Human Capital Innovation dalam Menghadapi Skill Gap Tenaga Kerja Indonesia di Era Artificial Intelligence
DOI:
https://doi.org/10.61132/anggaran.v4i2.2484Keywords:
Artificial Intelligence, Human Capital Innovation, Labor Market, Mixed Method, Skill GapAbstract
The rapid advancement of Artificial Intelligence (AI) has transformed workforce competency requirements and intensified the skills gap between educational outcomes and industry demands. This challenge requires human capital innovation to improve workforce readiness in the digital transformation era. This study aims to analyze the role of human capital innovation in addressing the workforce skills gap in Indonesia using a Systematic Literature Review (SLR). A total of 32 relevant scholarly articles on human capital, Artificial Intelligence, and workforce skills gaps in Indonesia were systematically reviewed. The data were analyzed through thematic synthesis to identify major challenges and competency development strategies. The findings indicate that the skills gap is primarily caused by the mismatch between educational curricula and industrial needs, limited AI literacy, and inadequate digital competencies among workers. The most frequently identified strategies include curriculum transformation, continuous upskilling and reskilling programs, strengthening AI literacy, and collaboration among government, higher education institutions, and industry. These findings suggest that adaptive human capital development supported by lifelong learning is essential for enhancing the competitiveness of Indonesia's workforce and ensuring successful adaptation to the rapid changes brought about by Artificial Intelligence.
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References
Barney, J. (1991). Firm resources and sustained competitive advantage. Journal of Management, 17(1), 99–120. https://doi.org/10.1177/014920639101700108
Barney, J. (1991). Firm resources and sustained competitive advantage. Journal of Management, 17(1), 99–120. https://doi.org/10.1177/014920639101700108
Barney, J. (1991). Firm resources and sustained competitive advantage. Journal of Management, 17(1), 99–120. https://doi.org/10.1177/014920639101700108
Becker, G. S. (1964). Human capital: A theoretical and empirical analysis, with special reference to education. Columbia University Press.
Becker, G. S. (1964). Human capital: A theoretical and empirical analysis, with special reference to education. Columbia University Press.
Budhwar, P., Chowdhury, S., Wood, G., Aguinis, H., Bamber, G. J., Beltran, J. R., ... Varma, A. (2023). Human resource management in the age of generative artificial intelligence: Perspectives and research directions on ChatGPT. Human Resource Management Journal, 33(3), 606–659. https://doi.org/10.1111/1748-8583.12524
Budhwar, P., Chowdhury, S., Wood, G., Aguinis, H., Bamber, G. J., Beltran, J. R., et al. (2023). Human resource management in the age of generative artificial intelligence: Perspectives and research directions on ChatGPT. Human Resource Management Journal, 33(3), 606–659. https://doi.org/10.1111/1748-8583.12524
Budhwar, P., Chowdhury, S., Wood, G., Aguinis, H., Bamber, G. J., Beltran, J. R., et al. (2023). Human resource management in the age of generative artificial intelligence: Perspectives and research directions on ChatGPT. Human Resource Management Journal, 33(3), 606–659. https://doi.org/10.1111/1748-8583.12524
Bujold, A., Grandbois, É., & Bastin, M. (2024). Responsible artificial intelligence in human resource management: A systematic review and future research agenda. Human Resource Management Review. https://doi.org/10.1016/j.hrmr.2024.101062
Bujold, A., Grandbois, É., & Bastin, M. (2024). Responsible artificial intelligence in human resource management: A systematic review and future research agenda. Human Resource Management Review. https://doi.org/10.1016/j.hrmr.2024.101062
Feuerriegel, S., Hartmann, J., Janiesch, C., & Zschech, P. (2023). Generative AI. Business & Information Systems Engineering. https://doi.org/10.2139/ssrn.4443189
Malik, A., Budhwar, P., & Kazmi, B. A. (2023). Artificial intelligence (AI)-assisted HRM: Towards an extended strategic framework. Human Resource Management Review, 33(1), 100940. https://doi.org/10.1016/j.hrmr.2022.100940
Malik, A., Budhwar, P., & Kazmi, B. A. (2023). Artificial intelligence (AI)-assisted HRM: Towards an extended strategic framework. Human Resource Management Review, 33(1), 100940. https://doi.org/10.1016/j.hrmr.2022.100940
Malik, A., Budhwar, P., & Kazmi, B. A. (2023). Artificial intelligence (AI)-assisted HRM: Towards an extended strategic framework. Human Resource Management Review, 33(1), 100940. https://doi.org/10.1016/j.hrmr.2022.100940
Malik, A., Budhwar, P., Mohan, H., & Srikanth, N. R. (2023). 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
Malik, A., Budhwar, P., Mohan, H., & Srikanth, N. R. (2023). 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
Organisation for Economic Co-operation and Development. (2023). OECD skills outlook 2023: Skills for a resilient green and digital transition. OECD Publishing. https://doi.org/10.1787/08785bba-en
Organisation for Economic Co-operation and Development. (2023). OECD skills outlook 2023: Skills for a resilient green and digital transition. OECD Publishing. https://doi.org/10.1787/08785bba-en
Page, M. J., McKenzie, J. E., Bossuyt, P. M., Boutron, I., Hoffmann, T. C., Mulrow, C. D., et al. (2021). The PRISMA 2020 statement: An updated guideline for reporting systematic reviews. The BMJ, 372, n71. https://doi.org/10.1136/bmj.n71
Page, M. J., McKenzie, J. E., Bossuyt, P. M., Boutron, I., Hoffmann, T. C., Mulrow, C. D., et al. (2021). The PRISMA 2020 statement: An updated guideline for reporting systematic reviews. The BMJ, 372, n71. https://doi.org/10.1136/bmj.n71
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
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
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
Snyder, H. (2019). Literature review as a research methodology: An overview and guidelines. Journal of Business Research, 104, 333–339. https://doi.org/10.1016/j.jbusres.2019.07.039
Snyder, H. (2019). Literature review as a research methodology: An overview and guidelines. Journal of Business Research, 104, 333–339. https://doi.org/10.1016/j.jbusres.2019.07.039
Teece, D. J. (2018). Business models and dynamic capabilities. Long Range Planning, 51(1), 40–49. https://doi.org/10.1016/j.lrp.2017.06.007
Teece, D. J. (2018). Business models and dynamic capabilities. Long Range Planning, 51(1), 40–49. https://doi.org/10.1016/j.lrp.2017.06.007
Teece, D. J. (2018). Business models and dynamic capabilities. Long Range Planning, 51(1), 40–49. https://doi.org/10.1016/j.lrp.2017.06.007
Thomas, J., & Harden, A. (2008). Methods for the thematic synthesis of qualitative research in systematic reviews. BMC Medical Research Methodology, 8, Article 45. https://doi.org/10.1186/1471-2288-8-45
World Economic Forum. (2025). The future of jobs report 2025.
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