HRMARS - Artificial Intelligence (AI), as a phenomenon in education, is progressively considered as a revitalizing power, but little has been said about its application in Technical and Vocational Education and Training (TVET) despite the mounting pressure on institutions to meet the needs of Industry 4.0. This mini review is a synthesis of existing evidence that investigates the use of AI in teaching and learning, workforce development, as well as curriculum design. Defined keywords were used to search the Scopus as well as Google Scholar (August 2025) literature; it included studies related to AI in vocational education settings and excluded the grey or non-English literature. The results show that AI can substantially contribute to workforce preparedness by analyzing predictive skills gaps, micro-credentialing, as well as industry-oriented curricula; to teaching and learning by supporting adaptive platforms, intelligent tutoring, and simulations; alongside redesigning curriculum through flexible and responsive paths in alignment with changing labor markets. However, it remains highly constrained by other factors such as, the digital divide, unequal institution readiness, ethical and data privacy, as well as lack of longitudinal evidence regarding the long-term impact. These issues of conflicting technological innovation and human-related mentoring as well as threats of overdependence on automation are also found in other discourses. AI must be applied to the future in a way that is ethically and policy sound, scalable and fair, as well as as a hybrid that does not replace human teachers. Its applications include AI-based analysis and certification, industry education collaboration, the notions of lifetime learning, inclusiveness, as well as moral responsibility. As mentioned in this review, one must focus on the issues that are yet to be resolved and make use of the opportunities that are available so that the TVET systems can be modified in a manner that would enable them to become equitable, flexible, as well as responsive to the needs of the new workforce.
Rajamanickam et al. (2026) studied this question.