Governing AI Agents: Secure Access, Identity, and Control at Enterprise Scale (EMEA Broadcast)

AI agents are advancing quickly, but without seamless governance, trusted identity, and policy enforcement, they remain risky to scale. While AI models can reason and plan, they are not designed to execute across complex systems with the governance, security, and control enterprises require. The missing layer in enterprise AI is execution. 

SnapLogic serves as that trusted execution layer, where agent actions are governed by policy, executed with the correct user identity, and fully auditable across enterprise systems.

In this session, you will see how to move from building AI agents to executing them in real enterprise workflows. You’ll walk away with a practical framework for operationalizing AI agents securely, with the governance, access control, and visibility needed to move from experimentation to enterprise scale. We’ll explore how SnapLogic’s MCP Server architecture enables sovereign tool calling, giving enterprises control over what tools AI agents can invoke — and how. 

This webinar will explore:

• Governing AI agents from day one. See how SnapLogic’s MCP Server controls what agents can access, who they act as, and how every action is enforced, tracked, and verified through the same policy engine already governing your APIs.
• Eliminating shared service account risk. Learn how token propagation carries the end-user’s identity from the agent through the integration layer into enterprise systems, ensuring AI operates with the right permissions at every step.
• Moving beyond AI pilots to production-ready execution. Build a practical framework for deploying secure, observable AI workflows with centralized governance, audit-ready execution logs, and architecture designed to scale across the enterprise.