AI is reshaping how organizations use data—and with it, the scope and complexity of privacy risk. While traditional privacy frameworks provide a solid foundation, they weren’t built for the unique challenges posed by AI: opaque models, dynamic data flows, and algorithmic bias.
This session breaks down how privacy professionals can adapt and apply emerging AI risk frameworks, like the EU AI Act, to build scalable, effective governance programs. We’ll explore how to extend privacy-by-design principles into AI systems, assess risk with confidence, and collaborate across security, legal, and data science teams to lead responsibly in the age of intelligent automation.
What you’ll learn:
- How privacy, security, and AI risk intersect—and where frameworks fall short
- Which emerging AI risk frameworks matter (and why)
- Practical strategies for assessing AI privacy risk at scale
- How to evolve your privacy program to meet new regulatory and organizational demands
- What it takes to build AI governance that’s flexible, cross-functional, and future-ready
Whether you’re refining internal policies or designing controls for AI systems, you’ll walk away with a sharper lens, and a framework that scales.