Artificial Intelligence (AI) is not merely another technological trend for Technical and Vocational Education and Training (TVET); it challenges some of its foundational assumptions. As AI reshapes occupational profiles and production processes, TVET systems are compelled to reconsider what constitutes vocational competence, how skills are assessed, and who benefits from technological change. It is influencing changing skill demands, driving curriculum transformation, and redefining approaches to teaching, learning, and assessment. As a result, AI is becoming an increasingly influential force in the way vocational education is designed, implemented, and experienced. This issue aims to examine the dynamic relationship between AI and TVET and to highlight emerging developments at this critical intersection.
The contributions in this issue demonstrate that AI integration in TVET is neither linear nor uniform. Instead, it unfolds across unequal infrastructures, diverse institutional cultures, and contrasting pedagogical traditions. The tension between technological innovation and structural constraint emerges as a recurring theme throughout the issue.
Issue 26
The Impact of Artificial Intelligence (AI) on Technical and Vocational Education and Training (TVET)
About TVET@Asia
TVET@Asia is an open content online journal for scientists and practitioners in the field of Technical and Vocational Education and Training (TVET) and Vocational Teacher Education (VTE) in the East and Southeast- Asian region.
Its main purpose is to provide access to peer reviewed papers and thus to enhance the dissemination of relevant content and the initiation of open discussions within the TVET community.
Impact of equity, inclusiveness, and digital divide on Artificial Intelligence adoption in Technical and Vocational Education and Training Institutions in Africa. A case of Zimbabwe
This study examines the challenges and opportunities presented by equity, inclusiveness, and the digital divide in the adoption of Artificial Intelligence (AI) within Technical and Vocational Education and Training (TVET) institutions in Zimbabwe. The study adopted mixed methods design, employing quantitative surveys to map infrastructural and device equity disparities (the digital divide) and qualitative critical ethnography. It used a sample size totalling 5 TVET institutions and 50 key informants. Quantitative data was analysed using frequency distributions to map the prevalence of infrastructural disparities and regression analysis to determine the statistical significance of access gaps related to socio-economic factors. Qualitative data was analysed using thematic analysis to identify, analyse, and report patterns (themes) within the interview and focus group data. Findings revealed significant disparities in AI readiness, with urban institutions generally better equipped. Challenges such as limited funding and high internet costs disproportionately affect marginalized groups. The study concludes that while AI has transformative potential for TVET, equitable adoption is obstructed by systemic inequities and the digital divide. Key recommendations include investing in digital infrastructure, creating national AI strategies for TVET, integrating digital literacy into curricula, and fostering public-private partnerships for AI training.
When Crisis Drives Innovation: How VET Leaders Interpret AI as Response to Workforce Challenges and Status Decline
Across vocational education institutions in England and Australia, educators are adopting artificial intelligence (AI) out of necessity rather than through policy directive. Staff managing 47-hour marking loads within 36.25 paid hours have discovered that AI tools can reduce administrative time by up to 80%, even when their use operates beyond formal policy frameworks. This study utilises uncertainty reduction theory to explore how vocational education and training (VET) leaders engage with proactive (anticipating future possibilities) and retroactive (interpreting observed behaviours) processes to navigate technological disruption. Through qualitative semi-structured interviews, the research investigates how technological uncertainty intersects with broader sector challenges, including recruitment, workload, and professional recognition. Analysis reveals leaders managing complex information flows about technology adoption occurring outside formal channels. With teaching staff age averaging 55–57 years, leaders describe facilitating information exchange between generations, with some educators lacking fundamental computer skills whilst others bring industry-derived technological confidence. VET administrators recognise educator resilience emerging through crisis-driven technological adaptations, despite persistent structural constraints. The research demonstrates organisational uncertainty management through recursive cycles linking observation with planning. Successfully integrating AI requires balancing informal experimentation with formal compliance, protecting staff whilst maintaining regulatory adherence within risk-averse cultures. Addressing technological uncertainty and structural workforce challenges must occur simultaneously.
