Abstract
Artificial intelligence (AI) is transforming workplaces by enhancing learning, skills development and labor market preparation, prompting UNESCO to forecast that many low-skilled, repetitive tasks in Technical and Vocational Education and Training (TVET) will be automated. Integrating AI into TVET is thus essential for boosting economic and human resource competitiveness. As a global leader in semiconductors, Chinese Taiwan has advanced AI through the “Taiwan AI Action Plan” since 2018 to foster talent and collaborations to position itself as an AI hub. Nevertheless, Hong Kong's Vocational and Professional Education and Training (VPET) initiative continues to emphasize educational articulation over AI talent needs, lagging behind other Asian Tigers. Hence, this paper aims to explore AI-TVET linkages amid industrialization evolution from Industry 4.0 to 6.0, reviews Chinese Taiwan's policies across governance, partnerships and education, and offers lessons for Hong Kong's VPET to prepare for future disruptions.
Keywords
Introduction
Artificial intelligence (AI) is reshaping the future workplace ecology by enhancing learning experiences, improving skills development, and preparing students for rapidly evolving labor markets. UNESCO (2023) predicts that many low-skilled, repetitive tasks traditionally trained through Technical and Vocational Education and Training (TVET) will be automated or replaced by industrial robots. This makes the integration of AI into TVET not merely optional, but essential for sustaining relevance, quality, and competitiveness (UNESCO, 2022).
Chinese Taiwan holds a leading position in the global technology industry, commanding approximately 46% of the foundry market share and 51% in semiconductor assembly and testing in 2023 (TrendForce, 2023). Chinese Taiwan also leads globally in integrated circuit foundry, packaging, and testing services, representing its vital and leading role in the global technology industry. While Chinese Taiwan has experienced robust growth in AI, the increasing maturity of AI is reshaping future services and products across industries. Since 2018, the Taiwan authorities have actively promoted AI development through the “Taiwan AI Action Plan” (Executive Yuan, 2018). This initiative focuses on cultivating AI expertise and transforming both public and private sectors, with the ambitious goal of positioning Chinese Taiwan as a global leader in AI technology and one of the world's foremost smart regions by nurturing AI talent and facilitating TVET development. Consequently, collaboration among Chinese Taiwan's universities, research institutions, emerging startups, and established companies on diverse AI projects has become crucial. These efforts have played a key role in transforming industries and attracting local and international firms to establish research and development (R&D) and innovation hubs in the Asia-Pacific region, thereby strengthening the entire TVET system (Hu et al., 2018). In contrast, the Government of Hong Kong Special Administrative Region (HKSARG) has invested heavily in recent years to promote AI industry development and R&D applications, yet it lacks comprehensive policy planning for AI talent cultivation and reindustrialization policy planning with STEM industries (Chun et al., 2022). Hong Kong's major TVET initiative—Vocational and Professional Education and Training (VPET)—continues to emphasize articulation from secondary to tertiary education rather than addressing talent demands from the AI sector. This has caused Hong Kong's AI industry competitiveness to lag behind other Four Asian Tigers.
Policy borrowing in comparative education involves the deliberate, selective adoption and adaptation of policies from one context to another, rather than wholesale transplantation (Phillips & Ochs, 2003; Steiner-Khamsi, 2004). Against this backdrop, Chinese Taiwan will serve as a “lender” exemplar due to its coherent, sustained AI-TVET integration within a manufacturing-heavy industrial base, while Hong Kong acts as a “borrower” seeking to enhance VPET amid a service-dominated economy and fragmented AI governance. In addition, this paper will also outline the conceptual linkage between AI and TVET within the context of recent industrialization evolutions. It is hoped that this selective policy borrowing from Chinese Taiwan can help Hong Kong build sustainable partnerships, prevent skill mismatches under Industry 6.0—an era of “ubiquitous, customer-driven, virtualized, antifragile manufacturing” (Annanperä et al., 2021), and foster collaborative innovation ecosystems attuned to its unique strengths. Meanwhile, revolutionizing TVET practices can prepare students not only for current labor markets but also for future disruptions.
Understanding Conceptual Linkage Between TVET and AI Within Newest Industrialization Evolution (Industry 4.0 to Industry 6.0) Context
The critical importance of in line TVET systems with the evolving demands of modern industries, with a particular focus on the transformative role of AI is reshaping vocational education curricula. The immense potential of AI not only enhances learning outcomes and personalizes educational experiences within the vocational training context but also provides the opportunities and the inherent challenges associated with the integration of AI into vocational education. The integration process includes examining the development of relevant curricula, the implementation of personalized learning approaches enabled by AI, and the crucial ethical considerations that must be addressed to ensure responsible and equitable use of AI in educational settings.
