Best Practices for User Consent in the Age of AI Agents

Read full article from Curity here:  https://curity.io/blog/user-consent-best-practices-in-the-age-of-ai-agents/?utm_source=nhimg

Every day, we use a variety of digital systems, applications, and websites—whether for work, personal tasks, or entertainment. Many of these systems are interconnected: you might use one app to aggregate data and another to act on that data.

Imagine an application that books a restaurant table and automatically adds a reminder to your calendar. Whenever you delegate access from one application to another—especially across different vendors—you want to remain in control of what actions are allowed. This is the essence of user consent.

With the rise of autonomous AI agents—LLM-powered applications that can perform tasks on your behalf—the need for robust consent management has never been greater.

What is User Consent and Why Does It Matter?

Consent is the explicit granting of privileges to an application or system. When you allow one application to access another, you should be fully aware of:

• Which application is requesting access
• Which application will receive access
• What data can be read or modified
• How long the access lasts

For third-party applications (applications from different vendors), explicit consent is critical. In contrast, when the applications belong to the same vendor, consent is often already implied in the account creation process.

A well-designed consent screen should provide clear, concise information to help users make informed decisions. For example, GitHub provides a consent interface that clearly displays the requested permissions, reducing the risk of impersonation or over-privileged access.

Additionally, users should have the ability to manage and revoke consents. This includes:

• Reviewing which applications have access
• Revoking access when it’s no longer needed
• Ensuring compromised applications cannot continue accessing your data

The Impact of AI Agents

AI agents are the next evolution in digital applications. Unlike traditional apps, AI agents can act autonomously:

• Place orders or bookings
• Send emails or fill forms
• Modify data across applications

Technically, an AI agent is just another API client—it needs credentials (e.g., access tokens via OAuth) to act on the user’s behalf. However, agents differ from typical apps because they can act without direct user interaction. This introduces new risks:

• Agents may take unexpected actions to “complete” a task.
• They might be tricked via prompt injection or hallucinate actions.
• Users may lose granular control over what actions are performed.

This makes robust consent management essential when granting AI agents access.

Fine-Grained Permissions

Consent for AI agents must be more granular than usual:

• Agents should only receive the permissions required for the specific task at hand.
• For example, if an agent is reading emails to label them, it should not be allowed to delete or send emails.
• APIs must support fine-grained scopes to enforce this principle of least privilege.

Time-Limited and Transaction-Based Consent

Unlike traditional applications, consent for AI agents should be time-limited and ideally per transaction:

• Consent should automatically expire, preventing long-term unauthorized access.
• Users may need to grant consent repeatedly for new actions or requests.
• This ensures the agent cannot gain unexpected or ongoing access.

Balancing Usability with Security

Frequent consent prompts may frustrate users, but over-privileged, long-lived consents are a security risk. Vendors must strike a balance:

• Avoid overwhelming users with repeated requests
• Prevent granting excessive permissions at once

Best Practices for AI Agent Consent

Here are some key best practices for interacting with AI agents and granting API access:

1. Limit API Privileges
   • Always follow the principle of least privilege.
   • Grant only the minimal permissions required for the task.
2. Ensure Consent Expires
   • Use short-lived, transaction-based consent where possible.
   • Reauthenticate only when necessary; users should choose how long consent is valid.
3. Reconsent for High-Privilege Operations
   • For actions outside the original consent scope, trigger step-up authentication.
   • Issue new tokens with the necessary higher privileges only after explicit user approval.
4. Customize Consent Options
   • Allow users to tailor consents with additional conditions, such as transaction limits or time constraints.
   • Support claims issued to access tokens based on user-defined input.
5. Enable Revocation of Long-Lived Consents
   • Users must be able to revoke consent at any time.
   • Revoking consent should invalidate refresh tokens and ideally active access tokens.

Conclusion

Consent screens in today’s systems are often inadequate—they may be too vague, too complex, or lack proper management options. With AI agents becoming more autonomous, robust and fine-grained consent mechanisms are critical.

Users retain control over AI actions only if vendors provide the right tools. Backend and AI agent vendors must ensure:

• Granular API scopes
• Transaction-based or time-limited consents
• Easy consent management and revocation

Properly implemented, consent management empowers users while maintaining security, even in the age of autonomous AI agents.