Why Your Company AI Agent Needs Its Own Identity and Accounts

An AI agent needs its own identity because every action it takes should be traceable to the agent, limited to what its role requires, and removable without disturbing a person's account. In practice, that means a dedicated account or service identity for each agent, with scoped permissions, its own credentials, a named human owner and a log of what it did. Borrowing an employee's login is faster on the first day, but it hides who acted, grants more access than the task needs and breaks when that person changes role or leaves.

Key takeaways

• Give each agent a dedicated identity, separate from every employee, so each action is attributable to the agent and to the human who owns it.
• Scope access to the role. Start with read access, add drafting, and allow sending or writing only where an approval boundary exists.
• Keep credentials in a managed secret store, rotate them on a schedule, and name a human owner and a backup for every agent identity.
• Record which identity did what, on whose request and with which approval, so reviews and investigations rest on evidence.
• Plan for revocation. You should be able to switch off one agent without touching a person's account or any other agent.

What does it mean for an AI agent to have its own identity?

Identity is the answer to the question every system asks before it does anything: who is asking? When a person opens the CRM, the CRM sees a user with a role. When an agent updates the same CRM, the system should see an account that belongs to the agent, with a role designed for the agent's job.

A dedicated identity usually has five parts. First, a name that makes the agent recognizable in logs and in other people's inboxes. Second, credentials that belong to it alone. Third, permissions in each tool it touches, set for the role and nothing more. Fourth, a named human who is accountable for it. Fifth, a lifecycle: creation, periodic review, credential rotation and retirement.

The form varies by tool. Some products support service accounts or application credentials. Others only understand user seats, so the agent gets a seat of its own, labeled clearly as an agent. Some allow delegated access through OAuth, where the agent acts for a specific person under consent limited to named scopes. All three are legitimate, and all three are different from typing an employee's password into a system and hoping nobody notices.

Why is borrowing an employee's login a problem?

It looks harmless because it works immediately. The costs show up later, and they tend to show up together.

• Attribution disappears. The log says the employee sent the message or changed the record, and nobody can tell whether the person or the agent did it. When something goes wrong, the first hour is spent working out who acted.
• Access is too wide. An employee's account reflects everything that person might need across their work, not what one agent task requires. The agent inherits all of it, including systems it should never see.
• The agent inherits the person's life. Password changes, multi-factor prompts, a new role, a leave of absence or a departure all affect the agent. Either it stops working at a bad moment, or it keeps working with access that should have been removed.
• Security controls get weakened. To make a login usable by software, teams often exempt it from the checks that protect human accounts, such as a second factor. That exemption then sits on a powerful account.
• Incident response gets harder. To stop the agent you have to lock a person out. To keep the person working you have to leave the agent running.
• Access reviews lose meaning. A review that cannot separate human activity from agent activity cannot answer whether the access is still appropriate.

The common thread is that a shared login erases a distinction you will eventually need: what a person decided versus what an agent did on their behalf. Authorization guidance such as the OWASP Authorization Cheat Sheet treats clear, enforced permissions per principal as a baseline. An agent is a principal too.

What should a dedicated agent identity look like in each tool?

The right form depends on what each tool supports. Use this decision guide, tool by tool.

• Use a service account or application credential when the tool supports one and the agent works on a schedule or in response to events, such as reading a shared folder or posting to a ticket queue.
• Use delegated OAuth with narrow scopes when the agent must act for a specific person, for example preparing a draft in that person's calendar, and the person can see and revoke the consent at any time.
• Use a dedicated user seat, named as an agent, when the tool has no service account concept. Treat it like a service account: no shared password in a team chat, no personal phone as the second factor.
• Use a person instead of an account when the action is rare, high impact or hard to reverse. The agent prepares the work and a human executes it.
• Never use an employee's personal login. If a tool offers nothing else, that is a reason to reconsider the integration or to put an approval step in front of it.

Whichever form you pick, apply least privilege: begin with the smallest access that lets the role function and widen it only when real work shows a need. The same habit appears in authorization guidance as deny by default and check every request.

How do you set up an agent identity, step by step?

This plan works for a first agent and scales to later ones. Do the steps in order, because each one depends on the one before it.