Connection Between TVET and AI
TVET plays an essential role in equipping individuals with practical skills for the workforce, particularly in an era dominated by rapid technological advancements. The integration of AI into TVET systems represents a transformative opportunity to enhance learning outcomes, bridge skill gaps, and prepare learners for future job markets. However, the integration encompasses multifaceted strategies and considerations, including equal access, workforce readiness, collaboration, infrastructure, teacher training, and research and policy (OECD, 2024). These strategies and considerations are interconnected and require a holistic approach to ensure inclusive and effective implementation. AI's potential in TVET lies in its ability to personalize education, automate routine tasks, and simulate real-world scenarios, thereby making training more efficient and responsive to industry needs (McKinsey & Company, 2023). For instance, AI-driven tools such as adaptive learning platforms and virtual simulations can tailor educational experiences to individual learner needs, improving engagement and retention. However, successful integration requires addressing challenges like digital divides, ethical concerns, and educator preparedness. Ahmad et al. (2025) indicate that AI can significantly boost technical proficiency and industry readiness, but only when implemented with careful consideration of contextual factors. In governance perspective, policies and frameworks from organizations like UNESCO and the European Union (EU) place the importance of ethical AI deployment to promote equity and inclusion (UNESCO-UNEVOC, 2023). The EU AI Act, for example, classifies AI in education as high-risk, mandating transparency and human oversight to mitigate biases and ensure data protection (European Union, 2024). Similarly, national strategies in countries like Germany and France focus on human-centric AI development, though gaps in vocational teacher training persist (Tegelbeckers et al., 2025).
AI also enables TVET that extends far beyond mere technological augmentation. In addition to enhancing pedagogical approaches and personalizing learning experiences, AI addresses critical challenges such as skill obsolescence and misalignment with industry needs. For example, AI-driven simulators and intelligent tutoring systems have improved hands-on skills and student engagement in vocational fields like welding and robotics (Zary & Zary, 2025). Empirical studies indicate that AI boosts technical proficiency and industry readiness, although implementation is hindered by infrastructure limitations, limited digital fluency among teachers, and inadequate training (Deckker & Sumanasekara, 2025; Parker et al., 2024). These barriers are compounded by fears of job displacement, disruptions to traditional pedagogical structures, the absence of clear institutional policies, and the risk of over-reliance on AI (Sutedjo et al., 2025). In response, education systems must prioritize the development of AI literacy—a comprehensive set of competencies encompassing critical thinking, adaptability, and socio-technical awareness, rather than purely technical skills (Palmquist et al., 2025). Embedding AI in TVET presents both challenges and opportunities to move beyond conventional hands-on methods toward pedagogies that integrate digital tools with human-centered teaching (ILO, 2024; UNESCO, 2023). The sector continues to grapple with broader digital transformation issues, including low information and communication technology (ICT) integration in areas such as monitoring, evaluation, career guidance, assessment, and teacher training. Promising initiatives include industry-public sector exchange platforms and shared training programs, which represent regional best practices for bringing AI into classrooms. Ultimately, AI has the potential to revolutionize skill-based education in TVET, provided it is guided by coherent ethical policies, robust teacher training, and equitable access to digital infrastructure. Apparently, integration must always enhance, rather than undermine, human-centered vocational instruction.
From Industry 4.0 to Industry 6.0: Implication for TVET
The global industrial landscape is undergoing profound transformation, driven by technological convergence, socio-economic disruptions, and environmental pressures. The trajectory from Industry 4.0 to the envisioned Industry 6.0 signals a fundamental reconfiguration of value creation and governance (Chourasia et al., 2022). Industry 4.0, emerging in the 2010s, introduced smart and connected systems that integrated IoT, AI, and cyber-physical technologies to enable real-time monitoring, autonomous decision-making, and efficiency-driven automation. Industry 5.0, formally articulated by the European Commission in 2023, builds on this foundation by emphasizing human-centric collaboration. Advanced AI enhances productivity and resilience while embedding sustainability and inclusivity into industrial systems. Generative AI expands opportunities for innovation but also raises challenges around ethics, creativity, and governance. Looking ahead, Industry 6.0 envisions regenerative ecosystems that integrate emotional AI, ethical reasoning, and bio-cybernetic systems. Breakthroughs in quantum computing, neuroadaptive interfaces, and Human Digital Twins will underpin intelligent, self-regulating systems designed to prioritize human well-being and planetary health (Gomaa, 2025).
These shifts carry significant implications for TVET. Traditional TVET systems, constrained by outdated curricula and rigid delivery methods, struggle to prepare learners for rapidly evolving industrial demands. In contrast, AI-driven TVET models offer dynamic solutions. Automated competency mapping and real-time content generation ensure curricula remain responsive to labor market needs (Becker et al., 2022). Adaptive platforms personalize learning pathways, while immersive tools such as simulations and virtual reality provide safe environments for skill practice. Continuous, data-driven assessment replaces periodic evaluations, enabling early identification of gaps and timely interventions. AI-powered student support systems extend guidance and accessibility, promoting inclusivity for diverse learners (Leong, 2025).
