Vijay Mitra

AI dramatically expands the attack surface, yet the skills required to test these systems remain scarce. Enterprises are under pressure to build internal capability, but few understand what AI red teaming requires in practice. This debate challenges assumptions around in house readiness and exposes where maturing may be overestimated. Panellists will discuss the feasibility of building internal AI red teams, the tooling and expertise genuinely required, and where external specialists remain critical.

Join relaxed, topic-led roundtables designed to connect you with peers facing similar challenges in securing AI across the enterprise. In a no-slide, no-stage setting, each table will tackle a timely Secure AI theme. Lightly moderated to spark honest discussion, challenge assumptions, and share what's really happening on the ground.

Enterprise AI is already in production, but security models haven't caught up. Teams are deploying copilots, agents, and AI-powered workflows faster than organisations can define acceptable risk, leading to inconsistent decisions and growing exposure. The challenge isn't understanding every AI threat, it's deciding where to draw the line and enforcing it consistently. This panel focuses on a critical question: how do organisations define and apply AI risk boundaries in practice, across data use, model behaviour, and autonomy, without slowing down delivery?