AI innovation now outpaces traditional governance and planning cycles. By the time your architecture board approves a standard, the technology has moved on. By the time your roadmap reaches year two, the assumptions behind it are obsolete. But moving fast without architectural intent creates a different chaos: redundant agents, ungoverned AI sprawl, and a landscape more complex than the one you were simplifying.

The question isn't speed versus control, it's: what does control look like when the thing you're governing is learning, adapting, and acting on its own?

1. How do you write a three-year roadmap when the technology changes every three months?

2. You spent a decade building integration architecture. An AI agent just bypassed it. Now what?

3. Your data governance was built for dashboards and reports. Is it ready for autonomous agents acting on that same data in real time?

4. What happens to your integration architecture when AI agents start negotiating with each other across system boundaries?

5. Compliance frameworks assume a person is accountable. Who signs off when an AI agent approves a €2M purchase order?

You'll leave with: A set of architectural principles for the agentic era, co-developed in the room,  that balance speed of innovation with enterprise-grade governance and strategic coherence.