The outcomes of AI-enabled TVET are transformative. Personalized learning fosters higher skill proficiency, intelligent job-matching platforms improve placement rates, and reliance on digital resources reduces costs. Learner engagement is strengthened through interactive platforms, scalability is achieved via online delivery, and industry relevance is secured through continuous alignment with emerging trends. Collectively, these innovations position AI-driven TVET as a future-ready system that not only addresses the limitations of conventional approaches but also equips learners with adaptable, multidisciplinary skills essential for navigating Industry 4.0, 5.0, and ultimately 6.0 (Gomaa, 2025; Verma et al., 2025). By embedding adaptability, inclusivity, and ethical responsiveness into vocational education, AI-driven TVET becomes more than a mechanism for skill acquisition. It emerges as a strategic driver of resilience, innovation, and equity, ensuring workforce development remains echoed with both technological disruption and broader societal priorities.
Chinese Taiwan and Hong Kong, as compact, high-income Asian economies and members of the “Four Asian Tigers,” share historical, cultural, and geographic ties from rapid post-war industrialization. However, their economic structures and TVET systems differ markedly, requiring careful justification for policy learning. Chinese Taiwan's economy is manufacturing-dominant, with semiconductors and ICT hardware as pillars (holding ∼46% of global foundry share in 2023). This has enabled its deep AI integration into production, supply chains, and TVET curricula emphasizing hardware, chip design, and applied engineering. In contrast, Hong Kong has deindustrialized since the 1980s to 1990s, shifting to services, finance, real estate, and trade intermediation, with VPET historically focused on educational articulation, service-sector skills, and rebranding to counter vocational stigma rather than advanced manufacturing alignment. Moreover, such contextual differences mediate transferability. Chinese Taiwan's authority-led, multi-agency approach suits its manufacturing base but may not fit Hong Kong's market-driven, finance-centric and fragmented policy environment. Instead, selective policy borrowing, such as adapting cross-sector partnerships, talent targets, and interdisciplinary AI literacy that tailored to Hong Kong's financial strengths, research capacity, and mainland proximity, can enhance VPET's responsiveness to AI disruptions. Hence, the following section will adopt “policy borrowing” approach (Phillips & Ochs, 2003) to recognizes that lessons from Chinese Taiwan cannot be transplanted wholesale but filtered through local economic priorities, institutional legacies, and socio-cultural norms to enhance VPET's responsiveness to AI-driven disruptions in Hong Kong.
Overview of Chinese Taiwan's AI Policy Planning and TVET
Chinese Taiwan has strategically positioned AI as a cornerstone for its future economic growth and enhanced global competitiveness, recognizing its transformative capacity across various industries and within society (Chang & Hsiung, 2025). The region possesses several inherent advantages that make it a promising player in the AI sector, including a world-leading position in the manufacturing of ICT hardware, a dynamic ecosystem of small and medium-sized enterprises (SMEs), and a strong foundation of ICT-enabled innovation across diverse vertical industries. This established technological prowess provides fertile ground for the further development and application of AI technologies, while TVET is recognized as the critical need for a skilled workforce to realize its AI ambitions and an indispensable component in cultivating the necessary human capital (Tseng, 2025a). TVET institutions are tasked with the crucial role of equipping individuals with practical skills and vocational competencies that in line with the evolving demands of the AI-driven economy. The connection between overarching AI strategies and the capabilities fostered within the TVET system is therefore paramount for Chinese Taiwan's success in the global AI landscape.
AI Policy Framework in Chinese Taiwan: Contextualizing AI Ambitions and the Role of TVET
Taiwan authorities adopted a proactive stance in supporting the growth of its AI industry, implementing various policy measures and establishing corresponding legal frameworks to foster industrial advancement (Tseng & Chang, 2024). Several key policy documents outline Chinese Taiwan's strategic direction in AI (Table 1), including the “Digital Nation and Innovative Economic Development Plan” launched in 2016, the “Taiwan AI Action Plan” introduced in 2018, and the more recent “Taiwan AI Action Plan 2.0” spanning from 2023 to 2026 (Chang & Hsiung, 2025). These documents illustrate a sustained and evolving commitment to AI development over time. The all-embracing objectives of Chinese Taiwan's AI policy framework are multifaceted, encompassing the cultivation of a robust AI talent pool, the promotion of substantial industrial growth in the AI sector, the improvement of working conditions through AI applications, and the strengthening of Chinese Taiwan's technological influence in global markets. This comprehensive approach indicates a recognition that AI development must yield broad benefits across economic, social, and international spheres (Chang, 2024).
Key Objectives and Initiatives of Chinese Taiwan's AI Policy.
