Can Vocational Education Be the Frontline for AI Literacy?

“We need to start with the basics: there is a lot of hype and mystery around these technologies, which can act against us in a number of ways. First, it makes the technology seem scary or unapproachable for a lot of educators. They might dismiss it because of the hype, or because they feel overwhelmed with the pace of change.”

Leon Furze, PhD at Deakin University, Generative Artificial Intelligence

Australia’s Vocational Education and Training (VET) sector is a sleeping giant in the artificial intelligence literacy challenge. Each year, five million students pass through VET programs spanning everything from traditional trades like building, electrical, and plumbing to allied health, childcare, education, creative arts, and emerging digital technologies. Yet this massive educational pipeline, arguably the most directly connected to Australia’s workforce, has been largely absent from conversations about preparing workers for an AI-driven economy.

The scale of opportunity becomes even clearer when considering that roughly two-thirds of Australians work in small and medium enterprises. These are the time-poor business owners and employees who, as consultant and PhD candidate Leon Furze puts it, are “working from six o’clock in the morning to 10 o’clock at night, carrying out the roles of half-a-dozen people by ourselves.” They desperately need AI literacy but lack the luxury of time to develop it independently.

The challenge is both urgent and complex. While traditional educational sectors grapple with AI’s implications—universities debating academic integrity and schools struggling with assessment validity—VET faces a different set of questions. How can trainers be upskilled quickly enough to guide students? What role should VET’s uniquely flexible assessment structures play in responsibly adopting AI? And perhaps most critically, how can the sector ensure equity and quality as multimodal AI reshapes the future of work?

Yet VET also holds unique advantages. Its practical focus, direct industry connections, and diverse assessment methods position it not as a follower in the AI literacy race, but as a potential leader. Unlike other educational sectors, VET’s students are learning skills they’ll use immediately in workplaces where AI is already being integrated into everyday tools and processes.

To better understand how vocational education might become the frontline for AI literacy in Australia, we spoke with Leon Furze, a consultant, bestselling author, and PhD candidate at Deakin University with over fifteen years’ experience in education, who has taught VET courses and spent four years supporting VET providers in understanding artificial intelligence.

Leon Furze is an international consultant, author, and speaker with over fifteen years of experience in secondary and tertiary education and leadership. Furze is studying his PhD at Deakin University in the implications of Generative Artificial Intelligence on writing instruction and education.

Furze has held roles at multiple levels of school and board leadership. He has held positions as a non-executive director on the boards of Young Change Agents and Reframing Autism, and the Council for the Victorian Association for the Teaching of English.

Furze completed his master of education at the University of Melbourne in 2016 with a focus on student wellbeing, leading schools through change, and linking education systems and communities. He has published dozens of books, articles, and courses, with his most recent publications, Practical Reading Strategies and Practical Writing Strategies, reaching an international audience.

Furze presents at state and national conferences and runs online and face-to-face professional learning for schools, individuals, and businesses. Through consultancy and advisory work, he helps educators from K-12 to tertiary to understand the implications of Generative Artificial Intelligence in education.

The ambitious vision of VET leading AI literacy faces one fundamental prerequisite: trainers themselves must understand the technology. “All of this is hypothetical if the trainers themselves don’t understand the technology,” Furze emphasizes, highlighting the critical foundation that must be established before any meaningful student instruction can occur.

The challenge extends beyond simple unfamiliarity. Many educators approach AI with a mixture of apprehension and overwhelm, reactions that Furze attributes to widespread misconceptions about the technology’s nature and complexity. “We need to start with the basics: there is a lot of hype and mystery around these technologies, which can act against us in a number of ways. First, it makes the technology seem scary or unapproachable to many educators. They might dismiss it because of the hype, or because they feel overwhelmed with the pace of change.”

This resistance stems from a fundamental misunderstanding of what generative AI represents. Rather than revolutionary technology requiring a complete pedagogical overhaul, Furze positions it as an evolution of existing digital systems. “GenAI is a novel technology, but it’s built on the back of existing digital systems we use every day,” he explains. This perspective shifts the learning challenge from mastering something entirely foreign to understanding how familiar concepts have been enhanced and expanded.

