Across ANZ enterprises, the gap between AI ambition and AI outcome rarely comes down to appetite — it comes down to execution: fragmented processes, manual workarounds, and legacy dependencies that quietly absorb the value AI was meant to create. This panel moves past the well-worn "pilots to scale" narrative to ask a sharper question: what does it actually take — operationally, not just strategically — to convert AI investment into outcomes that show up on the P&L?

As agentic AI moves from experimentation to execution, it's making autonomous decisions and taking action inside core enterprise systems — a different class of security question than traditional AI oversight. This panel brings together security and technology leaders to explore what governance, control, and accountability look like when the "user" making a decision might be an AI agent, and how enterprises are building trust into these systems without slowing them down.

Much of the conversation about enterprise AI still centres on models and use cases — but for many organisations, the real constraint is what sits underneath: infrastructure that wasn’t built for AI-scale workloads, and a talent base stretched thin trying to operate it. This panel looks past the hype cycle to the less glamorous work of modernisation — the platform, workforce, and operating model decisions that determine whether an enterprise can actually compete in the AI era, or simply keep pace with it.

• Peer networking before the match