Chinese Taiwan's strategic priorities in AI include a strong emphasis on the development of AI chip technology and its application in various industries, the advancement of AI computing capabilities alongside the creation of a localized large-language model known as Trustworthy AI Dialog Engine (TAIDE), and the establishment of Chinese Taiwan as a prominent AI innovation hub. The development of TAIDE, tailored to Chinese Taiwan's data and languages, aims to leverage its existing leadership in the semiconductor industry and addresses specific industry needs. Furthermore, the creation of an AI innovation hub seeks to foster a dynamic ecosystem for research and development. To achieve these objectives, the authorities have launched key initiatives such as the “AI Talent Program,” which aims to cultivate and train thousands of professionals with expertise in AI, and the development of AI test fields and regulatory sandboxes designed to ease restrictions on innovative technologies and encourage experimentation (Lin & Yeh, 2024). These initiatives reflect a dual focus on building both the human capital and the enabling environment necessary for AI to flourish. Remarkably, the governance of AI policy in Chinese Taiwan involves a collaborative effort among several key authority agencies. The Chinese Taiwan's National Science and Technology Council (NSTC) plays a central role in formulating national science and technology policies, including those related to AI (EDUtech_talks, 2024). Chines Taiwan's digital affairs authority is responsible for promoting Chinese Taiwan's overall digital development, which includes AI, and has established the Artificial Intelligence Evaluation Centre (AIEC) to regulate the use of generative AI systems among authority agencies. Taiwan's education authority is primarily responsible for initiatives related to AI education and talent development programs across various educational levels. This multi-agency involvement underscores the cross-sectoral nature of AI policy and the necessity for effective coordination to ensure its successful implementation.
The Landscape of Chinese Taiwan's TVET
Chinese Taiwan's TVET system has historically played a pivotal role in facilitating economic development by consistently providing a skilled workforce essential for industrial expansion and technological advancement (Pan, 2016). This established system is widely recognized as a key factor contributing to Chinese Taiwan's economic success. The structure of Chinese Taiwan's TVET system encompasses both secondary and higher education levels (Table 2). The education affairs authority (2018) stated that the secondary vocational education includes programs offered in vocational high schools, specialized vocational divisions within general senior high schools, and vocational programs in comprehensive senior high schools. Higher vocational education is provided by junior colleges, technical colleges (also known as institutes of technology), and universities of science and technology. This dual-level structure offers multiple pathways for students to acquire vocational skills tailored to different career trajectories and educational aspirations.
Structure of Chinese Taiwan's TVET System.
Pan (2016) outlined that the primary objectives of Chinese Taiwan's TVET system are to equip students with practical skills and relevant knowledge that directly address the needs of various industries, to foster a spirit of innovation and problem-solving, and ultimately to enhance the employability of graduates. The emphasis on practical application ensures that graduates are well-prepared to enter the workforce and contribute effectively to their respective fields. The policy framework governing TVET in Chinese Taiwan is primarily based on the Technological and Vocational Education Act, enacted in 2015, along with various related guidelines issued by the education affairs authority (Technical and Vocational Education Act, 2019). This legal and regulatory framework provides the necessary structure and direction for the development and implementation of TVET programs across the region. Despite its historical success, Chinese Taiwan's TVET system faces several ongoing challenges. These include the imperative to continuously adapt to the rapid pace of technological changes, ensuring the consistent quality of teaching and learning across all institutions, and effectively addressing the evolving demands of the labor market in a dynamic global economy (Cheng, 2023; Yu & Hsu, 2003). Overcoming these challenges is crucial for maintaining the relevance and effectiveness of TVET in supporting Chinese Taiwan's future economic and technological goals.
Fostering Industry–University–Government Collaborative Partnerships in AI and TVET Sector
Taiwan authority actively encourages and facilitates partnerships among industry stakeholders, universities, and research institutions to accelerate the cultivation of AI talent and to promote the advancement and application of AI research (Tseng, 2025b). This emphasis on collaborative efforts reflects a recognition that a coordinated approach is essential for maximizing progress in the rapidly evolving field of AI (Table 3). One notable example of such collaboration is the “AI on Chip Taiwan Alliance,” which specifically aims to support the development of cutting-edge AI chip technology and to foster its application within various industry sectors (Tsai, 2024). This alliance leverages Chinese Taiwan's existing strengths in the semiconductor industry to drive innovation in this critical component of AI technology. Moreover, the digital affairs authority (MODA) plays a significant role in facilitating these collaborations by organizing networking events that bring together stakeholders from different sectors. Additionally, MODA (2025) provides crucial financial support to AI startups through initiatives such as the “Enhanced AI Startup Investment Program,” which allocates substantial funding to nurture the growth of the AI ecosystem. In the realm of education, the education affairs authority and various universities have jointly established the “Taiwan Artificial Intelligence College Alliance”. This alliance enables students to enroll in AI courses offered across different universities and to obtain recognized certifications in AI-related fields. The ambitious goal of this initiative is to equip over 10,000 students with essential AI expertise within the next three years, directly addressing the growing demand for AI professionals in Chinese Taiwan's technology industry.
Examples of Industry–University–Government Partnerships in AI.
