Expansion of BigID’s DAG and DAM capabilities brings identity controls, least-privilege enforcement, and real-time activity monitoring to non-human AI entities

BigID announced the expansion of its Data Access Governance (DAG) capabilities to cover AI agents: the autonomous, non-human entities now operating inside enterprise environments with broad data access and little oversight.

The next wave of insider risk isn’t human: it’s the agents we deployed to help us, operating without visibility or guardrails. Agentic AI is no longer an emerging consideration – agents are browsing internal systems, retrieving sensitive records, writing to databases, and acting on behalf of users today, often with permissions set months ago, never reviewed, and scoped far too broadly. They operate continuously, at machine speed, across systems that cross organizational boundaries. Most enterprise governance frameworks were not built for them.

BigID now is.

“Access governance has always focused on people,” said Nimrod Vax, Chief Product Officer and Co-Founder at BigID. “Agents are now first-class data consumers, and they’re operating at a scale and speed that makes traditional review cycles irrelevant. BigID extends the same data-centric governance model we apply to humans directly to agents.”

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What’s New

Agent Identity Discovery and Mapping. BigID automatically discovers AI agents operating in the environment, cataloging the data stores they access, the permissions they hold, the systems they touch, and the scope of their activity. If an agent is interacting with your data, BigID knows about it.

Access Right-Sizing for Non-Human Identities. Apply least-privilege principles to AI agents the same way you apply them to human users. BigID compares provisioned access against actual access behavior and surfaces remediation paths for over-permissioned agents before a misconfiguration creates an incident.

Real-Time Agent Activity Monitoring. Track what AI agents are doing with data in real time: reads, writes, data movements, cross-system access, with full classification context attached. Security teams see not just that an agent accessed a record, but what sensitivity that record carries and whether the access was in policy.

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The BigID Difference

Identity governance was built for humans, and agents aren’t humans. They don’t log off, don’t forget, and don’t stop when something looks wrong. They operate at a scale and speed that makes traditional review cycles irrelevant. BigID extends its proven data-centric governance model to non-human identities natively: the same discovery engine, the same classification layer, the same risk framework, applied to entities that never stop running.

Other vendors are retrofitting human IAM tools to handle agents. BigID governs agents at the data layer, where the actual exposure lives, understanding not just who accessed what, but what that data is and whether that access should have happened at all.