Kiteworks: Controlling Data Access and Use by AI Agents for Compliant AI

I've watched organizations rush AI adoption straight into a compliance crisis — and the gap is always the same. Regulated data doesn't stay put when agents are in the loop. AI agents autonomously push private data across compliance boundaries, routing it through systems and workflows that traditional security was never designed to monitor, much less control.

The problem isn't that AI is inherently risky. The problem is that most organizations are governing AI outputs without governing the data underneath them. That's where exposure lives.

In this session, I'll show you how Kiteworks Compliant AI closes that gap. We'll walk through how to apply attribute-based access control so agents only touch what they're authorized to touch, how real-time policy enforcement stops violations before they happen rather than flagging them after the fact, and how comprehensive AI audit trails give you the visibility regulators expect and your security, compliance, and legal teams need. You'll also see how granular controls let you define exactly how agents interact with sensitive data — not just whether they can access it, but what they can do with it, where it can go, and who gets notified when boundaries are tested.

You'll leave with a concrete framework for governing data in motion, not just data at rest. If your organization is deploying AI in a regulated environment — healthcare, financial services, defense, government, manufacturing, and others — this session is the one you can't afford to skip.