Chinese Taiwan also fosters direct industry–university collaborations that focus on cultivating specialized AI and interdisciplinary talents while enhancing research and development capacity. These collaborations address a critical gap regarding universities often produce graduates with strong theoretical knowledge but limited practical experience, while industry requires professionals who can contribute immediately to projects. In order to echoing curricula with industry needs and involving students in real-world projects, these collaborations ensure that graduates acquire practical skills and are industry-ready. Objectives include training students in niche areas such as computer vision, robotics, and AI ethics, promoting interdisciplinary learning that integrates AI with business, healthcare, and social sciences, and enhancing R&D capacity through joint projects. The outcomes are evident in the form of industry-ready graduates, boosted research output, interdisciplinary innovation, and closer ties between academia and industry (Mou et al., 2018). These collaborations also contribute to economic competitiveness by ensuring that Chinese Taiwan's workforce and research ecosystem remain globally relevant. Their broader impact lies in maintaining continuous alignment between education and industry needs, ensuring that Chinese Taiwan's AI ecosystem is not only research-driven but also application-oriented, producing tangible economic and social benefits.
In sum, these four initiatives form a holistic strategy for advancing Chinese Taiwan's AI ecosystem. Each initiative addresses a different aspect of the AI landscape, including hardware innovation, talent cultivation, entrepreneurial ecosystem, and applied research. Their complementary strengths create synergies that reinforce one another. For example, graduates from the AI College Alliance feed into startups supported by the investment program, university research informs AI chip development, startups drive applications that utilize AI chips, and authority policies ensure coordination across these efforts (Lin, 2024; Overseas Community Affairs Council, 2025). Eventually, these partnerships strengthen Chinese Taiwan's competitiveness in the global AI race by leveraging its semiconductor strengths, cultivating talent, supporting startups, and aligning academia with industry (Office of Academic Affairs, Soochow University, 2025). At the same time, they face challenges such as coordination complexity, global competition, talent retention, and scalability. Addressing these challenges will be critical for sustaining momentum beyond initial targets and ensuring long-term success.
Overview of Hong Kong's AI Policy Planning and TVET
VPET and AI Policy in Hong Kong
In contrast to Chinese Taiwan's integrated approach, Hong Kong's VPET and AI policy landscape exhibits a more fragmented structure. VPET in Hong Kong has evolved significantly to meet the city's changing social and economic needs, positioning itself as a parallel pathway to traditional academic education and aiming to nurture high-quality talent with applied knowledge and skills for economic and industrial development. The roots of vocational education in Hong Kong date back to 1905 with the establishment of the first Vocational Education and Training (VET) college (Waters, 2000). A major milestone was the creation of the Vocational Training Council (VTC) in 1982, which now comprises 14 member institutions offering a broad spectrum of programs tailored to industry skill demands. In response to persistent perceptions of inferiority associated with vocational education in Chinese societies (Lau & Kan, 2013; Yau et al., 2018), the government initiative rebranded VET as VPET in 2015, following recommendations from the Task Force on Promotion of Vocational Education. The recommendations included three-pronged strategy focused on rebranding, strengthening promotion, and encouraging youth participation (Education Bureau, 2015). Entering the twenty-first century, VPET has further modernized through the introduction of qualifications frameworks, deeper industry collaboration, and the establishment of new institutions to address emerging sectors, such as the Hong Kong Institute of Information Technology in 2023. Recently, the University of Applied Sciences (UAS) model has elevated VPET to the university degree level, providing young people with an alternative route to higher education and professional success (Hong Kong Special Administrative Region Government, 2023). With growing recognition of the value of VPET, the integration of AI into vocational education is also underway, further enhancing the relevance and future-readiness of Hong Kong's workforce.
Incorporating AI in the Education System
The launch of the Innovation and Technology Development Blueprint (ITDB) in 2022 has significantly accelerated the advancement of AI and data science within Hong Kong's VPET sector (Innovation, Technology and Industry Bureau, 2022). In response, the VTC established the Hong Kong Institute of Information Technology (HKIIT) in 2024, which specializes in AI and other technology-related programs. HKIIT now offers a range of higher diploma programs and specialized courses in areas such as applied AI, data science, smart technology, and mobile applications development, providing students with up-to-date skills that meet evolving industry demands. Other VPET providers have also introduced similar offerings, ensuring that graduates are well-equipped to contribute to Hong Kong's growing innovation and technology ecosystem (Innovation, Technology and Industry Bureau, 2025).
VPET and AI in Secondary Education
In recent years, the government has actively promoted VPET at the secondary school level by offering Applied Learning (ApL) courses as elective subjects for senior secondary students. ApL serves as an important introduction to VPET, enabling students to explore both theoretical concepts and practical skills across a range of professional and vocational fields. To keep pace with social, economic, and technological advancements, the Education Bureau has expanded and refined the ApL curriculum, increasing the number of courses from 41 in the 2020–22 cohort to 55 for the 2025–27 cohort (Legislative Council of the Hong Kong Special Administrative Region, 2024). The latest offerings include more courses in emerging areas such as AI and information technology, with subjects like “AI and Robotics,” “Digital Construction,” and “Tech Basics” (Education Bureau, 2025). These enhancements provide secondary school students with broader opportunities to gain early exposure to VPET, better preparing them for further studies and future careers in rapidly evolving industries.
