Session discusses how encoding governance as code (policy gates, immutable evidence capture & lineage) turns vague risk statements into automated, auditable defenses. Session shows how Policy-as-Code stops risky promotions, surface exfil attempts and produce the evidence auditors and boards require to approve AI deployments. Key Takeaways-

#1 Understand the minimal, board‑readable architecture (policy‑as‑code + secrets + evidence store + lineage) required to make agentic AI auditable

#2 Learn how automated policy gates and immutable evidence capture convert governance requirements.

#3 Get a pragmatic 30–90 day pilot plan and KPIs that you can present to the board to demonstrate controlled AI adoption