Topic starter
24/07/2026 4:08 pm
TL;DR: AI agents share ownership, review, and delegation patterns with human identities, while still requiring dedicated machine identities, vault-based secrets, and least privilege, according to Noma Security. The governance gap is that runtime behaviour, delegation chains, and session-level manipulation cannot be handled by either human IAM or service account models alone.
Editorial analysis by NHI Mgmt Group, based on content published by Noma Security: “That’s a Great Question – Rethinking Identity for AI Agents”.
Key questions
Q: What breaks when agentic AI is governed like a normal application account?
A: Security controls break down because agentic systems do not behave like fixed-function applications.
Q: Why do delegated AI agent chains increase access risk?
A: Because each hop can lose the original task boundary.
Q: What are the signs that AI agent permissions are too broad in enterprise environments?
A: Common warning signs include agents accessing tools they do not need, performing irreversible actions without confirmation, retrieving cross-tenant or unrelated data, and acting with long-lived credentials.
Practitioner guidance
- Map agent ownership and accountability Assign a named owner, approver, and retirement path to every agent so lifecycle governance is not left implicit or shared across teams.
- Separate human, agent, and sub-agent privileges Give each actor in the delegation chain its own bounded identity so one human credential does not silently propagate through the workflow.
- Use vault-based non-interactive authentication Store agent secrets in a vault and avoid human credentials, so authentication stays machine-oriented and revocation remains controllable.
Bottom line: AI agents sit between human governance and machine identity controls, so a single identity model is not enough to manage them cleanly.
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24/07/2026 4:13 pm
AI agent identity governance is a hybrid discipline, not a user clone exercise. Agents inherit ownership, approval, and review concepts from human IAM, but they also require non-interactive authentication, vault-based secrets, and least privilege from NHI governance. Treating them as only one thing creates blind spots in either accountability or machine control. The practitioner conclusion is that governance has to be compositional from the start.
A few things that frame the scale:
- Half of companies using generative AI will deploy agentic AI by 2027, according to Deloitte's 2025 Technology Predictions.
A question worth separating out:
Q: How can organizations effectively manage access delegation for AI agents?
A: Organizations can manage access delegation for AI agents by implementing policy-based authorization frameworks that ensure correct access levels are maintained. This also involves continuously monitoring agent activities to prevent overprivileged actions.
👉 Read our full editorial: AI agent identity governance needs a hybrid model, not a user clone