Artificial intelligence adoption in technical-vocational higher education: employability and workforce policy implications

Purpose This study investigated students' experiences of artificial intelligence (AI) adoption in Technical-Vocational Higher Education (TVHE) in Jolo, Sulu, Philippines, examining its implications for learning, employability, and institutional readiness. Design/methodology/approach Using a qualitative phenomenological design, semi-structured interviews were conducted with fifteen purposively selected TVHE students. Data were analyzed through Braun and Clarke's reflexive thematic analysis, interpreted using the Technology Acceptance Model, Human Capital Theory, and Digital Governance Theory. Findings Students perceived AI as a continuously available learning scaffold that supported academic learning, practical-skills preparation, and employability readiness, while expressing concerns about information reliability and over-reliance. Effective AI adoption was perceived to require institutional readiness, including infrastructure, AI-literacy training, and ethical governance. Research limitations/implications This study advances AI-in-education research by conceptualizing AI readiness as a multidimensional construct integrating technical, cognitive, and institutional dimensions rather than technology adoption alone. It also extends research on AI in higher education by foregrounding TVHE students' lived experiences in a resource-constrained context, highlighting the influence of governance and contextual conditions on AI adoption. Furthermore, the proposed Integrated AI-TVHE Transformation Model provides a conceptual foundation for future empirical studies examining the relationships among learner acceptance, human capital development, institutional readiness, and workforce preparedness across diverse educational settings. Practical implications The findings provide practical guidance for Technical-Vocational Higher Education (TVHE) institutions, educators, curriculum developers, and policymakers seeking to integrate artificial intelligence (AI) responsibly into vocational education. Institutions should embed AI literacy across vocational curricula, strengthen faculty capacity through continuous professional development, and establish ethical AI governance policies that promote responsible use and academic integrity. Policymakers should prioritize affordable, high-impact investments in digital infrastructure, AI literacy initiatives, and industry partnerships to improve institutional readiness and align vocational education with evolving workforce demands. These measures can enhance graduates' employability, digital competence, and lifelong learning in AI-enabled workplaces. Originality/value The study integrates TAM, Human Capital Theory, and a Digital Governance perspective to develop a context-specific interpretation of AI adoption in TVHE. It conceptualizes readiness across learner acceptance, hybrid digital-vocational capability development, and institutional enablement, while contributing student-centered evidence from a geographically isolated and resource-constrained setting.