Guide

Consumer chatbot AI disclosure checklist

Track evidence for customer-facing AI chat, support, sales, advice, companion, and patient communication experiences.

Consumer chatbot review should connect external AI experiences to disclosure text, escalation paths, owner review, jurisdiction scope, and operational evidence.

Identify the external user experience

Start with the surface a consumer sees: support chatbot, sales assistant, claims helper, financial or health advice flow, AI companion, or patient communication experience. A backend model route matters, but the user-facing disclosure obligation usually starts with the experience.

Attach disclosure and escalation evidence

Useful evidence includes the exact disclosure text, where it appears, when it appears, which product owner approved it, and how a user can escalate to a human. Gateway or app telemetry can prove the experience exists, but the disclosure copy is often customer-attested.

Keep federal pointers thin

Tallin should point consumer-impacting claims to FTC or sector counsel review without pretending to decide the law. The product's job is to package the AI-system context and evidence so counsel can review it faster.

Key takeaways

  • Track consumer-facing experiences, not only backend model providers.
  • Attach the exact disclosure copy and human-escalation path.
  • Use Tallin evidence for routes, owners, and activity where available.
  • Treat federal and sector obligations as review pointers, not Tallin verdicts.

Turn AI evidence into a ledger.

Start with a free AI Exposure Assessment, then replace estimates with observed and inferred signals from your own workspace.