Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

AI workloads are appearing across AWS environments faster than most teams can inventory them. New APIs, EKS clusters, model integrations, and AI services are showing up across accounts and regions without a clear ownership trail or centralized visibility. By the time security catches up, the environment has already changed again.

AI adoption within AWS environments is accelerating faster than most security and governance programs. AI agents, APIs, MCP servers, and model integrations are entering production across cloud environments, often without centralized visibility or runtime controls. In this webinar, you’ll see how teams can discover AI workloads across AWS accounts, understand what AI systems are actually doing at runtime, enforce policy in real time, and generate continuous governance evidence without slowing engineering teams down. The session focuses on practical operational capabilities for AI systems already running in production.

In this session, you’ll learn: How to see what your AI systems are actually doing across AWS How to use that visibility to understand behavior and impact How to act in real time with blocking, rate-limiting, and quarantine How to operationalize AI governance with the AI Control Platform.

In this webcast, we get into why signature-based protection breaks down in AI-first environments, what behavioral detection and positive security models actually look like in production, and what it takes to evaluate whether your runtime tools are genuinely adapting to your environment or just adding noise to your stack.

What happens when isolated vulnerabilities become a real attack path? This webinar shows how today’s API risks connect into the exact scenarios making headlines, and what business leaders need to do about it.