The promise of AI agents is compelling: systems that no longer just answer questions, but make decisions and take actions on your behalf, across every application, inbox and workflow your business runs on.
For individuals, this is already a productivity force multiplier. For enterprises, the need for strong governance and security has made that vision feel unattainable.
In practice, the people who are experiencing that magic today are mostly doing it outside of IT's purview. They've been connecting their own model context protocol (MCP) servers and plugging agents into data sources without approval, creating exactly the kind of shadow AI risk that keeps CISOs up at night: proprietary data potentially flowing to unvetted models or agents accessing systems they should not access.
Agents behave differently than human users. They can explore paths, call APIs and attempt workflows in ways that require clear boundaries and oversight.
Enterprises need a way to give their people the magic of agentic productivity while maintaining a single point of control over what those agents can access and do.
