How to choose a dental AI receptionist: test the handoff, not just the voice

1. Define the job before comparing vendors

Write down the problem in operational terms. “We need AI” is not a testable requirement. “We need an after-hours appointment request to reach the next morning’s worklist with the correct visit type and a responsible person” is. If direct booking is required, say what must be confirmed before the patient hears that the appointment is booked.

Distinguish call answering, message taking, appointment requests, and confirmed scheduling. They can all be useful, but they are not interchangeable. A vendor that reliably collects a request may fit an overflow workflow even if it cannot complete a booking. A direct-booking product needs a different level of integration and exception testing.

List the tasks that remain with staff: clinical decisions, disputed charges, unusual scheduling exceptions, and any request outside the approved scope. This prevents an evaluation from quietly assuming that software replaces the entire front-desk role. It also gives the vendor a fair boundary to demonstrate.

2. Ask what “integrates with our PMS” actually means

A logo on an integrations page is not a description of a workflow. Ask which product version, hosting setup, permissions, and actions are supported. Reading availability, creating a new appointment, changing an appointment, and updating a patient record should be demonstrated separately.

Open Dental’s appointment API, for example, documents separate operations for finding slots, creating appointments, and updating them. Its slot-search documentation also explains differences between search methods. This is a useful illustration of why “API access” and “the right scheduling behavior for our practice” are different questions.

In your demonstration, inspect the destination record. Confirm the intended provider, location, operatory, visit type, duration, and time. Ask what happens when another booking takes the slot between the search and confirmation. If the integration times out after sending a change, the system should not blindly repeat an action whose result is unknown.

Treat unresolved outcomes as a product capability to evaluate, not an embarrassing edge case to skip. Ask how staff identify an uncertain booking, check the source system, and reconcile the request. Do not infer that a vendor implements these controls because its underlying PMS provides an API.

Source: Open Dental

3. Test the awkward calls as well as the easy ones

Give every vendor the same fictional scenarios and expected outcomes. Keep real patient data out of an unapproved demonstration. Begin with a normal booking, then vary one condition at a time so the reason for a failure is visible.

Test ambiguity: two patients with similar names, a caller who changes the requested date, or a request for “the usual appointment.” The desired result may be a clarifying question or a staff handoff, not a confident booking. Specify that result before the demo rather than deciding afterward that whatever happened was acceptable.

Also test service interruptions. A disconnected call, an unavailable staff destination, or a scheduling-system outage should leave a recoverable state. Ask the demonstrator to show the worklist entry and explain who will review it. A reassuring spoken response does not prove that the work reached anyone.

• Two callers request the same remaining slot.
• A caller asks for a person during unstaffed hours.
• The patient requests a change after the original appointment is identified.
• The scheduling system rejects a write or returns no clear result.
• The caller asks a clinical question outside the agent’s approved role.
• The call ends before the patient confirms the proposed time.

4. Use a scorecard with gates, not a vague star rating

Use four evidence states: not demonstrated, demonstrated with a gap, passed in a controlled test, and verified during the agreed pilot. This is an internal decision aid, not a universal ranking formula. Keep a link or record identifier for the evidence supporting each result.

Do not average a serious problem out of existence. Privacy approval, incorrect identity matching, inappropriate clinical responses, and bookings made without confirmation should have explicit acceptance criteria. The responsible practice team decides which failures block release and which can be addressed by narrowing the scope.

For the remaining criteria, choose weights before the pilot. An after-hours message service and a multi-location booking workflow have different priorities. The scorecard should express those priorities, rather than reward a large feature list that the team will not use.

5. Review the deployment, not just a compliance badge

HHS guidance says that a cloud provider handling electronic protected health information on behalf of a covered entity can be a business associate, even when it cannot decrypt the information. It also describes the need for appropriate agreements and risk analysis. A badge or a vendor’s willingness to sign a BAA does not replace reviewing the actual arrangement.

Ask where audio, transcripts, appointment details, and support logs travel. Identify the organizations involved, who can access the data, how long each type is retained, and what happens when the service ends. Give those answers to the people responsible for privacy and security decisions in your practice.

Do not ask a sales demonstration to settle jurisdiction-specific recording, consent, or healthcare-law questions. Have your advisors approve the applicable workflow and caller wording before real use. This guide is an operational checklist, not legal advice or a certification of any product.

Source: U.S. Department of Health and Human Services

6. Make the pilot reversible and the decision specific

Start with a defined location, call window, and task set. Record the current process first: unique requests, completed bookings, unresolved handoffs, staff correction time, and caller requests for a person. Use comparable definitions during the pilot so an improvement in one metric does not hide a worsening in another.

Agree who reviews exceptions, how often, and how the team can return calls to the existing process. Describe the rollback path in plain language. If the connection fails on a busy morning, the front desk should not need to discover the fallback from a contract or a developer’s inbox.

At the decision meeting, separate measured results from expectations. A vendor may have passed booking tests but still lack an approved after-hours transfer arrangement. The appropriate decision could be to launch only the tested scope, extend the pilot, or stop. A qualified “not yet” is more useful than a blanket success label.

Ethon supports appointment-booking and care-coordination workflows, but the relevant question is what can be configured and verified for your practice. Use the same scorecard for an Ethon walkthrough. Confirm the exact integration actions, staff boundaries, and deployment requirements instead of treating this guide as evidence that a specific implementation has passed.