VPET and AI in Post-Secondary Education
The HKIIT is dedicated to collaborating closely with the IT sector to develop a curriculum echoed with industry needs. Through partnerships with industry, it integrates real-world expertise into its programs by inviting professionals to deliver lectures, share insights, offer internships, and provide industry certification training. The institute also facilitates professional development by arranging training for its academic staff through industry partners, while offering in-service training courses to both IT and non-IT professionals to help raise digital literacy across Hong Kong. HKIIT delivers both pre-employment training for young people and ongoing professional development for those already in the workforce.
For pre-employment training, HKIIT admitted its first group of students in the 2024/25 academic year. These programs focus on two key areas: Information and Communications Technology, and Multimedia and Entertainment Technology, equipping students with essential IT expertise and practical skills for the industry.
Its “SkillsUP” initiative offers tailored reskilling and upskilling programs for working professional, covering areas such as Web and Mobile Application Development, Artificial Intelligence and Machine Learning, Cloud Computing, and Information and Network Security (Vocational Training Council, 2024). The institute also provides a wide array of continuing education courses in various formats and levels to cater to the diverse learning needs of Hong Kong residents. Besides, to address the growing demand for talent in the Greater Bay Area (GBA), the Technological and Higher Education Institute of Hong Kong (THEi), a member institution of the Vocational Training Council (VTC), is collaborating with the Hong Kong General Chamber of Commerce (HKGCC) to develop applied bachelor's and master's degree programs in emerging technologies and industries. These programs will cover key areas such as the digital economy, AI, and Environment, Social and Governance (ESG), aiming to equip graduates with the practical skills and knowledge needed to support the region's high-quality development and enhance Hong Kong's competitiveness as an international financial and innovation hub (Vocational Training Council, 2024b).
Challenges of Linking AI into VPET
The shortage of qualified AI teaching staff significantly hinders the quality of AI education. A key issue is that many teachers lack the necessary digital competencies to effectively integrate AI into learning environments. As AI is still relatively new in educational contexts, teachers often do not possess the knowledge or confidence to use AI-powered educational applications to enhance their teaching, let alone to foster students’ own AI capabilities (Ng et al., 2023). However, traditional training alone may not be sufficient to keep pace with the fast-evolving AI landscape. One promising strategy is to enhance faculty-industry exchange by facilitating secondments for VPET instructors to work in AI firms. This approach allows educators to gain hands-on experience with the latest industry trends and technologies, ensuring they remain current and can bring real-world insights back to their teaching.
Alternatively, limited industry collaboration remains another obstacle for connecting AI into VPET in Hong Kong. In this connection, it is crucial for the government to actively engage AI-leading corporations and technology firms to participate in work-based training schemes, especially through a dual-track mode that combines classroom learning with real-world industry experience. To better prepare VPET institutions to echo with AI industry's needs, VPET program content shall be regularly updated to reflect the latest industry trends, technological advancements and practical skill requirements, so VPET graduates will get job-ready and more competitive in the rapidly evolving AI landscape. Likewise, these collaborations can go beyond internships and job placements. AI companies can co-develop curricula, provide guest lecturers and mentors, sponsor innovation labs, and offer access to proprietary tools and platforms for hands-on learning.
While Chinese Taiwan's coherent and forward-looking AI governance features sustained commitment through the AI Action Plan and 2.0 and integrates across multiple agencies to set up an effective strategic partnership, this multi-agency coordination safeguarding AI policy is not siloed but integrated across education, industry, and governance. Comparatively, Hong Kong exhibits a more fragmented approach. While the government has invested in AI research and development, there is no all-rounded policy framework that explicitly links VPET to AI talent cultivation or industrial alignment. The rebranding of vocational education into VPET in 2015 was a significant step in addressing cultural perceptions, but subsequent initiatives have remained focused on articulation pathways and institutional expansion. The establishment of the Alliance of UAS and the HKIIT are important milestones, yet they lack integration into a broader AI policy strategy. Even the HKSARG has launched ITDB, Smart City Blueprint for Hong Kong and Hong Kong Smart City Blueprint 2.0, unless there is an overarching policy implementation strategy, otherwise these blueprints become mere castles in the air. VPET may still risk functioning as a parallel track to academic education rather than as a dynamic system responsive to technological disruption. This fragmentation is further compounded by limited industry-university collaboration in AI adoption, leaving graduates with skills that may not fully match emerging labor market demands.
Discussion: How Hong Kong Can Learn From Chinese Taiwan to Ensure the VPET Future Vision?
Based on Chinese Taiwan's practices, it demonstrates the fruitfulness of establishing strong collaborative relationships between educational institutions and industry partners in the realm of TVET, given the government provides the largest flexibility for industries to initiate their AI innovations. This strategy not only ensures TVET graduates better prepare for the demands of the AI-driven job market and economic transformation, but cultivate versatile abilities and cross-disciplinary competencies among them to thrive in the evolving digital age (Cheng, 2023). Such experiences also lead us to consider how Hong Kong's VPET initiative should be further developed to equip students with a broader range of skills that complement the integration of AI in the workplace under Industry 6.0 era.
