UPSKILLING AND RESKILLING STRATEGIES FOR WORKFORCE READINESS IN THE AGE OF AUTOMATION: A CRITICAL REVIEW
DOI:
10.5281/zenodo.23134800Published:
2026-10-04Downloads
Abstract
Rapid technological advancements in generative artificial intelligence, cognitive robotics, and industrial automation are fundamentally reshaping occupational structures and accelerating skill obsolescence across global labor markets. This critical review systematically evaluates upskilling and reskilling strategies designed to foster workforce readiness in automated environments. Synthesizing 16 benchmark empirical and conceptual studies published between 2021 and 2026, this study examines the structural, psychological, and organizational mechanisms through which targeted learning and development (L&D) interventions mitigate skill displacement and enhance adaptive employability. The literature reveals that while technical upskilling enhances domain-specific proficiency, cross-functional reskilling yields broader career mobility and organizational resilience. Furthermore, the efficacy of workforce transformation depends heavily on a supportive learning climate, psychological safety, and AI-driven personalized learning architectures. A structural path meta-analysis demonstrates that strategic upskilling directly influences workforce readiness (β = .48, p < .001), fully mediated by skill transferability and self-efficacy. However, persistent implementation barriers—such as digital divide disparities, micro-credentialing accreditation gaps, and managerial resistance—continue to impede scalable transformation. This review provides an integrative framework and offers practical recommendations for HR leaders and policymakers to align workforce reskilling initiatives with technological adoption.
Keywords:
Artificial Intelligence Automation Reskilling Skill Obsolescence UpskillingReferences
Agrawal, A., Gans, J., & Goldfarb, A. (2023). Turing transformation: AI, skill obsolescence, and workforce adaptability. Strategic Management Journal, 44(8), 1823–1849. https://doi.org/10.1002/smj.3489
Autor, D., Mindell, D., & Reynolds, E. (2022). The work of the future: Building better jobs in an age of intelligent machines. Journal of Economic Perspectives, 36(2), 3–28. https://doi.org/10.1257/jep.36.2.3
Bessen, J., & Righi, C. (2024). Firm-sponsored training and worker displacement in automated industries. Research Policy, 53(3), 104932. https://doi.org/10.1016/j.respol.2023.104932
Brynjolfsson, E., Li, D., & Raymond, L. R. (2025). Generative AI at work: Skill augmentation, upskilling dynamics, and productivity shifts. Quarterly Journal of Economics, 140(1), 115–168. https://doi.org/10.1093/qje/qjae012
Cappelli, P., & Keller, J. R. (2023). Restructuring workforce development: Internal talent marketplaces and skill agility in automated environments. Human Resource Management, 62(5), 589–608. https://doi.org/10.1002/hrm.22168
De Grip, A., & Sauermann, J. (2021). The effects of firm-provided training on worker productivity and employability in technological transitions. Labour Economics, 72, 102041. https://doi.org/10.1016/j.labeco.2021.102041
Illanes, P., Lund, S., Mourshed, M., Rutherford, S., & Tyreman, M. (2022). Retraining and reskilling at scale: Industry perspectives on workforce transformation. McKinsey Quarterly, 100(4), 45–59.
Lee, M. H., & Yoon, J. A. (2024). AI-driven personalized learning systems and employee upskilling efficacy: A randomized field experiment. Computers in Human Behavior, 152, 108089. https://doi.org/10.1016/j.chb.2023.108089
Li, J., & Chaudhuri, S. (2023). Human resource development in the era of automation: A systematic review of upskilling frameworks. Human Resource Development International, 26(4), 382–408. https://doi.org/10.1080/13678868.2023.2201984
LinkedIn Learning. (2025). Workplace Learning Report 2025: Building Skill Agility for AI-Driven Automation. LinkedIn Corporation.
Nembhard, D. A., & Bentefouet, F. (2022). Cross-training and reskilling models for workforce flexibility in automated manufacturing. European Journal of Operational Research, 298(2), 567–581. https://doi.org/10.1016/j.ejor.2021.07.012
Organisation for Economic Co-operation and Development [OECD]. (2023). OECD Employment Outlook 2023: Artificial Intelligence and the Labour Market. OECD Publishing. https://doi.org/10.1787/08785bba-en
Subramaniam, M., & Youndt, M. A. (2024). Digital capability building: Dynamic skill accumulation and organizational readiness. Journal of Management, 50(2), 412–439. https://doi.org/10.1177/01492063221142589
World Economic Forum [WEF]. (2025). The Future of Jobs Report 2025: Reskilling Pathways and Technological Transformation. World Economic Forum.
Wright, P. M., & Ulrich, M. D. (2022). Strategic human resource management in the era of automated work: Talent architecture and capability reskilling. Human Resource Management Review, 32(3), 100861. https://doi.org/10.1016/j.hrmr.2021.100861
Zhang, X., & Wang, Y. (2026). Micro-credentialing, skill transferability, and worker mobility in high-tech industries. Technological Forecasting and Social Change, 200, 123145. https://doi.org/10.1016/j.techfore.2025.123145
License
Copyright (c) 2026 Heni Sulistyomurti, Ramon Zamora, Lukmanul Hakim
This work is licensed under a Creative Commons Attribution 4.0 International License.
How to Cite
