Human Capital in AI-Enabled Digital Transformation: A Systematic Review of Workforce Competencies and HRM Mechanisms

Authors

DOI:

https://doi.org/10.31181/jopi41202669

Keywords:

Human capital, Digital transformation, Industry 4.0, Industry 5.0, Artificial intelligence, Human resource management, Workforce skills, Organizational strategy, Transport services, Logistics

Abstract

This article presents a systematic literature review of the role of human capital in digital transformation and artificial intelligence (AI), focusing on how these developments reshape workforce competencies and human resource management (HRM) during the transition from Industry 4.0 to Industry 5.0. Following the PRISMA guidelines, the study combines thematic coding with comparative analysis. From an initial pool of 216 publications, 46 studies were selected for in-depth analysis. The review examines how AI and digitalisation change workforce skill requirements and how HRM mechanisms can help organisations develop and sustain the necessary competencies. The findings indicate a shift from routine and manual tasks toward hybrid competency profiles that integrate data analytics skills, AI literacy, human–machine interaction skills, and higher-order socio-cognitive capabilities, including adaptive reasoning, collaboration, and ethical judgement. HRM emerges as a strategic integrator that supports continuous reskilling, predictive skills-gap analysis, and the development of effective human–AI teams. Based on these findings, the study proposes a multilevel framework explaining how institutional mechanisms, organisational strategy, HRM practices, and human–AI complementarity jointly shape workforce competitiveness in AI-enabled digital transformation. The framework contributes to human-centric digitalisation by linking workforce competitiveness to capability velocity and human–AI complementarity. It also provides managerial implications for designing learning, governance, and decision-making structures that enable organisations to respond to evolving competency requirements and translate technological potential into sustainable operational advantages.

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References

Abrahamsson, K., Ennals, R., Harlin, U., & Mathieu, C. (2025). Green Skills, Workplace Innovations and Just Transition. European Journal of Workplace Innovation, 9(1 & 2), 4–11. https://doi.org/10.46364/ejwi.v9i1.1515

Lu, Y. (2017). Industry 4.0: A survey on technologies, applications and open research issues. Journal of Industrial Information Integration, 6, 1–10. https://doi.org/10.1016/j.jii.2017.04.005

Schumacher, A., Nemeth, T., & Sihn, W. (2019). Roadmapping towards industrial digitalisation based on an Industry 4.0 maturity model for manufacturing enterprises. Procedia CIRP, 79, 409–414. https://doi.org/10.1016/j.procir.2019.02.110

European Commission, Directorate-General for Research and Innovation, Breque, M., De Nul, L., & Petridis, A. (2021). Industry 5.0 – Towards a sustainable, human-centric and resilient European industry. Publications Office of the European Union. https://doi.org/10.2777/308407

Yang, J., Liu, Y., & Morgan, P. L. (2024). Human–machine interaction towards Industry 5.0: Human-centric smart manufacturing. Digital Engineering, 2, 100013. https://doi.org/10.1016/j.dte.2024.100013

Abril-Jiménez, P., Carvajal-Flores, D., Buhid, E., & Cabrera-Umpierrez, M. F. (2024). Enhancing worker-centred digitalisation in industrial environments: A KPI evaluation methodology. Heliyon, 10(4), e26638. https://doi.org/10.1016/j.heliyon.2024.e26638

Horvat, D., Stahlecker, T., Zenker, A., Lerch, C., & Mladineo, M. (2018). A conceptual approach to analysing manufacturing companies’ profiles concerning Industry 4.0 in emerging economies. Procedia Manufacturing, 17, 419–426. https://doi.org/10.1016/j.promfg.2018.10.065

Page, M. J., McKenzie, J. E., Bossuyt, P. M., Boutron, I., Hoffmann, T. C., Mulrow, C. D., Shamseer, L., Tetzlaff, J. M., Akl, E. A., Brennan, S. E., Chou, R., Glanville, J., Grimshaw, J. M., Hróbjartsson, A., Lalu, M. M., Li, T., Loder, E. W., Mayo-Wilson, E., McDonald, S., McGuinness, L. A., Stewart, L. A., Thomas, J., Tricco, A. C., Welch, V. A., Whiting, P., & Moher, D. (2021). The PRISMA 2020 statement: An updated guideline for reporting systematic reviews. BMJ, 372, n71. https://doi.org/10.1136/bmj.n71

Sahoo, S. K., Sahu, S., Choudhury, B. B., Dhal, P. R., & Dhar, I. (2026). Transforming Decision-Making in Generation Z Education: A Systematic and Bibliometric Review of Artificial Intelligence. Journal of Contemporary Decision Science, 2(1), 114-130.

