Entro Security has announced Agentic Governance & Administration (AGA), a new pillar of its platform designed to help security and identity teams govern AI agents and AI access paths across enterprise systems. The company is showcasing AGA at RSA Conference 2026.

The core problem AGA addresses is one that traditional Identity Governance and Administration (IGA) tools weren’t built to solve. Existing IGA platforms govern people and applications, but agentic AI operates differently. The “user” is often an AI service or locally running agent. Access paths run through non-human identities: tokens, service accounts, API keys, and secrets. And the blast radius is shaped by OAuth scopes, integrations, and automation, not a single human login.

“Enterprise AI adoption rarely starts with a strategy deck. It starts with a connection,” said Itzik Alvas, Co-Founder and CEO of Entro Security. “A developer connects a tool to an LLM, a team installs an AI app in SaaS, or someone authenticates an agent against SharePoint, GitHub, Salesforce, or internal APIs. It works, spreads fast, and then security teams get questions they can’t answer fast enough. Who connected what, to which systems, with what permissions, and using which identities? Our AGA helps teams regain clarity and control as AI access becomes the default.”

AGA applies the same governance fundamentals that IAM teams already know, adapted for a world where agents connect in seconds, operate continuously, and drift as adoption spreads. The capability covers inventory, ownership, least privilege, auditability, and enforcement, applied to AI assistants, agent platforms, and locally running agents.

On the technical side, AGA builds a structured profile for each AI agent by pulling from three layers: sources (endpoint telemetry, agent foundries, cloud environments, MCP servers), targets (enterprise assets and applications the agent touches), and identities (human, non-human, or secret identities used to access those targets).

Two core capabilities sit on top of that foundation. Shadow AI Discovery uses EDR integrations to surface AI clients and local agent runtimes on workstations, and connects natively with agent foundries including AWS Bedrock and Copilot Studio to discover agents and the non-human identities they rely on. AI Agents Monitoring and Enforcement adds MCP activity visibility and policy controls, giving teams audit trails of allowed and blocked activity and controls to reduce sensitive data and secret exposure.

AGA is available now as part of the Entro platform.