Presented at the Velg conference, this session covers the ethical, strategic and practical integration of AI in Vocational Education and Training. It looks at how AI can transform two of the sector’s most tedious processes, RPL and traditional assessment, by introducing scenario-based role-play environments such as Competency AI that counter student cheating while saving assessors significant time.
Understanding the AI evolution
We are moving from Narrow AI toward Artificial General Intelligence, systems as capable as humans collectively, and eventually toward Artificial Super Intelligence, or the Singularity. That trajectory makes robust government regulation and institutional policy urgent, not optional.
Rethinking assessment to prevent cheating
Traditional methods of detecting AI-generated text in assignments no longer work. Institutions need to transition to flipped assessment models and simulated, scenario-based role-plays, like Competency AI, where competency is proven through active conversation and asking the right questions rather than submitting text a tool could have written.
Streamlining Recognition of Prior Learning
RPL is historically tedious and time-consuming. AI can automate the initial onboarding, map unpolished participant documents to specific TGA units, and identify gaps before an assessor even touches the file, potentially saving 50 to 60 percent of an assessor’s time.
The human in the loop is non-negotiable
AI can provide instant feedback and reduce an assessor’s time from 25 minutes to around 5 minutes per student, but the ultimate responsibility for verifying feedback and approving outcomes must always remain with a human assessor.
Future-proofing VET with multi-agent systems
The future of education involves multi-modal AI and multi-agent systems, where different autonomous agents, such as a bias auditor, an authenticity agent and a context expert, work together simultaneously to validate learning and adapt to each student’s specific needs.