Every enterprise offboarding process covers the departing employee's human account.
Security teams often use "orphaned" and "unsanctioned" interchangeably when describing rogue AI agents. The distinction matters because each type requires a different detection method and a different remediation path.
An orphaned AI agent is an agent whose creator or owner account has been disabled, deprovisioned, or deleted, while the agent itself continues to operate. The agent was built legitimately. It may have passed an informal review. But when the employee who built it left the organization, the offboarding process covered their human account and missed the machine identity entirely.
The agent keeps running. Its connector credentials, OAuth tokens, and embedded service account permissions remain valid. It continues to access the SaaS systems it was configured to reach. No one receives its alerts. No one reviews its activity. No one owns it.
This is the defining characteristic of orphaned AI agents: credentialed access without accountability.
An unsanctioned AI agent is an agent deployed without security review or IT approval. It may have an active owner. The person who built it may still be employed. But the agent was never registered, never assessed for risk, and never added to any inventory. It operates in the same shadow AI space as unauthorized SaaS apps, except that unlike a passive app, it takes autonomous actions.
Unsanctioned agents are the output of business unit shadow deployments. A sales operations team builds a Copilot Studio agent to automate CRM updates. A finance analyst creates an n8n workflow connecting to Salesforce and a cloud storage bucket. These are not malicious actors. They are business users solving real problems with the tools their platforms provide. The problem is that security teams have no visibility into what those agents can access or what they are doing.
The two categories overlap more often than security teams expect. An unsanctioned agent built by a business user becomes an orphaned agent the moment that user leaves the company. Because the agent was never inventoried, no offboarding process flags it. The transition from unsanctioned to orphaned is silent and automatic.
Non-human identities now outnumber human identities by 25 to 50 times in large organizations, and the majority of those NHIs were created locally inside applications, making them invisible to centralized IAM. AI agents are being created through the same app-local, ad hoc process. The orphan trajectory is already built into how they are deployed.
Understanding why orphaned and unsanctioned AI agents accumulate requires tracing the exact conditions that produce them.
Standard offboarding processes are built around human identity lifecycle events. When an employee leaves, IT disables their Active Directory account, revokes their SaaS licenses, and removes their access. What those processes do not cover is the machine identity the employee created on behalf of their work.
In Microsoft Copilot Studio, an agent is built using the creator's credentials. In Salesforce Agentforce, an agent may run using the creator's service account in maker mode. When the creator's human account is disabled, the agent's embedded credentials often remain valid. The agent continues to execute. The access persists.
One enterprise discovered 377 Copilot agents through a security assessment they did not know existed. Another found 2,500 agents already created before any inventory process was in place. Agent creation is fast. Agent discovery is not.
Low-code and no-code platforms have made agent creation accessible to every business function. Copilot Studio, n8n, and Salesforce Agentforce do not require engineering involvement. A business analyst can configure an agent with broad OAuth scopes in an afternoon.
Security teams are not in the loop during this process. The agent is not submitted for review. It is not added to a registry. It connects to production systems using whatever permissions the creator holds, and it starts operating immediately.
This is shadow AI at the agentic layer. Unlike a shadow SaaS app that passively receives data, a shadow agent takes actions. It reads records, writes updates, triggers workflows, and moves data across connected systems. The AI agent visibility gap this creates is not theoretical. It is the default state for most enterprise AI deployments today.
Agents created for pilots, experiments, or short-term projects are rarely decommissioned when the project ends. The creator moves on. The project is deprioritized. But the agent remains in the platform, its credentials still valid, its connections still live.
The result is a growing pool of de facto orphan agents with live access to production systems. No one is watching them. No one is responsible for them.
Orphaned and unsanctioned AI agents are not passive risks. They hold credentials, maintain connections, and in many cases continue executing scheduled tasks or responding to triggers. The risks they create are active.
Every AI agent is a non-human identity. It holds tokens, OAuth grants, or embedded service account credentials that grant it authority inside connected SaaS applications. When that agent becomes orphaned, the credentials do not expire. The access does not shrink. The effective authority the agent holds remains exactly what it was when the creator was still employed.
This is the core of the machine insider risk problem. AI agents act like insiders because they have the credentials of insiders. But no insider risk program covers them. The agent's behavior is not monitored against a baseline of expected activity. No one receives an alert when it accesses a record outside its original scope. No one questions why it is still running six months after its creator left.
Orphaned agents built in maker mode carry a specific escalation risk. In maker mode, the agent uses the creator's credentials for every action it takes. Any user who invokes the agent gains access to data at the creator's privilege level, regardless of their own permissions.
