Accountability should sit with the identity, security, and platform owners who control the lifecycle of access, not with individual users or a one-time project team. Blended identities require shared governance across IAM, IGA, cloud, and application owners. Clear ownership matters because policy without accountable operators rarely survives operational complexity or scale.
Why This Matters for Security Teams
Blended identities are not just an IAM taxonomy issue. They create a governance problem where a person, a service account, and an AI agent may all touch the same data, tools, and approval paths. If accountability is unclear, access reviews become ceremonial, exceptions multiply, and no one owns the full lifecycle of the identity that actually performed the action. NIST Cybersecurity Framework 2.0 treats governance as an enterprise responsibility, not a ticket queue.
This is where NHI governance becomes operationally important. The Ultimate Guide to NHIs makes clear that lifecycle control, secret rotation, and revocation must be managed continuously, while the OWASP Non-Human Identity Top 10 highlights how weak ownership leads to exposed credentials, privilege sprawl, and orphaned access. In practice, many security teams discover that nobody owns the blended identity until a breach, an audit finding, or an unplanned AI action forces the question.
How It Works in Practice
Accountability should be assigned to the teams that can actually change access, enforce policy, and retire identities: IAM, IGA, cloud platform, application owners, and the security function that sets control requirements. For blended identities, governance works best when one owner is responsible for the identity object and another is responsible for the business process that uses it. That split prevents the common failure mode where everyone approves access but nobody can revoke it.
Practitioners usually need three things in place. First, a defined inventory that distinguishes human users, service accounts, workload identities, and AI agent identities. Second, lifecycle ownership that ties each identity to an accountable system owner and a named operational backup. Third, runtime policy enforcement that verifies who or what is acting, what it is allowed to do, and whether the action still fits policy. That aligns with NIST SP 800-53 Rev 5 Security and Privacy Controls, especially access control, auditability, and system integrity requirements.
For organisations dealing with AI-enabled workflows, this matters even more because the access path may be dynamic. A chatbot, code agent, or orchestration workflow can trigger secrets use, API calls, and downstream privilege chains that do not map neatly to a single human approver. The right control model pairs the Top 10 NHI Issues with policy-as-code, delegated ownership, and evidence collection so that the person who owns the platform can prove what the identity did, when, and under whose policy. These controls tend to break down in highly federated environments where identity records, cloud entitlements, and application ownership are split across separate teams with no shared revocation process.
Common Variations and Edge Cases
Tighter accountability often increases coordination overhead, requiring organisations to balance clear ownership against the reality of shared platforms and fast-moving delivery teams. The tradeoff is worth it, but there is no universal standard for this yet on how to split accountability across human and machine actors in every operating model.
In regulated environments, the security team may set mandatory control requirements while business or platform owners remain responsible for operational execution. In product-led engineering teams, the application owner may own workload identities but IAM retains policy and evidence oversight. For AI agents, current guidance suggests treating the agent runtime as a governed workload, not a user, and assigning ownership to the system that creates, scopes, and retires its access. The Lifecycle Processes for Managing NHIs section of NHIMG’s guide is useful here because it maps ownership to issuance, rotation, monitoring, and deprovisioning. The practical test is simple: if a team cannot revoke access, rotate secrets, or explain an agent’s privileges, it does not truly own the identity. That model becomes fragile when inherited access is embedded in legacy apps or shadow automation that no one has formally assigned to an owner.
Standards & Framework Alignment
This section maps relevant standards and security frameworks to the operational risks and controls described in this guidance.
OWASP Non-Human Identity Top 10, OWASP Agentic AI Top 10 and CSA MAESTRO address the attack and risk surface, while NIST AI RMF and NIST CSF 2.0 set the governance and control requirements practitioners need to meet.
| Framework | Control / Reference | Relevance |
|---|---|---|
| OWASP Non-Human Identity Top 10 | NHI-01 | Ownership and lifecycle gaps are a core non-human identity risk. |
| OWASP Agentic AI Top 10 | A-03 | Blended identities include autonomous agents with action authority. |
| CSA MAESTRO | GOV-01 | MAESTRO emphasizes governance roles for agentic systems and workloads. |
| NIST AI RMF | GOVERN | AI governance requires clear accountability across automated decision paths. |
| NIST CSF 2.0 | GV.RM-1 | Governance and risk ownership are central to blended identity accountability. |
Assign a named owner to each NHI and require revocation, rotation, and review as part of the identity lifecycle.
Related resources from NHI Mgmt Group
- Who should be accountable for cloud identity governance when both developers and non-human identities need access?
- Who is accountable when unmanaged non-human identities create access risk in an organisation?
- Who is accountable for access decisions across employee and non-employee identities?
- How should critical infrastructure teams manage privileged access across human operators and non-human identities?
