Future Skills, Workforce Agility, and Human Resource Transformation in the AI Era Systematic Literature Review
Main Article Content
Abstract
Artificial intelligence (AI) is transforming work and human resource management (HRM), increasing the demand for future skills and workforce agility while raising concerns about employee well-being, autonomy, and the ethical governance of technology. This study aims to integrate the literature on future skills, workforce agility, HR transformation, and human-centered AI to clarify their conceptual relationships and identify key research gaps. Using a systematic thematic and integrative literature synthesis, the review examines contributions from human resource management, strategic management, information systems, and humanistic management. The synthesis indicates that digital and AI-related capabilities must be developed alongside critical thinking, creativity, collaboration, adaptability, and continuous learning. These capabilities can support workforce agility, while HR transformation provides organizational mechanisms for skills development, talent management, and the integration of AI into work processes. However, the literature remains fragmented in its definitions and measurements of future skills and agility, and empirical evidence explaining how agility translates into organizational performance remains limited. Research on human-centered AI in HRM is also insufficient to establish how technological efficiency can be reconciled with employee autonomy, well-being, and ethical accountability. The review highlights the need for an integrative framework connecting skills development, workforce agility, HR transformation, and human-centered governance. Future research should prioritize construct standardization, empirical and longitudinal testing, and examination of the organizational conditions under which AI augments rather than undermines human work.
Article Details
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
References
Ahammad, M. F., Glaister, K. W., & Gomes, E. (2019). Strategic agility and human resource management. Human Resource Management Review, 30(1), 100700. https://doi.org/10.1016/j.hrmr.2019.100700
Ajgaonkar, S., Neelam, N., & Wiemann, J. (2021). Drivers of workforce agility: A dynamic capability perspective. International Journal of Organizational Analysis, 30(4), 951–982. https://doi.org/10.1108/IJOA-11-2020-2507
Audrin, B., Audrin, C., & Salamin, X. (2024). Digital skills at work: Conceptual development and empirical validation of a measurement scale. Technological Forecasting and Social Change, 202, 123279. https://doi.org/10.1016/j.techfore.2024.123279
Bankins, S., & Formosa, P. (2023). The ethical implications of artificial intelligence (AI) for meaningful work. Journal of Business Ethics, 185(4), 725–740. https://doi.org/10.1007/s10551-023-05339-7
Basu, S., Majumdar, B., Mukherjee, K., Munjal, S., & Palaksha, C. (2022). Artificial intelligence–HRM interactions and outcomes: A systematic review and causal configurational explanation. Human Resource Management Review, 33(1), 100893. https://doi.org/10.1016/j.hrmr.2022.100893
Bouwmans, M., Lub, X., Orlowski, M., & Nguyen, T. T. (2024). Developing the digital transformation skills framework: A systematic literature review approach. PLOS ONE, 19(7), e0304127. https://doi.org/10.1371/journal.pone.0304127
Brynjolfsson, E., Li, D., & Raymond, L. (2025). Generative AI at work. The Quarterly Journal of Economics, 140(2), 889–942. https://doi.org/10.1093/qje/qjae044
Capraro, V., et al. (2024). The impact of generative artificial intelligence on socioeconomic inequalities and policy making. PNAS Nexus, 3(6), pgae191. https://doi.org/10.1093/pnasnexus/pgae191
Carter, L., Liu, D., & Cantrell, C. (2020). Exploring the intersection of the digital divide and artificial intelligence: A hermeneutic literature review. AIS Transactions on Human-Computer Interaction, 12(4), 253–275. https://doi.org/10.17705/1thci.00138
Chiu, T. K. F., Ahmad, Z., Ismailov, M., & Sanusi, I. T. (2024). What are artificial intelligence literacy and competency? A comprehensive framework to support them. Computers and Education Open, 6, 100171. https://doi.org/10.1016/j.caeo.2024.100171
Chuang, Y., Chiang, H.-L., & Lin, A.-P. (2025). Insights from the Job Demands–Resources Model: AI’s dual impact on employees’ work and life well-being. International Journal of Information Management, 83, 102887. https://doi.org/10.1016/j.ijinfomgt.2025.102887
Cooke, F. L., Dickmann, M., & Parry, E. (2022). Building sustainable societies through human-centred human resource management: Emerging issues and research opportunities. The International Journal of Human Resource Management, 33(1), 1–15. https://doi.org/10.1080/09585192.2021.2021732
Cramarenco, R. E., Burcă-Voicu, M. I., & Dabija, D. (2023). The impact of artificial intelligence (AI) on employees’ skills and well-being in global labor markets: A systematic review. Oeconomia Copernicana, 14(3), 731–767. https://doi.org/10.24136/oc.2023.022
Doz, Y., & Kosonen, M. (2008). The dynamics of strategic agility: Nokia’s rollercoaster experience. California Management Review, 50(3), 95–118. https://doi.org/10.2307/41166447
Dumitru, D., & Halpern, D. F. (2023). Critical thinking: Creating job-proof skills for the future of work. Journal of Intelligence, 11(10), 194. https://doi.org/10.3390/jintelligence11100194
Fenwick, A., Molnár, G., & Frangos, P. (2024a). Revisiting the role of HR in the age of AI: Bringing humans and machines closer together in the workplace. Frontiers in Artificial Intelligence, 6, 1272823. https://doi.org/10.3389/frai.2023.1272823