Strengthening Industry–University–Government Tripartite Collaboration to Build Up Sustainable Partnerships for VPET Sector
Chinese Taiwan has built a strong foundation for broader industry collaborations, with universities partnering with industry to cultivate specialized AI and interdisciplinary talent while enhancing R&D capacity. These partnerships ensure graduates to acquire industry-relevant skills—such as AI applications in manufacturing, healthcare, and smart systems—while boosting research capabilities and technology transfer. Such collaborations are embedded in the policies like the “Taiwan AI Action Plan 2.0” and investments through the NDF in promoting authority-industry partnerships. Universities will contribute cutting-edge research, while industries provide real-world challenges and funding in creating a virtuous cycle echoed with goals like building a “smart technology island” and global AI hub. In addition, the European Union's Centres of Vocational Excellence (EU CoVEs) offer another model. Effectively integrating AI into vocational training often requires resources and expertise beyond public systems alone, where private sector partners play a key role (Tegelbeckers et al., 2025). Collaborations with companies help keep curricula relevant and updated, provide technology accessibility, and develop new AI-driven educational tools through the partnership at the EU's Community of Practice for Centres of Vocational Excellence (CoP COVEs). Some CoVEs focus on digital manufacturing or smart agriculture, with companies supplying equipment, internships, and expertise for students learning AI applications (Tegelbeckers et al., 2025).
In contrast, while Hong Kong boasts world-class universities and research institutions, many VPET-related research outcomes fail to reach commercial application due to inadequate vocational technology transfer channels and weak industry linkages. The HKSARG should therefore leverage local universities’ basic research strengths to strengthen industry-university-government collaboration to build sustainable partnerships in the VPET sector (Lim, 2025). This would enhance technology commercialization and drive context-specific industrial development. On the one hand, the Government should optimize the “industry-university-government” through “Research, Academic and Industry Sectors One-plus (RAISe+) Scheme” to attract more institutional investment in university-affiliated technology startups (Federation of Hong Kong Industries (FHKI), 2025). It serves as a collaboration mechanism to encourage in-depth participation from all sectors in nurturing local VPET research talent and incubating STEAM-related startups. On the other hand, the Government can lead efforts to support leading enterprises in establishing joint R&D centers and talent training programs with local universities and VPET institutions (Lim, 2025).
Besides, SMEs—compared to large enterprises—have weaker market intelligence and fewer resources. The Government and professional organizations should introduce more supportive measures to help SMEs adapt to the AI era and leverage AI for business upgrading and transformation. Professional organizations, such as Federation of Hong Kong Industries and Hong Kong General Chamber of Commerce, can act as intermediaries showcasing specific AI technologies and products as well as matching suppliers with users (FHKI, 2025). Given that local startups and SMEs often face resource constraints and disadvantages in competitive bidding, Hong Kong could draw on the EU's CoVEs experience to establish VPET-led communities of practice with shared talent pools. The CoPs can focus on areas like digital manufacturing or smart agriculture, where companies provide equipment, internships, and expertise to let Hong Kong nurture abundant talent in AI and data science. This approach could also overcome the long-standing reluctance of industries and leading tech enterprises to initiate R&D collaborations with universities and VPET institutions to boost VPET development with AI applications.
Preventing Skill Mismatch under Industry 6.0 Context in Hong Kong: Enabling VPET to Nurture Collaborative Innovation Ecosystems for AI-based Economic and Societal Transformation
Enabling VPET to Nurture Collaborative Innovation Ecosystems for AI-Based Economic and Societal Transformation
Chinese Taiwan's overarching AI strategies, exemplified by the “Taiwan AI Action Plan 2.0,” explicitly recognize talent development as a fundamental pillar. This emphasis on cultivating AI expertise directly shapes priorities and directions in AI-related fields within the TVET system. The clearly identified goal of producing a substantial pool of AI talent to meet the growing demands of the technology industry serves as a key driver for various initiatives aimed at integrating AI education into vocational schools and colleges (National Science and Technology Council, 2019). Their industry urgency for skilled AI professionals emphasizes the importance of these educational efforts within the TVET framework. By equipping TVET graduates with the necessary AI literacies and competencies, Chinese Taiwan aims to create a workforce that is not only adept at utilizing AI but also capable of driving further technological advancements, contributing to overall economic competitiveness, fostering industrial innovation, and facilitating digital transformation across various sectors. In fact, Hong Kong Productivity Council (HKPC) and Hong Kong Institute of Economics and Business Strategy (HKIEBS) publish a report which aims to examine the development and status of the AI industry. The report highlights the dual hurdles of talent recruitment and data management as major obstacles to AI advancement in Hong Kong (HKPC and HKIEBS, 2024). 49% surveyed enterprises report difficulties in recruiting technical talent, and 41% point to a shortage of relevant talent within Hong Kong, resulting in a persistent skills gap. These statistics reveal a complex landscape where optimism coexists with structural challenges, while 45% of enterprises plan to expand their technical teams, many others remain cautious due to local talent scarcity (HKPC and HKIEBS, 2024). Meanwhile, according to the newest Secondary 6 Students’ Pathway Survey from Education Bureau (2024), only 16.6% of Secondary 6 graduates chose to pursue full-time VPET programs. This shows a significant talent shortage for VPET-related industries and reflects the mismatch between local education and industrial development needs falling behind with AI technological advancement. Thus, the HKSARG should nurture talents in AI and data science through VPET pathways because it is particularly important for VPET institutions to enhance their R&D capacity on AI technology, so they can better utilize their stronger connection to promote and transformation of various industries using AI.
