Artificial intelligence (AI) is rapidly transforming labor markets and skill demands, compelling vocational education and training (VET) systems worldwide to adapt. Existing studies focus on AI's technical or curricular impacts but lack a systemic analysis of how it reshapes stakeholder dynamics within the VET ecosystem. Drawing on stakeholder theory, this study employs a mixed-methods approach, combining systematic literature review, comparative case studies of Germany, Singapore, and China, and qualitative analysis of 42 policy documents. AI exerts asymmetric effects across stakeholders, elevating employer influence, intensifying learner urgency, challenging educator roles, and straining government oversight, while simultaneously fostering new governance models such as data consortia, modular credentials, and AI-enhanced apprenticeships. The paper proposes a dynamic stakeholder-based framework for understanding and guiding AI-driven VET transformation, offering practical strategies for equitable and resilient skills development in the digital age.
Gan Jie (Wed,) studied this question.