Which questions should the website AI chatbot handle?
Begin with the questions people actually ask and the documents the business is willing to stand behind. Then design the limits of the answer.
Group incoming questions by decision. A visitor may ask what a service covers, how to start, what information to prepare, or where to find support. Those questions can often use public, stable website content. Questions about a specific account, order, contract, or regulated advice require different permissions and may be better handed to a person.
Pick an initial narrow scope. For each question, identify the approved source, answer owner, and review trigger. If no approved source exists, create one or exclude the topic. A chatbot trained on a messy folder of outdated drafts can make the confusion sound confident. Better retrieval cannot fix authority that the business has not defined.
What counts as an acceptable answer?
Write examples of a good answer, an incomplete answer, and a question the bot should decline. A good answer names the relevant service, explains the next step, and links to the source page. An incomplete answer says what it can confirm and directs the visitor to a person for the missing detail. Do not let the bot invent a package price or promise a result to avoid saying it does not know.
NIST’s AI Risk Management Framework offers a useful model for defining an AI system’s context, measuring behavior, and governing changes. Apply that idea practically: assign an owner, test representative questions, and review failures rather than treating launch as the end of quality control.
How will the knowledge stay current?
Choose a source of truth. Public service pages, owner-approved FAQs, and current process documents may have different update cycles. Record which content can feed public answers and which stays private. When a service changes, there should be a clear way to update or remove the old answer before it misleads visitors.
Test with ambiguous wording, misspellings, conflicting source passages, and a request for information outside the approved scope. Review whether the bot cites the right page, preserves uncertainty, and points to a human when needed. Do not score it only on how often it responds. Sometimes the correct behavior is to stop.
What information should it collect?
If the bot collects a lead, define the minimum fields and what consent and privacy notice the organization approves. Separate public guidance from personal account support. A general website assistant should not request sensitive information simply because a visitor volunteers it. Define retention, access, and deletion through the business’s reviewed data process.
Build a test set before the pilot.
Bring ten common questions, their approved source pages, and three out-of-scope examples. That provides a test set for a pilot. See AI chatbot development for the service path. Talk to a Specialist to define a useful assistant with boundaries your team can maintain.
