AI in the Classroom and Beyond

Written By Kerri Buttery

What It Actually Looks Like in Practice

The Skills Forecast · Episode 3 · with Julian Ridden, The Anglican Schools NSW

AI in education is everywhere as a topic — but what does it actually take to embed it into a real school, rather than just talk about it? In this episode of The Skills Forecast, Kerri Buttery sits down with Julian Ridden, who leads AI strategy and governance across eighteen schools for the Anglican Schools Corporation, for an unusually candid, practitioner-level conversation. They cover why AI adoption in schools is “uneven” rather than universal, why the technology that promised to be education’s great equalizer has quietly become a new source of inequity, why detection tools can never solve AI plagiarism, and why trust — not technology — is the thing this generation has lost more than any before it.

Connect with Julian on LinkedIn.

“It is impossible to detect AI use with a tool. Stop. That’s it. That’s the whole line.”

- Julian Ridden, Head of AI, The Anglican Schools Corporation

Five things worth taking away

1. AI adoption in schools is “uneven,” and that’s the honest word for it.

Julian’s framing: after the initial shock of ChatGPT, schools have moved past asking “what is this?” and into a much slower, uneven process of figuring out intent — what each school actually wants AI to do for its staff and students. Some organisations are still at “I got it to rewrite my email”; others have full governance and policy in place. Different schools, sectors and even individual teachers are all moving at different speeds, and Julian argues that’s a normal, expected part of the shift.

2. The tool that was meant to be the great equaliser has become a new source of inequity.

When ChatGPT launched, Julian expected generative AI to be “the great leveller” — the first time in history anyone could talk to information and have it recontextualised for them. What’s actually happened, in his view, is the opposite: whoever can afford the best model now has the advantage, and whoever can’t is being left further behind. He frames this as the central governance question schools, RTOs and businesses all need to be asking — not which tool to pick, but how much inequity their AI access is quietly creating.

3. Fluency beats tool choice — and most AI PD is solving the wrong problem.

Julian’s central thesis: focusing on which AI tool to teach is the wrong starting point. What schools actually need to build first is fluency — a working understanding of what AI is, how it’s trained, where its bias comes from, and what you’re giving up when you use a free tool (“if something is free, you’re the product”). Get fluency right across a staff population first, and the tool conversation becomes far easier. Kerri flagged a free, ready-made starting point for anyone wanting to build this in their own team: Anthropic’s free “AI Fluency for Educators” course.

4. “It is impossible to detect AI use with a tool. Stop.”

Julian’s bluntest moment of the conversation, delivered as a direct challenge to any school still relying on AI-detection software: large language models are built on language, and every new model sounds more human than the last — a tool can’t reliably tell the difference, and educators chasing a percentage score are chasing a false signal. His alternative: redesign assessment to measure the process, not just the product (something he says VET is already structurally better placed to do than K–12), and use a real, worked example — a student who used AI to brainstorm ways to recontextualise a Romeo and Juliet scene, then wrote every word of the play themselves, but still missed the point of the task because the task itself was measuring the wrong thing.

5. Trust is what this generation has lost — and modelling is how you rebuild it.

Julian’s closing thread: today’s students are the first generation to grow up unable to fully trust what they see, read or hear — including their own teachers. His example: his own daughter runs her HSC essays back through AI to rewrite them, not to cheat, but because her school’s AI-detection tool was flagging her own writing as “30% AI written.” His prescription is modelling: leaders and teachers openly showing their AI use — what they asked for, what they changed, what they kept — rather than quietly using it and hoping no one notices. He argues this is the only way to rebuild the permission and trust that detection tools and blanket bans have eroded.

Mentioned resources

AI in schools — governance and policy

Student wellbeing and AI companions

Human-centred AI leadership

Assessment and AI literacy

Where the conversation goes

•     00:00 — Welcome to Julian Ridden — from classroom history teacher to Head of AI across eighteen schools

•     06:00 — AI adoption in schools is “uneven” — and why that’s the honest word for it

•     09:00 — Governance, equity and the “great equalizer” that became a new divide

•     14:00 — Fluency over tool choice: what AI literacy actually means

•     21:00 — The confidence gap: what the research says (and why Julian thinks it’s already out of date)

•     24:00 — Modeling AI use: how leaders build permission to experiment

•     28:00 — “It is impossible to detect AI use with a tool. Stop.” — rethinking AI plagiarism and assessment

•     33:00 — Leon Furze’s AI Assessment Scale and clarifying the rules with students

•     35:00 — Does Australia’s national AI framework actually help at the coalface?

•     38:00 — Beyond the framework: Magnifica Humanitas and human-centred AI leadership

•     42:00 — How students are actually using AI — and the trust problem underneath it

•     52:00 — Julian’s top tips, jobs shifting not disappearing, and what’s next with Claire Field

Watch or listen

Watch on YouTube: The Skills Forecast — Episode 3

Listen on Spotify or Apple Podcasts

About the guest

As Head of AI at The Anglican Schools Corporation (TASC), Julian Ridden leads the strategic adoption of generative AI and next-generation school systems across member schools. His work focuses on ethical implementation, AI policy development, and facilitating professional development workshops to empower educators and students in leveraging AI effectively and responsibly.

Alongside his role at TASC, he serves as a Senior Industry Fellow at RMIT University, contributing to research and educational innovation through the Centre for Future Skills and Workforce Transformation. His mission is to ensure education systems align with evolving workforce needs by addressing AI integration challenges and opportunities, while confidently guiding stakeholders toward meaningful engagement with cutting-edge technologies.

His expertise lies at the intersection of AI, education, and market expansion. He has led national AI initiatives in schools, aligning innovation with compliance and curriculum frameworks, and delivered executive-level strategy that turns emerging technology into measurable impact. He operates as a bridge between users and business outcomes. His approach integrates voice of customer, product strategy, and go-to-market execution to ensure innovation is not only technically sound but also trusted, adopted, and sustainable. He thrives in high-growth, high-change environments where adaptability and cross-functional collaboration are key to success.

What's next

Episode 4 of The Skills Forecast is in October 2026 — Kerri talks with Claire Field about the intersection of VET and Higher Education. Register for the next live session, or subscribe on your podcast platform of choice so you don't miss it.

Kerri Buttery
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The VET Sector at a Crossroads