Responsible Artificial Intelligence for Managing Vocational Certificate Education in Thailand

Artificial intelligence (AI) is entering vocational education at the same time that vocational institutions are under pressure to respond faster to changing occupations, improve student support, demonstrate quality, and use limited resources more effectively. For Thailand’s Vocational Certificate (Prakatniyabat Wichachip: PWC) level, however, adoption cannot be treated as a generic digital-transformation project. PWC programmes serve upper-secondary learners across highly diverse occupational fields; many learners are minors, and a substantial proportion of learning is practical, safety-sensitive, or connected to workplaces. This article develops a context-specific framework for the responsible use of AI in the management of Thai PWC education. It uses a structured integrative review and policy analysis of Thai legal and policy documents, international standards and guidance, and peer-reviewed research, with sources reviewed through 30 July 2026. The analysis identifies seven management domains in which AI may add value: strategic intelligence, curriculum and occupational alignment, student access and support, resource operations, work-based learning, assessment and quality assurance, and administrative knowledge management. It also identifies six cross-cutting risk clusters: child rights and privacy; bias and exclusion; validity and reliability; erosion of human agency; academic and cognitive integrity; and cybersecurity, vendor, and sustainability risks. The article proposes a Responsible AI Management Framework for Thai PWC Institutions comprising seven principles, four risk tiers, seven lifecycle gates, a multilevel accountability architecture, and a phased implementation roadmap. The central argument is that AI should augment—never displace—professional and collective judgement in decisions that affect admission, progression, assessment, discipline, placement, or learner welfare. Readiness should therefore be demonstrated through governance, data stewardship, staff capability, impact assessment, contestability, and evidence of educational value, rather than through tool acquisition. The framework offers actionable guidance for the Office of the Vocational Education Commission, colleges, quality-assurance bodies, employers, and researchers, while establishing a research agenda for locally validated, equitable, and child-centred AI use in Thai vocational education.