AI Governance: The Security Perspective
summary
IAPP reports 500+ professionals surveyed, 70% of companies deployed AI, and fewer than 30% had an AI governance function (expected to rise to ~60%); Cranium AI spins out March after building ~16 models and publishing GenAI endpoints; security often owns the operational role (~50–60% CISO-led) and must supply AI red-teaming and AI bill of materials style inventories; practical needs include inventories, RBAC on training data, MITRE ATLAS/OWASP-style adversarial checks, NIST AI RMF alignment, and EU AI Act compliance.
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chapters (18)
- 0:00AI governance introduction
- 2:16Why AI governance is urgent
- 9:32Where governance needs grow fastest
- 12:47Top AI deployment risks
- 16:42Chief AI officer role debate
- 19:58Who leads AI governance teams
- 23:13Building AI governance fluency
- 26:28Security in AI governance
- 30:02Security tools for AI governance
- 32:06AI red-teaming challenges
- 34:33Frameworks for AI governance
- 36:38Steps to build AI governance
- 38:44Resources for AI governance
- 39:05Q&A: Hard law vs governance
- 42:15Q&A: AI vs data governance
- 46:27Q&A: Board-level AI risk
- 48:56Q&A: Diversity in AI teams
- 51:26Closing remarks
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