Short answer. AI agent authentication works the way an app signs in. An agent can't type a password or answer an MFA prompt, so it presents a credential issued to it, such as an API key or a token that expires after a short time. When it acts for a person, the request also carries that person's identity, so each system knows which agent acted and for whom.
Many questions about agent authentication start with a practical problem: connecting an agent to real tools without handing it a key or a password. Teams also want that access to be easy to limit and revoke, with a record of which agent acted for whom.
Many agents authenticate with a stored API key or a person's own token
The quickest way to connect an agent is to paste an API key or a personal token into its configuration. It works, but the key often ends up in config files and environment variables, and anyone who copies it can use it from anywhere. A personal token also gives the agent everything that person can reach, and the logs show only the person.
Agents that act for a person sign in through that person, and scheduled agents use their own credential
Practitioners usually split agents into two groups. An agent people use, such as a sales assistant, signs in through each person with their work login, so its requests carry that person's identity and stay within their access. A background agent that runs on a schedule, such as a nightly sync, has no person behind it and uses a credential issued to the agent itself, limited to that one job.
Credentials can stay out of the agent entirely
Some teams keep credentials away from the agent altogether. The service credentials sit in one place, and the right one is attached to each request as it passes through, based on the agent and the person it acts for. When no key is stored in the agent's configuration, a leaked config file doesn't expose a credential, and revoking the agent stops it at its next request.
Authentication proves who is calling, and each tool call still needs its own check
A valid credential tells a tool which agent is calling and for whom. It doesn't decide whether that agent should run a delete or an export right now. That takes a check on each tool call against policy before it runs, which is where many teams start limiting what agents can do.
Frequently Asked Questions
Can an AI agent use MFA?
Not in the usual sense, since no one is there to answer a prompt. The person's MFA applies when they sign in to connect a service. After that, the agent works with credentials attached to each request and checked against that person's access, which leaves no stored login in the agent for an attacker to reuse.
What is the difference between AI agent authentication and authorization?
Authentication proves which agent is calling and who it acts for. Authorization decides whether that agent can take a specific action right now, such as reading a record or sending an email. Many teams check authorization in real time on each tool call, since a valid login says nothing about whether one action is safe.
What is agent-to-agent authentication?
When one agent calls another, each call needs to show which agent is calling and which person the chain started with. If that person's identity isn't passed along, the second agent acts with its own access and the log loses track of who asked.