In the era of Industry 6.0, dynamic, multi-stakeholder collaborative innovation ecosystems (CIEs) connect academia, industry, and government to co-create, test, and scale responsible innovations through living labs, open innovation platforms, and decentralized experimentation. These mechanisms foster inclusive participation, context-sensitive development, and continuous learning, accelerating scalable solutions tailored to socio-technical contexts (Gomaa, 2025). TVET also provides flexibility for AI industry engagement and private sector involvement, serving as vital drivers of innovation (Deckker & Sumanasekara, 2025; Idris et al., 2025). Despite the potential of advanced technologies like AI and data science, their adoption in TVET remains limited (Amdan et al., 2025; Rosyadi et al., 2023), necessitating strengthened collaboration between educational institutions and industry partners to deliver resources, training, and real-world applications synchronized with labor market needs (Bonde, 2024; Rajamanickam et al., 2024). Private actors are also pivotal because they are offering funding, AI-driven tools, and project-based experiences to enhance workforce readiness and employability. Without comprehensive multi-stakeholder efforts, digital innovation's transformative potential in TVET will remain unrealized.
In the Hong Kong context, as core institutions for VPET, UASs should proactively partner with AI-related industries such as smart manufacturing, industrial design, and testing to complete the VPET ladder and provide suitable pathways for students entering these sectors (FHKI, 2025). AI-industry enterprises should bolster support for UASs through applied research projects and curriculum optimization to cultivate technical professionals and reduce post-graduation skills gaps, encouraging UASs as CIE driver to accelerate responsible co-creation, contextualization, and diffusion of innovations via an Academia-Research-Investment mechanism. When industry partnerships, phased implementation, participatory design, and institutional leadership underpin an ecological model for AI adoption in TVET (Zary & Zary, 2025), this model emphasises the value of industry collaborations, leveraging TVET's strong employment links to enable authentic and relevant AI applications, particularly when employers actively participate in design and implementation (UNESCO-UNEVOC, 2023). Future VPET development therefore should prioritize these elements to bridge skills gaps and foster resilient, human-centric innovation to an emerging, speculative paradigm envisioning highly autonomous, intelligent, and sustainable systems under Industry 6.0 context.
Concluding Remarks
Chinese Taiwan's experience shows clear evidence that the successful integration of AI into TVET requires more than isolated investments in technology. It needs a coherent AI strategy, multi-agency governance, and sustained collaboration across industry, universities, and government. Notably, Chinese Taiwan has positioned itself as a regional leader in AI-driven workforce development to embed AI talent cultivation into overarching policy frameworks, fostering interdisciplinary partnerships, and echoing TVET curricula with industry needs. In comparison, Hong Kong's VPET initiative remains largely focused on articulation pathways and institutional expansion and restricted attention to AI-specific talent pipelines or industry alignment. Without a strategic policy blueprint implementation for AI integration with TVET, Hong Kong risks falling behind in the global race for competitiveness among the Four Asian Tigers. Hence, Hong Kong can enhance its standing by adopting three primary insights from Chinese Taiwan's strategy, framed through a policy borrowing lens: developing collaborative innovation ecosystems as a comprehensive, multi-sector AI policy structure that clearly connects VPET to broader innovation goals; enabling industry-academia-government collaborations to blend theoretical and transversal AI skills via co-efforted initiatives; and introducing focused talent cultivation programs. Selective adaptation, mindful of Hong Kong's service-led economy and policy fragmentation, will be essential to avoid uncritical transfer and maximize relevance (Morley, 2024). Through these adaptations, Hong Kong could elevate VPET from a lesser-regarded option to a forward-thinking framework that prepares students with versatile and cross-disciplinary abilities. In the end, embedding AI within VPET would not only boost job prospects but also act as a catalyst for economic resilience, creativity, and greater social equity (Vallès-Peris & Gil, 2025), helping to maintain the competitiveness of Hong Kong's labor force amid the shift from Industry 4.0 toward Industry 6.0.
Footnotes
Ethical Considerations
Ethical approval was not required for this study since no empirical studies were conducted, and no human data or participants were involved.
Funding
The authors received no financial support for the research, authorship, and/or publication of this article.
Declaration of Conflicting Interests
The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.