Governing Intelligent Systems

Purpose

Make AI governance operational, traceable, and usable by the people who have to live with it. This is governance as infrastructure, not policy.

Session focus

• Decision authority and ownership
• Review loops that scale
• Auditability without bureaucracy

Working blocks

• Where AI risk actually comes from: Unowned decisions and fragmented systems.
• Designing authority into the system: Who decides what, and when decisions can change.
• Review, audit, and traceability: What must be explainable and what must be recorded.
• Governance as an accelerator: How constraints increase velocity.

Teams leave with

• Practical governance patterns
• Clarity on ownership and escalation
• A system that can be defended when it matters