Most clinics evaluate automation by the demo: the AI responds well, the flow feels smooth, the price fits the budget. That tests whether the product works on a showroom floor. It doesn't test whether it solves the operation's real problem.
The first question that matters is about integration: does the system talk to the scheduling and records tools the clinic already uses, or does it require switching tools to work? Automation that creates a parallel system tends to get abandoned within a few months.
The second is about handoff to a human: at exactly what point does the conversation leave the AI and reach someone on the team, and is that transition visible to the patient, or does it feel like the system failing?
The third is about data: where is patient information stored, for how long, and who has access. In healthcare, that answer can't be vague.
The fourth, and the most overlooked: what happens when the AI doesn't know how to respond. A good vendor shows you the failure behavior before showing you the success behavior.
The last question, and maybe the most practical one, is about real implementation time: how long until the system is actually running in the clinic's day-to-day, not in an isolated demo, and what the clinic needs to do in the meantime besides sign a contract.