State of Practice Reputation 2026: Can AI find you?

The short version

You ran a full book yesterday. The dentistry was good all day. Last night one missed phone call became a one-star review, and the review is not about any of the clinical work.

The comfortable belief is that if the clinical work is good, the reviews take care of themselves. This report tests that belief against 2.96 million reviews. Patients in this data praise the dentistry constantly, and they hand out one, two and three stars while doing it.

The pages below cover what patients praise, what they fault, what happens when problems pile up, which signals practices miss, and how to run the same diagnosis on your own reviews.

Compliments inside the complaint

The assumption: patients will tolerate a bad experience as long as the care is good. The data: patients split the two. Praise for the dentist, lost stars for the desk.

More than a third of three-star reviews contain a compliment for the dentist. The rating and the care have come apart, and the patient says so in writing.

Most complaints are not about the dentistry or the bill

The assumption: when patients complain, it is about the dentistry or the cost. The data: half of all complaint content is about the front office.

Counted by review instead of by content, 76.9% of negative reviews mention at least one front-office problem. Cost ranks seventh among complaint themes, below front-desk attitude, billing surprises and wait times. When money shows up, it is usually a bill that did not match the estimate, not the fee itself.

Billing draws nearly twenty complaints for every compliment. Nobody writes a five-star review because the bill matched the estimate. On Google these systems have no upside. They can only lose you stars.

The second miss

The assumption: one bad day will not cost us the relationship. The data: patients forgive one problem. At two, most talk about leaving.

Each added problem roughly doubles the odds a patient says they are looking for a new dentist. A patient does not experience scheduling, billing and phones as separate departments. It is one visit and one practice, and the review records the stack as a single experience. Leaving language counts phrases like never going back and finding a new dentist.

Two kinds of silence

The assumption: if something were wrong, I would hear about it. The data: unhappy patients often say nothing, and hear nothing back.

Two out of three four-star reviews with text state no complaint at all. Somebody liked the practice, withheld a star, and declined to say why. The second silence belongs to practices.

Five-star reviews receive replies more often than one-star reviews. The replies most likely to be written are the ones needed least. Responses have two audiences: the patient who wrote the review, and every prospective patient who reads it afterward.

Can AI find you?

Reviews used to decide whether a patient picked you from a list. Now they decide whether you make the list at all.

When a patient asks ChatGPT or Google AI for a dentist near them, the answer is built from what is already written about your practice online, and the largest body of that writing is your Google reviews. The complaints in this report are no longer only lost stars. They are the raw material an AI reads before it decides whether to recommend you.

A practice with a front-office pattern in its reviews, double bookings, unanswered phones, surprise bills, is a practice the AI has reasons to skip. A practice that answers its reviews and fixes the systems behind the complaints gives the AI reasons to say its name.

The full section on reputation and AI discoverability, with data on how AI assistants weigh reviews, is being added for the October 21 release of this report.