When AI Agents Act for Us: Rethinking User Consent

Every day, we use various applications for work, personal tasks, and entertainment, and many of them now interact with each other. One app might read your data, while another acts on it.

When you allow one application to act on your behalf in another system — often across different vendors — you need clear control over what it can do.

That control is called consent. Consent defines exactly what an application is allowed to do on your behalf. As LLM-powered AI agents increasingly take actions across systems, getting consent right becomes critical.

What is User Consent and How Does it Benefit Users?

In applications and digital systems, consent refers to explicitly granting an application privileges. When a user allows one application to access their data or act on their behalf in another system, they should clearly understand:

• Which application is requesting access
• Which application will be accessed
• What data can be read
• What data can be changed
• How long will that access last

Explicit user permission is typically required when the applications involved are owned by different vendors — what we commonly refer to as third-party applications. In some cases, this also applies to applications from the same vendor when they have different terms or policies.

In particular, when a user creates an account with company A, they already consent to how that company processes their data. But when an application wants to access APIs owned by another company, the user should have explicit control over that decision.

That control is exercised through a consent screen. It must provide enough information for the user to make an informed choice, without overwhelming them or being vague, so that the choice becomes meaningless. Designing that balance is one of the hardest parts of consent.

Consent in the Context of AI Agents

Technically, an AI agent is just another API client. Practically, it’s different. Traditional applications behave predictably because users directly control their actions. Agents, by contrast, introduce autonomy as they may decide what actions to take to complete a task.

That autonomy creates risk as agents can take unexpected actions, whether due to model errors or from an AI-Agent attack. As such, AI agents should always be treated as third-party applications that require explicit user consent. This means users should provide explicit consent whenever they delegate access to an AI agent. That consent keeps users informed about what the agent can do and for how long. It ensures users stay in control of agent actions and helps prevent unintended behavior.

Best Practices for Granting AI Agents Access to APIs

The following best practices describe how users should approach consent when working with AI agents. For users to act this way, however, AI application vendors and API providers must design their systems to support these behaviors. While framed from a user’s perspective, these recommendations primarily serve as guidance for vendors.

Limit Agent Privileges by Default

Always follow the principle of least privilege. Give AI agents only the permissions required to perform the specified task. This reduces the impact of misuse or unexpected behavior. It’s safer to increase privileges progressively — granting additional access only when needed — than to allow broad, over-privileged access from the start.

Ensure Consent Is Time-Limited

Consent should always expire. Ideally, it should be valid only for the duration of a request or session, requiring the agent to request new tokens when needed.

Importantly, re-consenting should not require reauthentication. Vendors should allow users to control how long consent lasts. For long-running or background tasks, users may choose to grant longer-lived consent intentionally.

Require Re-Consent for High-Privilege Actions

If an agent needs to perform actions beyond the scope of its original consent, APIs should deny the request and trigger a step-up flow. The user can then explicitly approve the higher level of access, and the agent can receive a new token with expanded privileges. This guarantees that sensitive operations always require fresh, explicit approval.

Support Customizable Consent

Consent should not be all-or-nothing. Vendors should allow users to configure the contents of consent. When a user approves a scope, additional claims can be included in the access token, some of which are derived directly from user input. This makes it possible to express constraints such as transaction limits or time windows, giving users finer control over how agents operate.

Allow Consent Revocation at Any Time

Long-lived consents must be manageable. Users should be able to revoke consent at any point, for example, if an agent is no longer needed or is suspected of being compromised. Revocation should invalidate refresh tokens and, ideally, immediately revoke active access tokens as well.

Conclusion

Today’s consent experiences are often inadequate: too vague or too rigid. As AI agents become more capable and autonomous, getting consent right becomes critical.

Users must be able to make informed decisions, but that’s only possible if vendors provide the right tools. AI application developers and API providers alike need to design for explicit, granular, and revocable consent to keep the ecosystem secure.

Learn more about how Curity helps secure IAM in the age of AI.