Sarkar, A., & Goswami, S. S. (2026). A Systematic Review of MCDM Techniques for Decision-Making in Smart Manufacturing Systems under Industry 4.0. Management Science Advances, 3(1), 290-306.

UNESCO Institute for Statistics (UIS). (2023). Digital literacy. Glossary. https://databrowser.uis.unesco.org/resources/glossary/3225

Cosgrove, J., & Cachia, R. (2025). DigComp 3.0 information leaflet – European Digital Competence Framework – fifth edition (JRC144679). Publications Office of the European Union, Luxembourg. https://doi.org/10.2760/1812776

van Tonder, C., Bossink, B., Schachtebeck, C., & Nieuwenhuizen, C. (2024). Key Dimensions That Measure the Digital Maturity Levels of Small and Medium-Sized Enterprises (SMEs). Journal of Technology Management & Innovation, 19(1), 110–130. https://doi.org/10.4067/S0718-27242024000100110

Schumacher, A., Erol, S., & Sihn, W. (2016). A Maturity Model for Assessing Industry 4.0 Readiness and Maturity of Manufacturing Enterprises. Procedia CIRP, 52, 161–166. https://doi.org/10.1016/j.procir.2016.07.040

Caiado, R. G. G., Scavarda, L. F., Gavião, L. O., Ivson, P., Nascimento, D. L. d. M., & Garza-Reyes, J. A. (2021). A fuzzy rule-based industry 4.0 maturity model for operations and supply chain management. International Journal of Production Economics, 231, 107883. https://doi.org/10.1016/j.ijpe.2020.107883

Alasoini, T., & Selander, K. (2023). Employee Participation, Digital Sophistication and Innovation Performance: Analysis Based on the Finnish MEADOW Survey. European Journal of Workplace Innovation, 8(1), 69–86. https://doi.org/10.46364/ejwi.v8i1.1215

Katonáné Gyönyörű, K. I., & Katona, J. (2025). Comprehensive overview of the concept and applications of AI-based adaptive learning. Acta Polytechnica Hungarica, 22(3), 167–186. https://doi.org/10.12700/APH.22.3.2025.3.9

Kryukov, V., Shakhgeldyan, K., Kiykova, E., Kiykova, D., & Saychuk, D. (2022). Assessment of transport enterprise readiness for digital transformation. Transportation Research Procedia, 63, 2710–2718. https://doi.org/10.1016/j.trpro.2022.06.313

Putnik, K., Oeij, P., Dhondt, S., van der Torre, W., Vroome, E. de, & Preenen, P. (2019). Innovation adoption of employees in the logistics sector in the Netherlands: The role of workplace innovation. European Journal of Workplace Innovation, 4(2). https://doi.org/10.46364/ejwi.v4i2.543

Ning, L., & Yao, D. (2023). The Impact of Digital Transformation on Supply Chain Capabilities and Supply Chain Competitive Performance. Sustainability, 15(13), 10107. https://doi.org/10.3390/su151310107

Yang, Y.-C., & Hsieh, Y.-H. (2024). The critical success factors of smart port digitalisation development in the post-COVID-19 era. Case Studies on Transport Policy, 17, 101231. https://doi.org/10.1016/j.cstp.2024.101231

Berretta, S., Tausch, A., Ontrup, G., Gilles, B., Peifer, C., & Kluge, A. (2023). Defining human-AI teaming the human-centered way: A scoping review and network analysis. Frontiers in Artificial Intelligence, 6, 1250725. https://doi.org/10.3389/frai.2023.1250725

Johansson, J., & Abrahamsson, L. (2021). Digitalisation and Sustainable Work: Obstacles and pathways. European Journal of Workplace Innovation, 6(2), 187–197. https://doi.org/10.46364/ejwi.v6i2.801

Fareri, S., Fantoni, G., Chiarello, F., Coli, E., & Binda, A. (2020). Estimating Industry 4.0 impact on job profiles and skills using text mining. Computers in Industry, 118, 103222. https://doi.org/10.1016/j.compind.2020.103222

Sima, V., Gheorghe, I. G., Subić, J., & Nancu, D. (2020). Influences of the Industry 4.0 Revolution on the Human Capital Development and Consumer Behavior: A Systematic Review. Sustainability, 12(10), 4035. https://doi.org/10.3390/su12104035

