AI has raised the stakes for every engineering leader in the room — but what does actually good look like now? Jyoti and John go beyond the hype to define what engineering excellence means in 2026: the delivery standards, the platform decisions, and the organizational discipline that separate firms that are winning with AI from those still trying to catch up.

When AI arrived, Citi was ready. That didn't happen by accident. Ian walks through the years of intentional delivery investment — the standardization, the platform discipline, the cultural change — that gave Citi a shorter, safer path to AI adoption than most of their peers. A practitioner story about what it actually takes to build an enterprise that can move at AI speed.

Adopting AI tools is the easy part. Rebuilding the operating model, team structure, and data foundations to actually sustain it is where most enterprises are still stuck. This session digs into what's actually holding orgs back, what's worth rebuilding first, and what it takes to move past incremental fixes.

Governance structures are struggling to keep pace with how fast AI adoption is moving. This session breaks down what responsible adoption actually takes: strong data foundations, real accountability structures, and delivery standards that separate confident adoption from chaos.

Security and resilience aren't the same thing — but in the AI era, you can't have one without the other. Leaders from large, heavily regulated enterprises share how they're building the practices, frameworks, and team structures that keep their organizations secure and operational as AI accelerates change and expands the risk surface.

AI doesn't create the problem of a fragmented enterprise foundation — it exposes it. Leaders share what happens when you try to move at AI speed across complex, non-standardized environments: the security gaps that open up, the risk that compounds, and the hard work of building the foundation that should have been there all along.