Use a blended-identity governance model. Define which steps are covered by user delegation, which steps are covered by service authority, and where escalation boundaries sit. Without that split, responsibility becomes unclear when the agent writes data, sends output, or touches a third-party system.
How should blended authority be defined for an AI agent?
A blended-identity model should not treat the agent as either purely user-driven or purely system-driven. The key is to define which actions are performed on the user’s behalf, which actions execute under service authority, and which decisions require explicit escalation. That boundary is what makes accountability, auditability, and privilege control workable when the agent can act in multiple modes.
In practice, blended authority is a policy design problem before it is a technical one. If the same agent can draft, write, transmit, and call external systems without a clear authority split, teams will misread who approved the action, who is responsible for the output, and which controls should have applied at the moment of execution.
Where do delegation boundaries need to sit?
The important boundary is the transition from user delegation to service authority. User delegation should cover actions that are clearly representational, while service authority should cover the narrow set of machine-run operations that the organisation is willing to let the agent perform independently. Anything that changes records, reaches outside the trust boundary, or creates durable side effects should be explicitly classified.
That split should be visible at the level of requests, not just accounts. An agent may be allowed to prepare an email under user intent, but sending it, posting data, or invoking a third-party API can require a different authority decision. This is where AI Agent Authorisation Guide is most useful: it frames per-action authorization, delegated authority, and human approval as separate decisions rather than one broad permission.
Good boundary design also means the agent can be constrained differently by context. A task scoped to summarisation should not silently inherit the ability to modify data or trigger downstream workflows. The more clearly the authority boundary is stated, the easier it becomes to stop privilege creep when the agent expands from advice into action.
What breaks when user and system authority are mixed?
Blended authority fails when responsibility is assigned to one actor but execution happens under another. That creates ambiguity in three places: who authorised the step, which identity should be audited, and what blast radius exists if the action is wrong. The problem becomes most obvious when the agent writes data, sends output externally, or touches third-party systems that the user could not directly access in the same way.
There is also a practical security problem: mixed authority often hides excessive privilege until after the fact. If the agent can switch between user context and service context without explicit controls, it is easy for a harmless-seeming interaction to become a durable system change. This is why Zero Trust for AI Agents matters here, because it ties the answer to verifying the principal, removing standing privilege, and enforcing policy per action.
When the authority model is unclear, incident response also gets weaker. Logs may show the agent executed the action, but not whether it did so as delegated user intent or as an independent service operation. That makes it harder to decide whether the right remediation is credential rotation, policy tightening, approval redesign, or a simple rollback.
Risk and Threat Considerations
Mixed authority increases the chance of overreach, accidental data modification, and trust confusion, especially where an agent can move from drafting to execution without a fresh approval point. It also broadens the impact of prompt injection, tool misuse, or compromised agent context because the attacker may inherit both the user-facing trust relationship and the service-side execution path.
Failure mechanism: The agent performs an action under the wrong authority boundary, so a user-intended workflow gains machine-grade reach into data, messages, or external services without a clear escalation check.
Impact: Organisations can lose accountability for sensitive actions, overstate who approved them, and expose systems to unauthorized writes, external leakage, or third-party abuse that is difficult to unwind after the fact.
Standards & Framework Alignment
This section maps relevant standards and security frameworks to the operational risks and controls described in this guidance.
OWASP Agentic AI Top 10 addresses the attack and risk surface, while NIST SP 800-53 Rev 5 and NIST Zero Trust (SP 800-207) set the governance and control requirements practitioners need to meet.
| Framework | Control / Reference | Relevance |
|---|---|---|
| OWASP Agentic AI Top 10 | ASI03 — Identity & Privilege Abuse | Blended authority creates identity and privilege confusion in agent actions. |
| Recommendation — Separate delegated user intent from service authority and gate every privileged agent action. | ||
| NIST SP 800-53 Rev 5 | IA-9 — Service Identification and Authentication | Service-run agent actions need distinct authentication from user delegation. |
| AC-6 — Least Privilege | The question is about limiting what the agent may do under mixed authority. | |
| AU-2 — Event Logging | Mixed authority requires traceable records of who approved and what executed. | |
| Recommendation — Authenticate agent services distinctly and bind each action to the correct principal. Limit agent permissions to the minimum required for the approved task. Log the authority source, approval state, and executed action for every agent step. | ||
| NIST Zero Trust (SP 800-207) | Zero Trust Architecture | Per-action verification and no implicit trust fit blended user and system authority. |
| Recommendation — Verify each agent action explicitly instead of inheriting trust across steps. | ||
Practitioner Guidance
What to verify: Define the exact point where delegated intent ends and service authority begins, then test whether that line still holds when the agent retries, chains tools, or acts on behalf of multiple users. If you cannot explain the authority source for a given action in one sentence, the control boundary is still too loose.
Decision rule: If an agent action can create persistent state, reach an external system, or trigger irreversible effects, require an explicit authority check rather than assuming the original user request is enough. If the action is advisory only, keep it in the user-delegated lane and do not let it inherit broader service permissions.
Practitioner takeaway: The objective is not to eliminate blended authority, but to make every meaningful action attributable to one authority mode at a time, with escalation only where the organisation is prepared to own the consequence.
Related resources from NHI Mgmt Group
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Reviewed and updated by the NHIMG editorial team on October 6, 2026.
NHI Mgmt Group — the #1 independent authority on Non-Human Identity, IAM, and Agentic AI security. nhimg.org