Trenerry, B., Chng, S., Wang, Y., Suhaila, Z. S., Lim, S. S., Lu, H. Y., & Oh, P. H. (2021). Preparing Workplaces for Digital Transformation: An Integrative Review and Framework of Multi-Level Factors. Frontiers in Psychology, 12, 620766. https://doi.org/10.3389/fpsyg.2021.620766

Kraus, S., Ferraris, A., & Bertello, A. (2023). The future of work: How innovation and digitalisation re-shape the workplace. Journal of Innovation & Knowledge, 8(4), 100438. https://doi.org/10.1016/j.jik.2023.100438

Sun, X., & Song, Y. (2025). Unlocking the Synergy: Increasing productivity through Human-AI collaboration in the Industry 5.0 Era. Computers & Industrial Engineering, 200, 110657. https://doi.org/10.1016/j.cie.2024.110657

Wen, D., Jiao, X., Liu, P., Zhu, G., Shi, Y., & Huang, K. (2024). Task-Oriented Over-the-Air Computation for Multi-Device Edge AI. IEEE Transactions on Wireless Communications, 23(3), 2039–2053. https://doi.org/10.1109/TWC.2023.3294703

Tupayachi, J., Xu, H., Omitaomu, O. A., Camur, M. C., Sharmin, A., & Li, X. (2024). Towards Next-Generation Urban Decision Support Systems through AI-Powered Construction of Scientific Ontology Using Large Language Models—A Case in Optimizing Intermodal Freight Transportation. Smart Cities, 7(5), 2392–2421. https://doi.org/10.3390/smartcities7050094

Horváth, D., & Szabó, R. Z. (2019). Driving forces and barriers of Industry 4.0: Do multinational and small and medium-sized companies have equal opportunities? Technological Forecasting and Social Change, 146, 119–132. https://doi.org/10.1016/j.techfore.2019.05.021

Saniuk, S., & Grabowska, S. (2023). Skills and Competencies of Industrial Employees in the Industry 5.0 Environment. In: Trojanowska, J., et al. (eds) Advances in Manufacturing IV, pp. 251–264. https://doi.org/10.1007/978-3-031-44282-7_20

Sardi, A., Sorano, E., Garengo, P., & Ferraris, A. (2021). The role of HRM in the innovation of performance measurement and management systems: a multiple case study in SMEs. Employee Relations, 43(2), 589–606. https://doi.org/10.1108/ER-03-2020-0101

Baranyi, V. (2025). Systematic literature review on the digital transformation of the personnel selection process. German Journal of Human Resource Management, 40(2), 223-254. https://doi.org/10.1177/23970022251363012

Maden Eyiusta, C., & Esen, A. (2025). Fostering organisational innovation in SMEs through employee-driven innovation: The role of IB-HRM practices and empowering leadership. European Management Journal, 44(3), 476–493. https://doi.org/10.1016/j.emj.2025.04.006

Martini, B., Bellisario, D., & Coletti, P. (2024). Human-Centered and Sustainable Artificial Intelligence in Industry 5.0: Challenges and Perspectives. Sustainability, 16(13), 5448. https://doi.org/10.3390/su16135448

Neugebauer, R., Hippmann, S., Leis, M., & Landherr, M. (2016). Industrie 4.0 - From the Perspective of Applied Research. Procedia CIRP, 57, 2–7. https://doi.org/10.1016/j.procir.2016.11.002

Frank, A. G., Dalenogare, L. S., & Ayala, N. F. (2019). Industry 4.0 technologies: Implementation patterns in manufacturing companies. International Journal of Production Economics, 210, 15–26. https://doi.org/10.1016/j.ijpe.2019.01.004

Mahmood, T., & Mubarik, M. S. (2020). Balancing innovation and exploitation in the fourth industrial revolution: Role of intellectual capital and technology absorptive capacity. Technological Forecasting and Social Change, 160, 120248. https://doi.org/10.1016/j.techfore.2020.120248

Hein-Pensel, F., Winkler, H., Brückner, A., Wölke, M., Jabs, I., Mayan, I. J., Kirschenbaum, A., Friedrich, J., & Zinke-Wehlmann, C. (2023). Maturity assessment for Industry 5.0: A review of existing maturity models. Journal of Manufacturing Systems, 66, 200–210. https://doi.org/10.1016/j.jmsy.2022.12.009

Tyagi, V., Mittal, S., & Gupta, A. (2025). Overview of Industry 5.0 and its impact on HR. In: Industry 5.0 and Human Resource Management, pp. 79–101. https://doi.org/10.1201/9781032677040-5

