AI is moving into enterprise workflows faster than most security programs can adapt. Shadow AI, opaque models, prompt-based data exposure and third-party AI dependencies are creating risk patterns that traditional governance and control frameworks were never designed to handle.

As AI reshapes both business operations and security functions, this discussion will focus on how organizations are securing AI at scale – addressing governance gaps, shadow AI and risk management challenges that emerge as adoption accelerates

This closed-door executive roundtable is designed for security leaders who are already confronting AI risk in production environments, as well as those preparing for near-term expansion. The discussion will focus on where AI security efforts most commonly break down, how leaders are making tradeoffs between control and speed, and which architectural decisions are hardest to reverse once AI is embedded into critical operations.

Rather than presentations, the session will prioritize peer discussion and shared lessons learned, with NTT Data and Cisco contributing perspective from enterprise AI deployments across regulated and hybrid environments.

We will explore:

• Where AI governance fails in practice as adoption accelerates across the enterprise
• How security leaders are making real tradeoffs between innovation velocity and risk
• Which AI security decisions create hidden debt that surfaces months later