AI governance is no longer just for your legal team, but is becoming a daily reality for developers, designers, and product managers. The rapid adoption of AI agents taking real-world actions introduces an entirely new risk profile for product teams as well.
But what does "governance" actually look like when you’re debugging an agent's reasoning loop or trying to hit a sprint deadline without getting blocked?
This session skips legal theory to focus on what product teams actually need to know. We’ll look at how to translate high-level guidelines like NIST’s AI Risk Management Framework and the EU AI Act into practical engineering decisions. We will use a beginner friendly governance framework as a lens on how to balance innovation with accountability, helping your team navigate: what we need to do for the product, what we should do ethically, what we must do legally, and what we can do technically.
Whether you’re writing code or managing the roadmap, you’ll leave with practical strategies to build systems that are resilient, compliant, and ready for global deployment.