Maasouman, M. A., & Demirli, K. (2016). Development of a lean maturity model for operational level planning. The International Journal of Advanced Manufacturing Technology, 83(5-8), 1171–1188. https://doi.org/10.1007/s00170-015-7513-4

Teece, D. J., Pisano, G., & Shuen, A. (1997). Dynamic capabilities and strategic management. Strategic Management Journal, 18(7), 509–533. https://doi.org/10.1002/(SICI)1097-0266(199708)18:7%3C509::AID-SMJ882%3E3.0.CO;2-Z

Helfat, C. E., & Peteraf, M. A. (2009). Understanding dynamic capabilities: Progress along a developmental path. Strategic Organization, 7(1), 91–102. https://doi.org/10.1177/1476127008100133

Karim, S., & Capron, L. (2016). Reconfiguration: Adding, redeploying, recombining and divesting resources and business units. Strategic Management Journal, 37(13), E54-E62. https://doi.org/10.1002/smj.2537

Ostrom, E. (1990). Governing the Commons: The Evolution of Institutions for Collective Action. Cambridge University Press. https://doi.org/10.1017/CBO9780511807763

UNDP - Chief Digital Office. (2022). Inclusive by Design: Accelerating Digital Transformation for the Global Goals. Policy Brief. United Nations Development Programme, New York. https://www.undp.org/publications/inclusive-design-accelerating-digital-transformation-global-goals

OECD. (2021). Development Co-operation Report 2021: Shaping a Just Digital Transformation. https://doi.org/10.1787/ce08832f-en

Hanisch, M., Goldsby, C. M., Fabian, N. E., & Oehmichen, J. (2023). Digital governance: A conceptual framework and research agenda. Journal of Business Research, 162, 113777. https://doi.org/10.1016/j.jbusres.2023.113777

Docherty, I., Marsden, G., & Anable, J. (2018). The governance of smart mobility. Transportation Research Part A, 115, 114–125. https://doi.org/10.1016/j.tra.2017.09.012

Bag, S., Pretorius, J. H. C., Gupta, S., & Dwivedi, Y. K. (2021). Role of institutional pressures and resources in the adoption of big data analytics powered artificial intelligence, sustainable manufacturing practices and circular economy capabilities. Technological Forecasting and Social Change, 163, 120420. https://doi.org/10.1016/j.techfore.2020.120420

Abourokbah, S. H., Mashat, R. M., & Salam, M. A. (2023). Role of Absorptive Capacity, Digital Capability, Agility, and Resilience in Supply Chain Innovation Performance. Sustainability, 15(4), 3636. https://doi.org/10.3390/su15043636

Atay, S., Müftüoğlu, C. T., Gülmez, N., & Şahin, M. (2025). Society 5.0 and human-centered technology: Redefining talent management in the digital age. Sustainable Futures, 9, 100733. https://doi.org/10.1016/j.sftr.2025.100733

Raina, K., Sharma, G. D., Taheri, B., Dev, D., & Chavriya, S. (2026). Artificial intelligence-driven management: Bridging innovation, knowledge creation, and sustainable business practices. Journal of Innovation & Knowledge, 11, 100860. https://doi.org/10.1016/j.jik.2025.100860

Kovács, E.-Zs., & Horváth, I. (2025). Trust, transparency, and AI adoption in business. Acta Polytechnica Hungarica, 22(6), 81–100. https://doi.org/10.12700/APH.22.6.2025.6.6

Cohen, W. M., & Levinthal, D. A. (1990). Absorptive Capacity: A New Perspective on Learning and Innovation. Administrative Science Quarterly, 35(1), 128–152. https://doi.org/10.2307/2393553

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Published

2026-10-13

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Vol. 4 No. 1 (2026): Journal of Operations Intelligence

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Articles

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Copyright (c) 2026 Marat Idrissov, Sebastian Lang, Thomas Stahlecker, Gulmira Mukhanova, Botagoz Kuanyshbayeva, Ágnes Csiszárik-Kocsir (Author)

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Idrissov, M., Lang, S., Stahlecker, T., Mukhanova, G., Kuanyshbayeva, B., & Csiszárik-Kocsir, Á. (2026). Human Capital in AI-Enabled Digital Transformation: A Systematic Review of Workforce Competencies and HRM Mechanisms. Journal of Operations Intelligence, 4(1), 162-185. https://doi.org/10.31181/jopi41202669