• Write the role in one sentence, then list the tools and data it needs to do that job. If a tool is not on the list, the agent gets no account there.
• Create one identity per agent in each tool, named so that anyone reading a log understands it, for example the role name followed by the word agent. Use separate identities for testing and for production.
• Assign permissions in tiers. Grant read first, then the ability to draft, and only then the ability to send or write, following the logic in read, draft and send as three different permissions.
• Store credentials in a secret store, never in prompts, shared documents or the agent's memory. A credential the agent can read is a credential that a malicious instruction hidden in a document might coax out.
• Name a human owner and a backup. They approve access changes, receive alerts about the identity and answer for it in reviews.
• Write the approval boundaries: which actions the agent may take alone, which need a person to confirm, and which it may never take.
• Turn on logging that captures the identity, the action, the target, the request that triggered it and any approval, as described in what to log for AI agent observability.
• Schedule credential rotation and access reviews, then write down the revocation procedure and rehearse it once, so that removing the agent is a known five-minute task and not an improvisation.

What does this look like in a real workflow?

Illustrative scenario: a small distribution company wants an agent to triage its support mailbox, look up order status and draft replies for a person to approve.

In the first version, the operations manager gives the agent her own mailbox login and order-system password. It works the same afternoon. A few weeks later she moves to a different team and her permissions change. The agent loses access to the order system, drafts incomplete replies, and nobody connects the two events for days. Meanwhile her account still carries rights to billing and contracts that the agent never needed.

In the second version, the company creates a support agent identity. It has read access to the shared support mailbox, read access to order status, and permission to save drafts but not to send. A named support lead owns it, with the operations manager as backup. Every draft is logged under the agent's name with the order it looked up. When the operations manager changes teams, nothing happens to the agent. When the company later wants to allow automatic replies to one narrow category of question, that is a deliberate permission change with an owner's approval, recorded in the log.

The work is the same in both versions. What differs is that the second is accountable, bounded and easy to change.

How does Be Human handle agent identity and accounts?

In a first engagement, Be Human defines one useful role, the tools and memory it needs, and the approval boundaries around it. For that role it sets up a dedicated identity in each connected system, with permissions limited to the agreed scope and credentials kept outside prompts and memory. Under managed operations, recurring work includes permission review, credential rotation, monitoring of connection health, integration maintenance and incident response, including revoking one agent's access without affecting any staff account. Access decisions stay with named people at the company, and when a connection expires or is revoked the agent stops and reports instead of improvising, as covered in what an agent should do when a connection expires.

Which mistakes should you avoid?

Most identity problems with agents come from a short list of habits that feel convenient.

• Sharing one identity across several agents. When two agents use the same account, you lose the ability to tell them apart or to remove one without the other.
• Granting broad access to avoid early friction. Wide permissions are easy to give and rarely taken back.
• Leaving the owner field empty. An identity nobody owns will not be reviewed, rotated or retired.
• Putting secrets into instructions or documents. Anything the agent can read can end up in an output, a log or a manipulated response. The OWASP Top 10 for LLM Applications discusses these risks in detail.
• Skipping the revocation drill. A procedure that has never been tried tends to fail when it is needed most.
• Treating the identity as a one-time setup. Roles change, tools change and permissions drift, so schedule reviews.

Frequently asked questions

Can an AI agent just use a shared team account? A shared account removes the one thing you need most when something goes wrong, which is knowing who acted. It also means the access is shaped by what the team needs overall, not by the agent's role. Give the agent its own identity and keep shared accounts for humans who can answer for their actions.

Does every tool need a separate agent account? Every tool the agent touches needs an identity the agent can act under, but the form can differ: a service account in one tool, a labeled seat in another, a narrow OAuth consent in a third. What matters is that each one is dedicated, scoped and traceable to the same agent. If a tool offers no safe way to do this, keep a person in the loop for that step.

Who should own an agent's identity? A named person in the team that uses the agent, with a backup, should own it. They approve permission changes, receive alerts and join access reviews. Ownership by a department alias or by nobody tends to mean no review at all.

What happens to the agent when an employee leaves? Nothing, if the agent has its own identity. Its credentials, permissions and logs are independent of any individual, so staff changes do not interrupt it or leave hidden access behind. Only the human owner role needs reassigning, which is a small, planned change.

Be Human editorial guidance. Examples are illustrative unless explicitly attributed. Sources provide background; implementation choices depend on your workflow.