Readiness of TVET Educators for AI-Supported Instruction: A Multi-Dimensional Assessment of Competencies and Pedagogical Adaption
Artificial intelligence (AI) is transforming teaching and learning in technical and vocational education and training (TVET), yet educators’ readiness for AI-supported instruction remains underexplored in developing contexts. This study assessed the levels and interrelationships of AI readiness, digital literacy, pedagogical adaptability, perception of AI, and attitudinal competencies among TVET educators, as well as differences across selected demographic variables. A cross-sectional survey design was adopted, involving 416 university-based TVET educators. Data were analysed using descriptive statistics, ANOVA, and correlation techniques. Findings revealed moderate levels of AI readiness and digital literacy, alongside high levels of pedagogical adaptability, perception of AI, and attitudinal competencies. Educators demonstrated strong foundational competencies but limited engagement with advanced AI-enabled instructional practices. Significant differences were observed in pedagogical adaptability across age groups, while attitudinal competencies were highest among educators with six to ten years of teaching experience. The competency dimensions were positively and significantly interrelated, indicating a coherent readiness ecosystem. Overall, while TVET educators exhibit favourable dispositions towards AI, their readiness for AI-supported instruction is still emerging, highlighting the need for structured professional development, improved digital infrastructure, and institution-wide AI integration frameworks.
Empowering Adult Educators’ Artificial Intelligence Competence: Current Understanding and Strategies for Future Directions in Brunei
The rapid emergence of artificial intelligence (AI) is transforming global industries and labour markets at an unprecedented rate, making it essential to fundamentally shift technical and vocational education and training (TVET) to equip the future-proof workforce with the essential AI competencies it needs. This shift has significant implications for TVET educators, who must be competent in integrating AI into their teaching and learning processes. This chapter draws on data from an international study examining the current landscape and future trends of adult educators’ practice and perceptions on AI. Whilst the study was conducted across multiple countries, this chapter focuses on findings from Brunei, situating it within broader discourses on AI in adult education. An online survey was conducted between June and August 2024. A total of 118 respondents working across the higher education and TVET institutions completed the survey in Brunei. This survey was used to examine the current landscape and future trends in adult educators’ practice and perceptions of AI in higher education and adult education contexts. Based on the findings, the chapter proposes a multi-layered strategy to empower adult educators, including TVET educators, that embeds AI literacy into their professional learning within a broader digital competence framework. This strategy repositions TVET educators as critical practitioners capable of mediating between AI and pedagogy to ensure AI adoption strengthens, rather than undermines, equity and learner agency. The chapter concludes by advocating for systemic professional learning, communities of practice, and policies that recognise AI competence as central to TVET educator professionalism.
Integration of AI into Art & Design TVET Curricula: Expert Perspectives on Strategies and Implications for Pakistan
The current study is a qualitative research examining the urgent need to consider utilizing Artificial Intelligence (AI) technologies in Technical and Vocational Education and Training (TVET) curricula and training programs in different Art and Design courses. Given that AI is rapidly changing the creative and technical sectors, TVET systems should keep up with it to provide graduates with the appropriate skills. A group of 12 informants participated in a focus group discussion (FGD), including specialists in five significant areas of the TVET: fashion design, graphic design, textile, interior design, and digital technology. During the FGD session, the discussions on the strategies to be used, opportunities, and challenges involved in integrating AI in the selected vocational training areas were thoroughly discussed. The results indicate that the most effective integration has been regarded as important in keeping TVET relevant. The respondents also found opportunity areas that should be developed in their curriculum, such as developing the skills to be more productive, to develop innovation, and to teach hybrid skill sets that could combine the technical AI skills with creative and critical thinking. Nevertheless, it was observed that there were immense obstacles that included educator training, ethical issues, and revision of old curricula. The paper concludes that a proactive and strategic approach toward AI integration, with outlined learning outcomes, ongoing instructional growth, and adaptable instructions, is needed to match the results of TVET and the needs of the digital economy in the South Asian market, in particular, Pakistan.
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