When the creator was a Salesforce administrator, the orphaned agent carries administrative-level access. A user without Salesforce provisioning can invoke that agent and extract CRM records they were never authorized to see. The agent did nothing technically wrong. IAM controls were bypassed by design. This is the confused deputy problem operating at scale, and it is invisible to every tool that does not correlate the runner's identity with the agent's inherited maker permissions.
Orphaned and unsanctioned agents create direct compliance exposure. Regulations including GDPR, HIPAA, and financial services frameworks require that access to sensitive data be authorized, documented, and reviewable. An agent with no owner, no audit trail of approval, and no record in any inventory fails all three requirements simultaneously.
When an auditor asks which systems accessed a specific dataset, an orphaned agent that touched that data will not appear in any access review. Its activity may appear in raw platform logs, but those logs do not identify the agent as orphaned, unsanctioned, or unowned. The compliance gap is structural, not incidental.
Security teams are not ignoring orphaned and unsanctioned AI agents. They simply do not have a tool designed to find them. Each existing category of security tooling has a structural gap that allows these agents to persist.
Identity and access management platforms are built around human identity lifecycle events. They track when a human account is created, modified, and deprovisioned. They do not track the machine identities that human created along the way.
When an employee is offboarded, IAM deprovisions their human account. It does not query Copilot Studio to find agents that used their credentials. It does not check Agentforce for service accounts tied to their profile. It does not know those agents exist. Non-human identities now outnumber human identities by 25 to 50 times in large organizations, and IAM programs that do not cover NHIs are missing the majority of the identities in the environment.
Cloud access security brokers see application usage. They can tell you that a user accessed Salesforce, that a file was downloaded, that a login came from an unusual location. What they cannot tell you is whether the entity accessing Salesforce was a human or an agent, who owns that agent, or whether the agent's creator account is still active.
CASB tools see the action. They do not see the agent identity behind it, the ownership chain above it, or the credential inheritance that made it possible. Ghost chasing configuration signals without runtime evidence of what actually happened is exactly the pattern CASB produces for agentic activity.
Native platform tools like Microsoft Purview provide logs for Copilot activity. Salesforce provides audit trails for Agentforce. But these tools are siloed by platform. They do not produce a cross-platform view of every agent in your environment.
More critically, they do not correlate agent activity with identity provider data. A Copilot Studio agent whose creator account was disabled in Azure AD three months ago will still appear as an active agent in the Copilot Studio interface. The platform does not know the creator is gone. It does not flag the agent as orphaned. It has no mechanism to do so.
The result is a visibility gap that no single-platform tool can close. Closing it requires a layer that sits above individual platforms and correlates agent configuration with identity provider state, effective authority inside each connected SaaS application, and real-time runtime behavior. That is the gap between theoretical configuration and runtime truth.
Closing the orphaned and unsanctioned agent gap requires a structured approach. The following framework addresses the problem in four operational steps.
No security program is possible without knowing what it is securing. The first requirement is a complete inventory of every AI agent operating across your environment, regardless of which platform built it.
That inventory must capture:
An inventory that captures only what agents are configured to do is a theoretical configuration map. Security teams need to know what agents can actually execute inside each connected system. That distinction is the foundation of AI agent governance.
Once the inventory exists, every agent must be matched against your identity provider. The question for each agent is direct: is the creator account still active?
Agents whose creator accounts are disabled should be flagged immediately as orphaned AI agents and treated as high-priority for review. The review must determine whether the agent is still needed, whether it should be reassigned to an active owner, or whether it should be deprovisioned.
Agents with no record in any approved registry are unsanctioned by definition. They require a risk assessment before any decision is made about continuation.
The offboarding process must be extended to cover machine identities. When a human account is deprovisioned, an automated check must query every AI agent platform for agents created by that account. Those agents must be flagged, reviewed, and either reassigned or deprovisioned before the human offboarding process closes.
This is not a manual process at scale. Organizations deploying hundreds of agents per week cannot rely on spreadsheet tracking or ad hoc investigation. The lifecycle policy must be automated and tied directly to identity provider events.
Every agent should have a named business owner, a technical custodian, a documented purpose, and an expiry date. Agents without all four attributes should not reach production.
Human access reviews happen on a quarterly cycle in most mature security programs. AI agents must be included in that cycle. The review should answer the same questions asked of human accounts:
Review QuestionHuman AccountAI AgentIs the account still needed?Is this employee still active?Is this agent still serving a business function?Is the access appropriate?Does this role match current responsibilities?Do the OAuth scopes match the agent's current task?Is the owner current?Is the manager still the right approver?Is the creator account still active?Is the access documented?Is the access request on file?Is the agent in the approved registry?
Agents that fail any of these checks require immediate remediation. Overpermissioned agents that pass the ownership check may still require scope reduction. The over-permissioned agent problem and the orphaned agent problem frequently appear together, and addressing one without the other leaves the blast radius intact.