmer.v6i2.773
Pardamean, B., Suparyanto, T., Cenggoro, T. W., Sudigyo, D., & Anugrahana, A. (2022). AI-based learning style prediction in online learning for primary education. IEEE Access, 10, 35725–35735. https://doi.org/10.1109/access.2022.3160177
Perello Marin, M. R., & Tuffaha, M. (2021). Artificial intelligence definition, applications and adoption in human resource management: A systematic literature review. International Journal of Business Innovation and Research, 1(1), 1. https://doi.org/10.1504/ijbir.2021.10040005
Robinson, C., & Pope, R. (2023). Minoritized individuals and knowledge-economy. International Encyclopedia of Education (Fourth Edition), 244–250. https://doi.org/10.1016/b978-0-12-818630-5.08039-8
Saadat, V., & Saadat, Z. (2016). Organizational learning as a key role of organizational success. Procedia—Social and Behavioral Sciences, 230, 219–225. https://doi.org/10.1016/j.sbspro.2016.09.028
Schnackenberg, A. K., & Tomlinson, E. C. (2016). Organizational transparency. Journal of Management, 42(7), 1784–1810. https://doi.org/10.1177/0149206314525202
Stamolampros, P., Korfiatis, N., Chalvatzis, K., & Buhalis, D. (2019). Job satisfaction and employee turnover determinants in high contact services: Insights from employees’ online reviews. Tourism Management, 75, 130–147. https://doi.org/10.1016/j.tourman.2019.04.030
Sucianti Wahdaniah, R., Ambalele, E., & Tellu, A. H. (2023). Human resource management transformation in the digital age: Recent trends and implications. International Journal of Applied Research and Sustainable Sciences, 1(3), 239–258. https://doi.org/10.59890/ijarss.v1i3.902
Varsha P., S. (2023). How can we manage biases in artificial intelligence systems—A systematic literature review. International Journal of Information Management Data Insights, 3(1), 100165. https://doi.org/10.1016/j.jjimei.2023.100165
Vasilenko, E.. (2019). Virtual reality in HR management as a condition of innovative changes in a company. https://doi.org/10.2991/icdtli-19.2019.85.
Vishwanath, B., & Vaddepalli, S. (2023). The future of work: Implications of artificial intelligence on HR practices. Tuijin Jishu/Journal of Propulsion Technology, 44(3), 1711–1724. https://doi.org/10.52783/tjjpt.v44.i3.562
Wamba-Taguimdje, S.-L., Wamba, S. F., Kamdjoug, J. R. K., & Tchatchouang, C. E. (2020). Influence of artificial intelligence (AI) on firm performance: The business value of AI-based transformation projects. Business Process Management Journal, 26(7), 1893–1924. https://doi.org/10.1108/BPMJ-10-2019-0411
Xiuqing, D., Rafiq, M., & Zhumin, W. (2023). AI-based performance appraisal systems. Exploring the Intersection of AI and Human Resources Management, 15–29. https://doi.org/10.4018/979-8-3693-0039-8.ch002
Yazdanmehr, A., Jawad, M., Benbunan-Fich, R., & Wang, J. (2024). The role of ethical climates in employee information security policy violations. Decision Support Systems, 177, 114086. https://doi.org/10.1016/j.dss.2023.114086