It was a privilege to speak and participate as a panellist at today's Building AI Without Boundaries: Data, Sovereignty and Scale workshop, hosted by QUT, the Australian Academy of Technological Sciences and Engineering (ATSE) and the ARC Industrial Transformation Training Centre — Joint Biomechanics, at QUT's Garden Point Campus in Brisbane.

My sincere thanks to the organising team — Distinguished Professor Yuantong Gu, Professor Clinton Fookes, Dr Laith Alzubaidi and Professor Mel Bridges — for pulling together a genuinely outstanding program and for the invitation to contribute.

The breadth and depth of thinking in the room was remarkable. Session 1 examined how AI can learn across distributed organisations without moving sensitive data — and what governance, accountability and sovereignty conditions have to be in place before that is truly safe to do. Session 2 tackled the question of how we build and scale AI systems efficiently and affordably. The panel discussions across both sessions were candid, rigorous and practically grounded.

My own contribution explored what I am calling the Board Test for Sovereign AI — five conditions boards should require to be satisfied before approving a federated AI project — with health as the primary example but the governance principles applying well beyond it.

#SovereignAI #AIGovernance #FederatedLearning #DigitalHealth #BoardGovernance #AustralianAI

Technology governance is no longer an ICT agenda item.

That was my clearest takeaway from the AICD Technology Governance Forum in Brisbane last week. Most boards are still treating technology as a topic that appears on the agenda, rather than the lens through which the entire agenda should be read.

I’ve written up my reflections — including five questions I’d encourage boards to put on the table now, and a challenge to the way we often talk about AI governance (enthusiasm without accountability isn’t governance).

Download the summary report here: Technology Governance.pdf‍ ‍(307 KB)

I recently spent a couple of days at the Australasian Institute of Digital Health’s AI.Care conference in Brisbane. I came away equal parts energised and sobered. Energised, because there’s real momentum: AI is no longer a speculative future in healthcare. It’s already in the room. Sobered, because the biggest barriers to adoption aren’t technical. They’re human, organisational, legal, and cultural.

AI.Care’s framing was practical: move beyond hype, learn from real deployments, and figure out what it takes to go from pilot to scale. The stated themes ranged from adoption and governance to workforce, privacy, security, consumer trust, data sovereignty and the role of national collaboration in Australia’s approach to AI in care. In other words: not “what can the model do?” but “what does it take to make this safe, useful, and sustainable in real health systems?”