Can I send user data to an LLM provider?

What to check before user data goes into prompts sent to a model provider's API, including provider terms, your own promises, sensitive data, and logging.

Short answer

Usually yes, if four things hold. The provider acts as your service provider under a contract that limits what it can do with the data. Your privacy policy discloses it. Sensitive data is handled with the consent it requires. And nothing you have already promised users says otherwise. Most problems come from the last two.

1. Check what you have already promised

Read your privacy policy, consent screens, and app store privacy labels before you build. If they say data is used only to provide specific features, or is never shared with third parties, an AI feature may require changes and notice to users first.

In February 2024 the FTC warned that quietly or retroactively changing privacy terms to allow new uses of data already collected, such as AI training, can be unfair or deceptive. Using existing data in a way that contradicts earlier promises can violate the FTC Act, and clear notice and affirmative consent are often what it takes to avoid that. An updated policy alone may not be enough.

2. Check the provider's terms for the plan you are actually using

The FTC has said model providers must honor their commitments about confidentiality, retention, and training, wherever those commitments appear: privacy policies, contracts, marketing, or marketplace listings. That protects you, but only if the commitments you rely on are actually in the terms for your account. API terms and consumer-app terms often differ, so read the ones for your account. Look for:

• Training: whether inputs and outputs are used to train models, and how to opt out if they are.
• Retention: how long prompts are kept, including for abuse monitoring, and whether zero-data-retention is available and turned on for your account.
• Data processing addendum: most providers offer one. Make sure it applies to your account.
• Region and subprocessors: where data is processed and who else touches it.
• Usage policies: restrictions on use cases such as medical advice, minors, or decisions about people.

3. Handle sensitive data separately

• Health data: Washington's My Health My Data Act excludes disclosures to a processor from "sharing" (which would need separate consent) when the processor uses the data to provide services consistent with the purpose it was collected for and disclosed to the user. That requires a binding processor contract setting out what the provider may do, and the provider has to stay within it; a provider that acts outside its instructions can become directly subject to the law. A provider that keeps your users' health data to train its general models, or passes it to others for their own purposes, should not be assumed to fall within the exclusion, whatever the contract calls it. The exclusion also doesn't remove your other duties on collection, security, and disclosure.
• Sensitive data under state privacy laws: most states with comprehensive privacy laws, including Virginia, Colorado, Connecticut, Oregon, Texas, and New Jersey, require opt-in consent to process sensitive data. California instead gives users a right to limit certain uses, and Utah and Iowa rely mainly on opt-out. If you rely on consent, make sure what users agreed to covers AI processing.
• Children: COPPA applies to child-directed services and to operators with actual knowledge that they collect personal information from children under 13. The FTC's amended COPPA Rule took effect June 23, 2025, and most companies had to comply by April 22, 2026. It requires separate parental consent for certain disclosures to third parties, including for targeted advertising, covers biometric and government identifiers, bars keeping children's data indefinitely, and adds security requirements. Check both your own obligations and those of any provider that receives children's data through your product.
• Financial and government ID data: keep it out of prompts unless the feature needs it.

4. Find every copy

Prompts are often copied to more places than the model provider: your application logs, an LLM observability tool, an analytics event, an error tracker. Each copy is data your privacy policy has to account for, and each vendor needs its own contract.

5. Look at the outputs too

• Tell users when they are getting AI-generated responses.
• Be careful with output that looks like medical, legal, or financial advice.
• California and New York regulate AI companion chatbots, with disclosure, crisis-response, and minor-safety requirements, and Utah regulates mental health chatbots. If your feature is a coach, companion, or confidant, check these laws.
• If output affects consequential decisions about people (employment, credit, housing, insurance, health care, education), Colorado's Automated Decision-Making Technology Act, effective January 1, 2027, requires notice, explanations of adverse decisions, and human review. Other states have similar rules.

Checklist an agent can run against the codebase

• Find the code that builds prompts and list every user field it includes.
• Find the provider client configuration: model, account or project, retention and zero-data-retention settings.
• List every place prompts or responses are logged, traced, or sent to analytics.
• Check whether any prompt can contain health, financial, children's, or ID data.
• Compare the results to the privacy policy, consent screens, and app store privacy labels, and flag any mismatch.

If this applies to you

An AI feature review covers the provider's terms, your disclosures and consent, the state laws above, and a build spec for the AI data path. If you are switching or adding a provider for an existing feature, a pre-build feature check covers that one change.