A cross-sector team of education, government, and industry professionals has developed a practical, ready-to-use toolkit to help VET educators and learning designers understand how AI is reshaping industry – and bring that knowledge directly into teaching and course design. Developed through the FSO Skills Accelerator AI programme, the AI in Industry Project is a proof of concept that gives educators a structured, prompt-based approach to identifying AI’s impact on employment and finding real-world case studies relevant to their students.
At a glance
FSO Skills Accelerator-AI initiative: AI in Industry Project
Partners: IATD NSW, Victorian Department of Jobs Skills Industry and Regions (DJSIR), Stratentia, Disrupters Co
Timeframe: Skills Accelerator Action Learning Sprint 3, February–April 2026
Primary goal: Develop a practical proof-of-concept toolkit to help VET educators and learning designers understand AI’s impact on industry employment, and find relevant AI case studies for use in teaching
Key outcomes:
- A structured, four-step framework with AI prompts that help educators map how AI affects tasks and skills in any job role or unit of competency
- A curated library of high-quality, regularly updated sources for real-world AI case studies, with ready-to-use prompts to find, summarise, and adapt examples for the classroom
- A shared taxonomy of AI capability types (Automation, Assistance, Augmentation, Human-led) to help educators categorise and communicate AI’s impact consistently
- An appendix of supporting resources including source tools, reference links, and prompt templates
The challenge
AI is being adopted across Australian and global industries at pace – reshaping tasks, shifting roles, and creating new skill expectations. For VET educators and learning designers, that creates a real problem: how do you keep course content and assessment current when the workplace is changing faster than training packages can be updated?
Two gaps were identified as particularly acute. First, educators lacked a structured, accessible way to understand which tasks in a given job role or unit of competency were being automated, assisted, or augmented by AI – and what that meant for the skills students needed to develop. Second, there was no reliable, easy-to-use approach to finding current, industry-verified AI case studies that could be used directly in teaching.
The project challenge, as scoped through the FSO Skills Accelerator, was to address both problems in a way that any VET educator could act on immediately – without requiring technical AI skills or extensive research time. The result needed to be practical, repeatable, and built around the reality of how educators work.
About the initiative
The AI in Industry Project was developed by a voluntary, cross-sector team brought together through the FSO Skills Accelerator AI Action Learning programme. The team drew on expertise spanning government workforce strategy, digital transformation in the training sector, and industry-level AI adoption.
The initiative tackled two of the three scope problems identified at the outset of the sprint:
- Problem 1: Giving educators a way to understand how AI might affect employment for their students – including which tasks and skills might be positively or negatively impacted
- Problem 2: Giving educators a way to find relevant, topical AI case studies for their industry or course context – and enough supporting information to use them in teaching
The output is a two-section proof-of-concept document. Section A provides a structured, four-step framework – including a ready-to-use AI prompt – that enables educators to analyse any job role or unit of competency and understand AI’s impact on tasks, skills, and workforce planning. Section B provides a curated set of verified sources for real-world AI case studies, together with three adaptable prompts that help educators find, summarise, and build classroom activities from those examples. Both sections are deliberately designed to be picked up and used without prior AI expertise.
The impact
Early testing of the toolkit with more than eight VET educators, confirmed that the prompts work as intended across a range of AI tools, including Microsoft Copilot, and for users without a teaching background as well as those with one. Testers reported being able to generate detailed, structured outputs – including full task analyses mapped to AI capability types – with a single prompt, and described the experience of working through the toolkit as genuinely instructive in itself. One tester, working in a government skills program delivery role, used the Section A prompts to produce a list of 22 tasks for educators teaching a graduate certificate in data science, with Copilot automatically offering to extend the analysis further. Another tester, with a background in supporting TAFE delivery, described the framing as one that “any teacher could go away from with a new approach to inform their own workflow.” Both testers noted the value of the toolkit not just as a reference resource, but as a practical experience that built their own confidence and understanding of AI in a work context.
For systems and processes:
- The structured prompt framework in Section A produced usable, detailed outputs in a single session – reducing the time and expertise required to map AI’s impact on a specific role or qualification
- The Section B prompts successfully surfaced current, relevant industry case studies from authoritative sources, including government and major technology providers, demonstrating the approach works across different industry contexts
- The toolkit’s modular design – two self-contained sections with independent prompts – means educators can use it selectively based on their immediate need, without working through the entire document
For people and culture:
- Testers without a teaching background were able to engage meaningfully with the toolkit, suggesting it is accessible to a broader range of VET sector professionals beyond classroom educators
- Multiple testers reported gaining new understanding of how to use AI tools more effectively as a direct result of working through the prompts – an unintended but significant learning outcome
- The toolkit prompted testers to consider practical extensions, including how the outputs could be used for assessment design and trainer capability planning, indicating strong potential for embedding into existing workflows
What worked well
Framing the toolkit around ready-to-use AI prompts made it immediately accessible – educators did not need technical AI skills to get value from it
The cross-sector team brought complementary perspectives that strengthened both the practical framing and the depth of the framework
Keeping the scope focused on two concrete problems (rather than all three identified in the sprint) allowed the team to produce a genuinely usable proof of concept within the sprint timeframe
Challenges faced
Balancing depth with accessibility – the underlying framework (particularly the four-step AI impact analysis) is technically rigorous, and the team worked to ensure it remained approachable for non-specialist educators
The pace of AI adoption in industry means some case study sources become outdated quickly; the toolkit addresses this by pointing to live, regularly updated repositories rather than static lists
Early testing suggested that some users may benefit from additional scaffolding on how to use AI tools more effectively – the toolkit introduced new ways of working with AI that, for some users, surfaced a need for broader AI literacy support alongside the resource itself
Next steps
The team will share the AI in Industry Project toolkit with the FSO Skills Accelerator network for broader testing and feedback. Based on that response, a future sprint may extend the toolkit to include agentic workflow versions of the prompts for more advanced AI users. The team is also exploring how the shared AI capability taxonomy could be integrated into curriculum planning frameworks more formally.
What participants said
“I ran the prompts and got a great list of tasks – Copilot included all the required columns and offered to provide additional detail. Using the resource, I asked to Copilot to find me a case study from a Victorian manufacturer that would be applicable to Cert IV in Engineering students. It came up with one!”
– Sprint participant, government skills program delivery
“I think any teacher could go away from this task with a new approach to inform their own workflow or that of students. The best parts for me were the explanations of ways to get better responses from AI – in particular, the prompts asking AI to come back with questions are super important.”
– Sprint participant, government skills support, TAFE sector
Access the resource
AI in Industry Project - a practical toolkit for VET educators and learning designers
- Section A helps you analyse how AI affects tasks and skills in any job role or unit of competency, using a structured four-step framework and ready-to-use AI prompts
- Section B helps you find current, real-world AI case studies relevant to your teaching area – with prompts to find, summarise, and adapt examples for the classroom
- Designed for use without prior AI expertise