Fenwick, A., Molnár, G., & Frangos, P. (2024b). The critical role of HRM in AI-driven digital transformation: A paradigm shift to enable firms to move from AI implementation to human-centric adoption. Discover Artificial Intelligence, 4, Article 34. https://doi.org/10.1007/s44163-024-00125-4
Franco, C., & Landini, F. (2021). Organizational drivers of innovation: The role of workforce agility. Research Policy, 51(2), 104423. https://doi.org/10.1016/j.respol.2021.104423
Goos, M., & Savona, M. (2024). The governance of artificial intelligence: Harnessing opportunities and mitigating challenges. Research Policy, 53(3), 104928. https://doi.org/10.1016/j.respol.2023.104928
Guest, D. (2017). Human resource management and employee well-being: Towards a new analytic framework. Human Resource Management Journal, 27(1), 22–38. https://doi.org/10.1111/1748-8583.12139
Heß, P., Janßen, S., & Leber, U. (2023). The effect of automation technology on workers’ training participation. Economics of Education Review, 96, 102438. https://doi.org/10.1016/j.econedurev.2023.102438
Hui, X., Reshef, O., & Zhou, L. (2024). The short-term effects of generative artificial intelligence on employment: Evidence from an online labor market. Organization Science, 35(6), 1977–1989. https://doi.org/10.1287/orsc.2023.18441
Jarrahi, M. H., Lutz, C., & Newlands, G. (2022). Artificial intelligence, human intelligence and hybrid intelligence based on mutual augmentation. Big Data & Society, 9(2). https://doi.org/10.1177/20539517221142824
Jooss, S., Collings, D. G., McMackin, J., & Dickmann, M. (2023). A skills-matching perspective on talent management: Developing strategic agility. Human Resource Management, 63(1), 141–157. https://doi.org/10.1002/hrm.22192
Kanbach, D. K., Heiduk, L., Blueher, G., Schreiter, M., & Lahmann, A. (2023). The GenAI is out of the bottle: Generative artificial intelligence from a business model innovation perspective. Review of Managerial Science, 18(4), 1189–1220. https://doi.org/10.1007/s11846-023-00696-z
Kotsiou, A., Fajardo-Tovar, D., Cowhitt, T., Major, L., & Wegerif, R. (2022). A scoping review of future skills frameworks. Irish Educational Studies, 41(1), 171–186. https://doi.org/10.1080/03323315.2021.2022522
Lamers, L., Meijerink, J., Jansen, G., & Boon, M. (2022). A capability approach to worker dignity under algorithmic management. Ethics and Information Technology, 24(1), Article 10. https://doi.org/10.1007/s10676-022-09637-y
Malik, A., Budhwar, P., Mohan, H., & Srikanth, N. R. (2022). Employee experience: The missing link for engaging employees: Insights from an MNE’s AI-based HR ecosystem. Human Resource Management, 62(1), 97–115. https://doi.org/10.1002/hrm.22133
McMackin, J., & Heffernan, M. (2020). Agile for HR: Fine in practice, but will it work in theory? Human Resource Management Review, 31(4), 100791. https://doi.org/10.1016/j.hrmr.2020.100791
Mirbabaie, M., Brünker, F., Frick, N., & Stieglitz, S. (2021). The rise of artificial intelligence: Understanding the AI identity threat at the workplace. Electronic Markets, 32(1), 73–99. https://doi.org/10.1007/s12525-021-00496-x
Moh’d, S., Gregory, P., Barroca, L., & Sharp, H. (2024). Agile human resource management: A systematic mapping study. German Journal of Human Resource Management, 38(4), 345–374. https://doi.org/10.1177/23970022231226316
Morandini, S., Fraboni, F., Angelis, M. D., Puzzo, G., Giusino, D., & Pietrantoni, L. (2023). The impact of artificial intelligence on workers’ skills: Upskilling and reskilling in organisations. Informing Science: The International Journal of an Emerging Transdiscipline, 26, 39–68. https://doi.org/10.28945/5078
Papagiannidis, E., Mikalef, P., & Conboy, K. (2025). Responsible artificial intelligence governance: A review and research framework. The Journal of Strategic Information Systems, 34(2), 101885. https://doi.org/10.1016/j.jsis.2024.101885
Parker, S. K., & Grote, G. (2019). Automation, algorithms, and beyond: Why work design matters more than ever in a digital world. Applied Psychology, 71(4), 1171–1204. https://doi.org/10.1111/apps.12241
Petermann, M. K. H., & Zacher, H. (2022). Workforce agility: Development and validation of a multidimensional measure. Frontiers in Psychology, 13, 841862. https://doi.org/10.3389/fpsyg.2022.841862
Prikshat, V., Islam, M., Patel, P., Malik, A., Budhwar, P., & Gupta, S. (2023). AI-augmented HRM: Literature review and a proposed multilevel framework for future research. Technological Forecasting and Social Change, 193, 122645. https://doi.org/10.1016/j.techfore.2023.122645
Raisch, S., & Krakowski, S. (2021). Artificial intelligence and management: The automation–augmentation paradox. Academy of Management Review, 46(1), 192–210. https://doi.org/10.5465/amr.2018.0072
Salmen, K., & Festing, M. (2021). Paving the way for progress in employee agility research: A systematic literature review and framework. The International Journal of Human Resource Management, 33(22), 4386–4439. https://doi.org/10.1080/09585192.2021.1943491
Tessarini, G., & Saltorato, P. (2021). Workforce agility: A systematic literature review and a research agenda proposal. Innovar, 31(81), 155–167. https://doi.org/10.15446/innovar.v31n81.95582
Xu, W., Dainoff, M. J., Ge, L., & Gao, Z. (2022). Transitioning to human interaction with AI systems: New challenges and opportunities for HCI professionals to enable human-centered AI. International Journal of Human-Computer Interaction, 39(3), 494–518. https://doi.org/10.1080/10447318.2022.2041900