A practical guide to approved-content AI support

Start with the questions, not the software

List the straightforward questions customers and prospects already ask. These are usually about availability, eligibility, process, access, delivery, payment or policy. The first version does not need to cover every situation; it needs to handle a useful, well-defined set reliably.

Match each question to the page, help article or document that contains the current answer. If the answer only exists in someone's inbox or memory, write and approve it before expecting an assistant to use it.

Decide what the assistant may use

A public website often contains old campaign pages, legal notices, navigation text and content that is not suitable as a customer answer. Review discovered pages, exclude irrelevant areas and approve only the sources you are prepared to stand behind.

• Prefer current, customer-facing guidance with a clear owner.
• Remove duplicate or contradictory versions of the same policy.
• Keep individual decisions and sensitive cases out of general automated answers.
• Record where a person should take over when published guidance is insufficient.

Design the honest fallback

An AI assistant should not turn missing knowledge into a confident guess. Define a short fallback that explains the limitation and gives the visitor a real contact route. Test questions that should fall back as deliberately as questions that should be answered.

Review after launch

Conversation review is not just quality control. Repeated unanswered questions show where customer guidance, onboarding or website navigation needs improvement. Update the source, approve it and test the answer again rather than patching the wording in isolation.