Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

The days of vendors selling naked tools that drive up professional services revenue are coming to a close. AI is making it possible to not just automate human tasks, but to deliver an entirely new agent operator-based platform. Humans become managers of agentic operators, and the operators do the day-to-day work of securing web applications and APIs.

A straightforward framework for matching each layer of protection to the problem it actually solves. Trying to understand vendors in the modern application security space can feel a lot like trying to solve word scramble. Whether it’s remembering what the “A’s” in "WAAP” stand for, figuring out if “WAF” includes APIs, or assessing the actual function of a new AI security product, understanding what tools your team actually needs is getting harder all the time.

AI is making decisions across your environment — calling APIs, accessing data, and taking action. Most organizations know it's happening, but far fewer can see it, let alone stop it. In this panel discussion, security leaders will share what they've learned deploying and governing AI workloads at scale on AWS, and what it takes to close the gap between deployment and accountability.

Security teams are receiving more alerts tied to AI workloads, but most miss the runtime context needed to understand what happened, why it happened, and whether it violated policy. AI visibility cannot stop at deployment and configuration. Join this live demo session to see how Wallarm AI Hypervisor helps teams understand what AI workloads are actually doing at runtime inside Kubernetes environments. The session focuses on giving security teams clearer operational context around AI behavior, outbound activity, sensitive data exposure, and user-driven actions across AI systems.