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Legacy identity and access management (IAM) can remain part of an organization’s controls for AI agents, but it should not be assumed to manage them safely without changes. Agents may act under a person’s delegated permissions, use their own identity, or inherit access from a workload, shared service account, or human account. The practical challenge is to identify each agent, assign responsibility, limit its access, manage its credentials throughout its lifecycle, and make its actions traceable.
Why are AI agents putting pressure on legacy IAM?
Many established IAM processes are built around people with relatively stable roles and access decisions made at a human pace. An autonomous software agent can act repeatedly and quickly, use credentials without a person present, or make calls to other systems and agents. If it runs through a shared or broadly privileged identity, existing controls may not clearly show which agent did what—or make it easy to withdraw only that agent’s access.
This is not a wholly new category of identity risk. It is a sharper version of non-human identity problems: incomplete inventories, unclear ownership, excessive permissions, uncertain credential rotation, and delayed remediation. The Cloud Security Alliance (CSA) described AI as amplifying longstanding IAM challenges in its January 2026 report, The State of Non-Human Identity and AI Security.
Microsoft’s Entra security guidance also identifies risks including external exposure, excessive provisioning, harmful autonomous decisions, prompt injection, propagation between agents, and “agent sprawl”—uncontrolled growth without adequate visibility, management, or lifecycle controls. That guidance describes Microsoft’s view and capabilities; it is not evidence that every organization experiences each risk in the same way.
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What identity should an AI agent use?
There is no single identity pattern for every agent. The right choice depends on whether the agent acts for a signed-in user or operates independently. The distinction affects how to grant access, preserve accountability, and revoke permissions.
| Identity pattern | How it works | Key control concern |
|---|---|---|
| Delegated user access | The agent acts for a signed-in person using permissions delegated from that user. | Preserve the user context and ensure revoking the delegation or session actually stops access. |
| Dedicated autonomous identity | The agent authenticates independently using an identity assigned to it. | Assign an accountable owner, scope its permissions narrowly, and retain logs tied to that identity. |
| Workload identity | The agent operates with an identity associated with a software workload. | Make the agent distinguishable from other workloads and govern its access and lifecycle. |
| Shared service account | The agent shares an account or credential with other software or agents. | Shared use can obscure attribution and expose the agent to permissions it does not need. |
| Human identity | The agent operates under a person’s account. | Activity can be difficult to distinguish from the person’s own actions, and the agent may inherit excessive access. |
CSA’s March 2026 survey found that respondents reported using workload identities for agents, shared service accounts, and human identities. Those categories may overlap; they describe reported practices, not mutually exclusive shares of all agent deployments.
What do the surveys say—and what do the figures mean?
The figures below are responses to vendor-commissioned online surveys published by CSA. They are not measured breach rates, and they do not establish that AI agents caused an incident or that one identity pattern caused a particular outcome. The two surveys used different respondents and fieldwork periods, so their results should not be combined as though they came from one dataset.
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CSA’s January 2026 survey
CSA’s January 2026 report and press release covered an Oasis Security-commissioned online survey of 383 IT and security professionals conducted in August and September 2025.
| Reported response | Result |
|---|---|
| Organizations lacked documented, formally adopted policies for creating or removing AI identities | 78% |
| Respondents were not confident legacy IAM solutions could effectively manage AI and non-human identity risks | 92% |
| Respondents rated their confidence in preventing attacks via non-human identities as low or moderate | 79% |
| AI-related identity creation and removal were fully automated | 14% |
| AI-related identity creation and removal were handled entirely by hand | 27% |
| Respondents said they did not track when new AI-related identities were created | More than 16% |
| Respondents said it took more than 24 hours to rotate or revoke a credential after potential exposure | 24% |
CSA’s March 2026 survey
CSA’s March 2026 report covered an Aembit-commissioned online survey of 228 IT and security professionals conducted in January 2026.
| Reported response | Result |
|---|---|
| Respondents could not clearly distinguish AI-agent activity from human activity | 68% |
| Respondents said agents often received more access than necessary | 74% |
| Respondents believed agents created new access pathways that were difficult to monitor | 79% |
| Respondents reported using workload identities for agents | 52% |
| Respondents reported using shared service accounts for agents | 43% |
| Respondents reported allowing agents to operate under human identities | 31% |
As CSA AVP of Research Hillary Baron put it in the March 24, 2026 press release, “The survey data indicates that existing IAM approaches were not designed for autonomous agents and are showing strain as deployments scale.” The survey supports a concern about operational readiness; it does not prove that legacy IAM is categorically unusable.
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How should an organization manage agent identities?
Treat each agent as an identity with an owner, an approved purpose, defined access, and a lifecycle—not simply as a feature attached to an application. Apply the controls in sequence so that discovery and accountability precede authorization and operation.
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- Assign accountable owners. Identify who approves the agent, who is responsible for its workload, and who conducts access reviews and retirement. An agent without a responsible owner is difficult to govern when its purpose changes or access must be withdrawn.
- Choose an explicit identity pattern. Decide whether the agent acts with delegated user permissions or independently. Avoid silently borrowing a broad human account or shared credential when a distinct, attributable identity is appropriate.
- Constrain authorization. Grant only the permissions needed for the agent’s specific task and resources. Review inherited rights and pay particular attention to high-impact actions.
- Automate credential lifecycle controls. Make identity creation, credential rotation, expiry, and revocation observable and timely. Define what responders will do if a credential may have been exposed.
- Keep attributable audit records. Log actions against the agent identity and, where relevant, the delegating user and task context. Records should support investigation of what the agent accessed and what it changed.
- Test containment. Establish and exercise how to disable an identity, revoke a token, or stop the agent runtime. Confirm that withdrawing access takes effect across the systems the agent can reach.
How can teams assess whether their IAM controls are sufficient?
Rather than treating “agent-ready” as a product label, check whether the controls work across the full identity lifecycle and during a live response. These questions apply when extending existing IAM, strengthening workload identity controls, or evaluating non-human identity governance capabilities.
- Attribution: Can investigators distinguish the agent’s activity from its owner’s and, when access is delegated, identify the user and context involved?
- Permission scope: Can access be limited to the task, resource, and context, without relying on a broad shared credential?
- Lifecycle: Can teams discover, approve, provision, review, rotate, revoke, and retire agent identities consistently?
- Runtime response: Can the organization withdraw access or contain execution quickly after suspicious behavior or credential exposure?
- Auditability and integration: Do logs support investigation and fit existing identity, security, and compliance workflows?
A control is incomplete if an agent is inventoried but has no owner, if it has an owner but its permissions are never reviewed, or if a token can be revoked but the team cannot tell which agent used it. Assess the end-to-end process, not merely whether an identity platform offers an agent-related feature.
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Is there already a standard for AI agent identity?
As of NIST’s May 18, 2026 publication, the cited NIST work is guidance development—not a completed agent-specific identity standard. NIST’s February 5, 2026 announcement introduced a concept paper and a potential National Cybersecurity Center of Excellence project concerning the identity and authority of software agents. It solicited input on how organizations use agents, what problems they introduce compared with other software, and what standards might guide agent identity and access management.
NIST’s May 2026 summary analyzed responses to its request for information and reported broad agreement that existing cybersecurity principles remain relevant but need adaptation for agent security. That summary describes feedback and themes; it is not a final standard or a certification checklist. Organizations can apply established identity and security practices now while following NIST’s work for further guidance.
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