Chair's opening remarks — data-led benchmark of AI deployment and infrastructure maturity across ANZ enterprises in 2026.
Most ANZ enterprises built their technology foundations for stability, not speed and now they're trying to run real-time AI workloads on infrastructure designed for batch processing and on-premise data centres. This panel gets honest about the gap between where ANZ infrastructure actually is and where it needs to be, without a five-year transformation programme.
A CTO on the modernisation decision that changed everything — what triggered it, what it cost, what nearly killed the project, and what the infrastructure looks like now. Not a vendor success story — a real account of the hardest technology decision a leadership team can make.
Every organisation is navigating the same question — what do you build yourself, what do you buy from a vendor, and what do you consume from a hyperscaler? This panel brings together CIOs and CTOs who have made different bets, made mistakes, and changed their minds. No vendor agenda — just the unfiltered decision-making behind the infrastructure choices that define the next decade.
Practitioners share where AI is genuinely changing risk and fraud outcomes versus where it's added a layer of complexity without the returns. Real implementation gaps, false positive problems, and governance realities that don't make it into vendor case studies.
How do you move AI from pilot to production when the regulatory environment is still being written? Peer exchange on navigating Australia's tightening AI frameworks, what's getting blocked internally, and how organisations are making deployment decisions under genuine uncertainty.
The decision between real-time and batch processing is shaping infrastructure investment for the next decade. Groups examine the workload patterns, cost implications and organisational readiness factors that should drive the choice — and where organisations are getting it wrong.
Not every organisation can start from a clean slate. This session walks through the decisions made when modernising a legacy data platform to support AI workloads — which parts of the old architecture were worth preserving, where the shortcuts came back to bite, and the sequencing that made the difference between a migration and a disaster.
AI deployment exposes every integration debt accumulated over years of point-to-point architecture. How are ANZ enterprise architecture leaders rationalising their integration layers, what governance models are working, and what happens to AI velocity when the integration foundation is not fit for purpose.
As hyperscalers bundle AI services into cloud contracts, the line between infrastructure provider and AI vendor is disappearing. This panel examines the concentration risk this creates, the negotiation leverage organisations are losing, and the architectural decisions that preserve optionality without sacrificing capability.
Rapid-fire practitioner confessions on the infrastructure decisions that looked right at the time and didn't age well. No slides, no polish — just the hard-won lessons from teams that have been in production long enough to have regrets.
You can't hire your way out of an AI engineering skills gap in ANZ. This session looks at what organisations are doing to build platform and ML engineering capability internally — what training programmes stick, what squad models work, and what the ones that failed had in common.
When everyone has a stake and nobody has final say, AI initiatives stall in committee. This session maps the ownership models actually working in ANZ enterprises and how to stop accountability gaps killing your infrastructure roadmap.
When AI workloads hit production, cloud bills follow and most ANZ finance teams were not prepared for the variability. A CIO on how they implemented FinOps discipline, brought compute spend under control and built a cost model that the CFO could actually trust, without slowing down engineering.