Abstract Digital technologies and artificial intelligence (AI) are reshaping transnational technical and vocational education and training (TVET) systems. This scoping review examines how digital and AI-enabled tools are adopted, governed, and experienced in cross-border vocational education. Drawing on peer-reviewed studies, policy analyses, and conference literature from 2020 to 2026, it synthesizes evidence on infrastructure, pedagogy, assessment, educator and learner readiness, institutional capacity, and key ethical and governance issues. Findings indicate that digital transformation in transnational TVET is uneven. Learning management systems, virtual classrooms, communication tools, and mobile learning applications form core cross-border delivery infrastructure. AI-enabled tools, such as adaptive learning, learning analytics, automated assessment, and simulation-based environments, are emerging but remain reliant on pedagogical alignment, competency-based assessment, sustained institutional support, and effective partnership arrangements. Across the literature, AI is positioned as an enabling component within broader vocational systems rather than a standalone solution. Key challenges include uneven digital infrastructure, variable educator capability, misaligned regulations, data governance concerns, and equity risks intensified by cross-border disparities. Evidence gaps persist in longitudinal and comparative studies, learner-centered research, and work on implementing ethical frameworks. A future research agenda emphasizes system-level evaluation of AI-enabled learning outcomes, cross-border quality assurance in digital assessment, partnership-based capacity building for educators, and inclusive implementation in low-resource contexts. Effective digital and AI integration in transnational TVET depends on institutional, pedagogical, and governance conditions.
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Sasan Rasi
Box Hill Institute
Box Hill Institute
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Sasan Rasi (Thu,) studied this question.
synapsesocial.com/papers/69fed090b9154b0b828779b9 — DOI: https://doi.org/10.1515/wvte-2026-0003