Customer-facing AI needs a defined job. “Answer anything about our business” creates a broad responsibility that is difficult to test. “Collect appointment preferences and pass unanswered questions to reception” gives the team a manageable starting point.
Before configuration
- Define the permitted tasks and prohibited commitments.
- Identify the information source and its update owner.
- Decide what information is necessary to collect.
- Set human handoff triggers and response expectations.
- Provide a manual route when the system is unavailable.
Before customer use
Test normal questions, incomplete details, requests outside service scope and questions the business cannot answer. Include repeated contacts, changed appointment preferences and attempts to get the assistant to ignore its rules.
Check the whole workflow. An accurate conversation is not a success if the booking lands in the wrong calendar or the customer record is duplicated. Confirm that a person can trace the outcome and correct it.
During the trial
Review a sample of interactions and all significant failures. Measure correct task completion, handoff quality, correction time and customer complaints. Choose thresholds and a stop condition before evaluating the results.
Keep the initial scope narrow and expand it only after checking evidence. Do not promise error-free operation. The team should understand the system's limits and know who can change them. For existing clinic workflows, use the site's reception-model and enquiry-routing guides to define the administrative boundary before selecting a tool.
Existing guides: Clinic enquiry routing · Reception model · Pilot design.