The Role of AI-Driven Human Resource Information Systems (HRIS) in Enhancing Employee Performance and Organizational Agility: Evidence from Industry 5.0
DOI:
https://doi.org/10.71282/jurmie.v3i6.2327Keywords:
Artificial Intelligence, Human Resource Information Systems, Employee Performance, Organizational Agility, Industry 5.0Abstract
The rapid advancement of Artificial Intelligence (AI) has significantly transformed Human Resource Information Systems (HRIS), enabling organizations to improve workforce management through intelligent automation, predictive analytics, and data-driven decision-making. In the context of Industry 5.0, organizations are encouraged to integrate advanced digital technologies while maintaining a human-centered approach that emphasizes employee well-being, innovation, and organizational resilience. This study aims to explore the role of AI-driven Human Resource Information Systems (HRIS) in enhancing employee performance and organizational agility. A qualitative case study approach was employed to obtain an in-depth understanding of AI implementation in human resource management. Data were collected through semi-structured interviews, organizational documents, and a review of recent literature, and were analyzed using thematic analysis. The findings indicate that AI-driven HRIS improves employee performance by supporting more accurate recruitment, personalized learning and development, efficient performance evaluation, and evidence-based managerial decision-making. Furthermore, AI-supported HRIS enhances organizational agility by strengthening strategic workforce planning, accelerating organizational responses to environmental changes, and improving adaptability in dynamic business environments. However, the successful implementation of AI-driven HRIS depends on organizational readiness, employee digital competencies, ethical AI governance, and leadership commitment. This study contributes to the Human Resource Management literature by providing insights into the integration of AI-driven HRIS within the Industry 5.0 framework and offers practical recommendations for organizations seeking sustainable digital transformation through intelligent human resource management.
Downloads
References
Braun, V., & Clarke, V. (2021). Thematic analysis: A practical guide. SAGE Publications.
Breque, M., De Nul, L., & Petridis, A. (2021). Industry 5.0: Towards a sustainable, human-centric and resilient European industry. European Commission.
Budhwar, P., Chowdhury, S., Wood, G., Aguinis, H., Bamber, G. J., Beltran, J. R., Boselie, P., Paauwe, J., & Varma, A. (2023). Human resource management in the age of generative artificial intelligence: Perspectives and research directions. Human Resource Management Journal, 33(4), 606–659.
Chowdhury, S., Dey, P. K., Joel-Edgar, S., Bhattacharya, S., Rodriguez-Espindola, O., Abadie, A., & Truong, L. (2023). Unlocking the value of artificial intelligence in human resource management through organizational capability. Journal of Business Research, 157, 113593.
Creswell, J. W., & Poth, C. N. (2018). Qualitative inquiry and research design: Choosing among five approaches (4th ed.). SAGE Publications.
European Commission. (2021). Industry 5.0: Towards a sustainable, human-centric and resilient European industry.
Hair, J. F., Hult, G. T. M., Ringle, C. M., & Sarstedt, M. (2022). A primer on partial least squares structural equation modeling (PLS-SEM) (3rd ed.). SAGE Publications.
Jatobá, A., Santos, J., Gutiérrez-Franco, E., Ishikawa, T., & Costa, R. (2023). Artificial intelligence in human resource management: Trends, opportunities, and ethical challenges. AI, 4(2), 341–360.
Lincoln, Y. S., & Guba, E. G. (1985). Naturalistic inquiry. SAGE Publications.
Longo, F., Padovano, A., & Umbrello, S. (2020). Value-oriented and ethical technology engineering in Industry 5.0: A human-centric perspective for the design of the factory of the future. Applied Sciences, 10(12), 4182.
Margherita, A. (2022). Human resources analytics: A systematization of research topics and directions for future research. Human Resource Management Review, 32(2), 100795.
Minbaeva, D. (2021). Disrupted HR? Human resource management in the digital age. Human Resource Management Review, 31(1), 100820.
Nyamboga, T., Okeyo, W., & Mukhwana, E. (2025). Electronic human resource management and organizational agility: The mediating role of strategic human resource management. International Journal of Research in Business and Social Science, 14(1), 52–67.
Rožanec, J. M., Novalija, I., Zajec, P., Kenda, K., Tavakoli, H., Suh, S., Soldatos, J., et al. (2022). Human-centric artificial intelligence architecture for Industry 5.0 applications. Applied Sciences, 12(9), 4567.
Saunders, M., Lewis, P., & Thornhill, A. (2023). Research methods for business students (9th ed.). Pearson.
Teece, D. J. (2018). Business models and dynamic capabilities. Long Range Planning, 51(1), 40–49.
Venugopal, A., Upadhyay, A. K., & Sharma, S. (2024). Artificial intelligence in human resource management: Current applications and future research agenda. Cogent Business & Management, 11(1), 2432550.
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.
Vyhmeister, E., & Castane, G. G. (2024). When Industry meets trustworthy AI: A systematic review of AI for Industry 5.0. arXiv.
Yin, R. K. (2018). Case study research and applications: Design and methods (6th ed.). SAGE Publications.
Downloads
Published
Issue
Section
License
Copyright (c) 2026 Mely Daniati, Ramadhika Trisnasari, Syahrial Shaddiq, Khuzaini, Zakky Zamrudi (Author)
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
