WHY THIS MATTERS NOW

The gap between AI spend and AI value keeps widening

This isn't theoretical. Governed, agent-driven delivery is already running in production inside at least one APRA-regulated Australian financial institution, with measurable results in delivery speed and compliance confidence.

Expect a direct conversation with peers navigating the same structural shift, not a product pitch.

• AI tools given to individual developers rarely translate into enterprise-wide productivity gains.

• Adding more engineering squads doesn't solve a capacity problem on its own, coordination overhead grows faster than the teams do.

• Knowledge concentrated in a handful of senior engineers isn't just a delivery risk, it's a governance one: reasoning that can't be audited can't be governed.

• Project-based delivery disbands the teams that built the deepest understanding of a system, right when that understanding matters most.

• Few organisations yet have a clear answer for what "good" looks like when AI agents are writing production code.

WHAT THIS DISCUSSION WILL COVER

Four areas the room will work through together

1. From project teams to persistent teams
What it takes to move toward outcome-funded, persistent engineering teams aligned to products and platforms, rather than teams that disband once a project ships.

2. AI as a governed capability, not a tool
The shift from individual developers using AI tools ad hoc, to AI treated as versioned, compounding organisational capability.

3. Governance built into the pipeline
Why controls that can't keep pace with delivery speed fail at scale, and what it looks like when compliance checks run inside the pipeline itself, not as a review bolted on afterward.

4. Where humans and AI agents actually split the work
How that split shifts with maturity, from AI assisting individual tasks under human review, toward humans governing outcomes while agents run the delivery itself.

WHAT YOU’LL TAKE AWAY

Leave with more than notes

A clearer read on the real constraint
Why AI tools alone aren't closing the productivity gap, and what actually needs to change first.

A practical view of persistent teams
How organisations are restructuring around outcome-funded, product-aligned engineering teams.

A sharper sense of what "good" looks like
How peers are thinking about code quality, reproducibility and governance as AI takes on more of the delivery cycle.

Perspectives from peers, not vendors
How other financial services engineering organisations are actually sequencing this shift.

A sense of where you stand
How your organisation's progress compares with peers navigating the exact same shift.

WHO WILL BE IN THE ROOM

A curated group of senior engineering and technology leaders

The value of this discussion comes from hearing how peers across banking, insurance, superannuation and wealth are actually approaching this shift, not from a single point of view.

Drawn from Australia's leading banking, insurance, superannuation and wealth organisations, including:

Technology Leadership
CTO · CIO

Engineering & Delivery
Head of Engineering · Chief Engineer · Head of Delivery

Data, AI & Platforms
Head of Data · Head of Platforms · Head of Applications · Head of Enterprise Architecture

Risk & Compliance
CRO · Head of Compliance