The legal governance of ai upskilling and reskilling: towards a new employer duty

Menezes Barreto Júnior, Joel and Hong León, Duliet and Perez Fernández, Jaime and Congo Mavambo, António Ramos and Domingas Chivango, Natalia Águeda joel.menezes@unic.co.ao, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED (2026) The legal governance of ai upskilling and reskilling: towards a new employer duty. Journal of Law and Epistemic Studies, 4 (e176). ISSN 3091-1575

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Abstract

This article examines whether the rapid adoption of artificial intelligence (AI) justifies a broader interpretation of employer responsibilities regarding continuous upskilling and reskilling. An interdisciplinary qualitative methodology was employed, combining doctrinal-comparative legal analysis with a systematic literature review conducted according to the PRISMA 2020 guidelines. Scientific evidence was collected from Scopus, Web of Science, ScienceDirect and SpringerLink, complemented by reports from the International Labour Organization (ILO), the Organisation for Economic Co-operation and Development (OECD) and the World Economic Forum (WEF). The findings indicate that AI-driven workforce transformation extends beyond technological innovation and significantly affects employability, requiring organisations to anticipate skills disruption through strategic workforce development. The study identifies a conceptual gap between labour law, strategic human resource management and corporate governance concerning employer responsibility for workforce capability development. To address this gap, it proposes the AI Employability Governance Framework (AEGF), an original model integrating strategic workforce foresight, continuous upskilling, reskilling pathways, shared employer responsibility, labour rights protection and sustainable employability. The framework contributes to the emerging debate on responsible AI governance by providing a conceptual foundation for more inclusive, resilient and legally informed models of workforce transformation.

Item Type: Article
Uncontrolled Keywords: artificial intelligence, upskilling, reskilling, labour law, human resource management
Subjects: Subjects > Social Sciences
Divisions: Universidad Internacional do Cuanza > Research > Articles and books
Depositing User: Sr Bibliotecario
Date Deposited: 13 Jul 2026 07:38
Last Modified: 13 Jul 2026 07:38
URI: https://repositorio.funiber.org/id/eprint/28709

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