Petar Tsankov

Many organizations have defined and committed to AI governance principles. But when it comes to enforcing them, governance too often stalls at the abstract, high-level checklist stage, disconnected from real AI systems and state-of-the-art technical evaluations.

In this session, we'll show you how to take AI governance beyond the checklist by mapping principles to real AI risks, executable controls, and deep technical evaluations, grounded in cutting-edge AI research.

This is AI Governance. Done Right. Because AI governance only works when it's grounded in real-world technical assessments.

You will walk away with:

● A clear, practical approach to turn AI governance principles into enforceable technical requirements

● Real-world examples of AI governance in action: what works, what fails

● Proven ways to scale AI governance with continuous AI assessments embedded in every AI deployment

If you're accountable for AI governance, risk, or compliance, this is how you close the last mile where trust, performance, and compliance meet.