The solution lies in methodical progression rather than rushed adoption. “We can take a step-by-step approach to introduce the fundamentals, such as how GenAI works, what the different models and types do, and so on, and not feel pressured to ‘move fast and break things,'” Furze advises. This approach directly counters the Silicon Valley mentality that has dominated much AI discourse, instead advocating for careful, considered implementation.

Once trainers understand the technology, the challenge becomes making AI literacy relevant to VET’s diverse student base. Furze emphasizes that successful integration depends entirely on connecting digital technologies to practical applications rather than teaching them in isolation.

“I think it’s always best to link the use of digital technologies to their real-world applications, and that is especially true for VET. Digital technologies should facilitate the things we do in our day-to-day lives,” Furze explains. This principle becomes particularly important when considering VET’s role in preparing workers for immediate employment across various industries.

The consequences of context-free instruction are significant. “Teaching digital literacies out of context is a problem because people don’t learn how to quickly apply their new skills, and so they forget them,” Furze warns. This insight highlights why traditional computer literacy courses often fail to create lasting competency—students learn isolated skills without understanding their practical value.

The solution requires integration rather than addition. “Integrate the instruction of AI and digital technologies into the fundamentals of whatever area or industry is being taught,” Furze recommends. This approach ensures AI literacy develops alongside core vocational competencies rather than competing with them for curriculum time.

For SME contexts specifically, Furze suggests focusing on immediate business applications: “For example, for an SME/business owner, how might digital technologies help with business management, planning, finances, etc.?” This targeted approach addresses the time constraints facing small business operators while demonstrating clear value propositions for AI adoption.

While other educational sectors struggle with AI’s challenge to traditional assessment methods, VET possesses inherent advantages that position it ahead of the curve. The sector’s emphasis on practical demonstration over written evaluation creates natural resilience against AI-assisted academic misconduct.

“VET has a wealth of available assessment types – much more than those commonly used in K-12 and Higher Education. While those other sectors are often reliant on written essays and exams, VET can use much more practical assessment, including observation, simulation, role play, dialogue, questioning, and so on,” Furze explains.

This diversity of assessment methods provides both protection and opportunity. Furze notes that these practical approaches “are much more robust to ‘AI misuse’, and also present opportunities where AI might be used well.” The dual benefit allows VET to maintain assessment integrity while exploring legitimate AI integration.

The opportunities for responsible AI use extend beyond simple resistance to misuse. Furze envisions innovative applications that transform AI from a potential threat to a valuable assessment tool: “For example, a student could complete a simulated employer/employee conversation with a voice-enabled chatbot (like ChatGPT), and submit the transcript as assessment evidence.”

Such approaches demonstrate how VET’s flexible assessment framework can accommodate emerging technologies while maintaining focus on authentic competency demonstration. Rather than banning AI use, the sector can channel it toward meaningful skill development that mirrors real workplace interactions.

Looking ahead, Furze sees significant opportunities for VET to capitalize on AI’s evolving capabilities, particularly as the technology moves beyond text-based interactions toward more sophisticated multimodal applications.

“As with the simulation example above, there are many places where VET could stand out and make the most of multimodal GenAI,” Furze observes. The convergence of practical vocational training with advanced AI capabilities creates unprecedented possibilities for both teaching and assessment innovation.

The technological trajectory favors VET’s hands-on approach. “Speech to speech models, like ChatGPT’s voice mode, will increasingly be an important way we interact with all digital technologies,” Furze explains. These developments align naturally with VET’s emphasis on practical communication and real-world application, positioning the sector to lead rather than follow technological adoption.

Accessibility represents a particularly promising frontier. “This could include technologies which improve accessibility and make it easier for students to complete assessments and literacy outcomes,” Furze notes. Advanced speech recognition and generation capabilities could support students with different learning needs while maintaining assessment rigor.

Content creation offers another avenue for leadership. “There will also be novel ways to create content, including video and audio, which VET trainers and educators should understand so that they have a wealth of assessment options available for students to demonstrate their understanding,” Furze explains.

The path forward requires VET providers to embrace their unique position at the intersection of practical education and technological innovation. By building on existing strengths in flexible assessment and real-world application, the sector can establish itself as the frontline for AI literacy development, serving both current students and the broader workforce they will join.