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06/06/2026 11:16 am
TL;DR: Agentic AI agents now browse the web, execute code, access SaaS applications, and take autonomous actions on behalf of users, creating a rapidly expanding attack surface that security teams are still struggling to define, according to Clutch Security. Access review processes assume privilege persists long enough to be reviewed; autonomous agents can acquire and discard access within a single session, breaking that premise.
NHIMG editorial — based on content published by Clutch Security: Why We Created the Agentic AI Masterclass
Questions worth separating out
Q: How should security teams govern agentic AI access in enterprise environments?
A: Treat each agent as a governed identity with an owner, a purpose, connected tools, and a revocation path.
Q: Why do agentic AI systems complicate least privilege?
A: Least privilege assumes you can define required access before execution begins.
Q: What breaks when shadow AI is not brought under governance?
A: You lose inventory, ownership, and lifecycle control.
Practitioner guidance
- Inventory every production agent and connected tool Create a governed asset register that lists each agent, its SaaS connections, internal data sources, and delegated credentials.
- Separate agent access from human access reviews Do not recertify agent permissions on the same cadence or with the same evidence used for employees.
- Control embedded credentials in MCP integrations Treat every MCP connection as an identity dependency, not just an application integration.
What's in the full article
Clutch Security's full article covers the operational detail this post intentionally leaves for the source:
- The masterclass structure and the specific problem areas the vendor says it covers for practitioners moving from awareness to implementation.
- The examples of myths and false controls the article argues should be challenged when securing agentic AI environments.
- The vendor's explanation of how it frames the path from terminology to threats to practical security responses.
- The illustrations and teaching format used to make the masterclass easier to consume for security teams.
👉 Read Clutch Security's article on the Agentic AI Masterclass and NHI risk →
Agentic AI security: what it means for IAM teams now?
Explore further
06/06/2026 11:58 am
Agentic AI turns identity from a provisioning problem into a runtime governance problem. The article is not describing another class of automation. It is describing actors that browse, execute, and chain actions across systems after deployment, which changes what identity controls can meaningfully observe. The implication is that IAM programmes must stop assuming access is static once issued and start treating runtime behaviour as part of identity governance.
A few things that frame the scale:
- 98% of companies plan to deploy even more AI agents within the next 12 months, despite documented rogue behaviour in 80% of current deployments, according to AI Agents: The New Attack Surface report.
- Only 52% of companies can track and audit the data their AI agents access, leaving 48% with a complete blind spot for compliance and breach investigation.
A question worth separating out:
Q: How do organisations decide whether an AI agent needs NHI controls, AI controls, or both?
A: Use the identity behaviour as the deciding factor. If the system needs credentials, tokens, or delegated access to operate, NHI controls are required. If it also makes runtime decisions about tools and actions without approval gates, AI governance is also required. Many enterprise agents will sit across both control domains.
👉 Read our full editorial: Agentic AI is expanding the NHI attack surface faster than controls
