Reviews still decide who gets chosen. A survey by BrightLocal, a company that sells review and local-marketing software, asked 1,002 US adults about local businesses and found that “97% of consumers read reviews for local businesses” . The same vendor survey found that “89% of consumers expect business owners to respond to reviews” . People read them. People expect you to answer them. And people are no longer the only readers. A second BrightLocal vendor survey describes consumers “fact-checking reviews cited by AI tools” . Your reviews now feed two audiences at once.
That raises the stakes on both sides. AI makes it cheap to ask for reviews and cheap to answer them. It also makes it cheap to fake them. The FTC said as much in its Operation AI Comply announcement, describing one target this way: “Rytr has marketed and sold an AI ‘writing assistant’ service for a number of uses, one of which was specifically ‘Testimonial & Review’ generation” . Announcing those actions, then-Chair Lina M. Khan said: “The FTC’s enforcement actions make clear that there is no AI exemption from the laws on the books” . If you run a dental practice, that sentence is the whole article. The rest is detail.
Questions this article answers
SAQ: the questions you should be asking (and nobody is)
- Who in our practice has written authority to post a review reply, and who checks it for patient details first?
- Could any part of our review request be read as implying a reward for a positive review?
- If a regulator asked for every review request and reply we have sent, could we produce them?
- Do we know which of our reviews AI tools are reading, and what they say about us in aggregate?
Fake it and the FTC will find you.
The video for this article is in production.
What the FTC banned
In August 2024 the FTC announced a final rule on fake reviews and testimonials . In the agency’s words, the rule “addresses reviews and testimonials that misrepresent that they are by someone who does not exist, such as AI-generated fake reviews, or who did not have actual experience with the business or its products or services, or that misrepresent the experience of the person giving it. It prohibits businesses from creating or selling such reviews or testimonials” . The rule also allows the agency “to seek civil penalties against knowing violators” .
The regulation itself is 16 CFR 465.2. Paragraph (a) makes it a violation “for a business to write, create, or sell a consumer review, consumer testimonial, or celebrity testimonial that materially misrepresents, expressly or by implication: (1) That the reviewer or testimonialist exists; (2) That the reviewer or testimonialist used or otherwise had experience with the product, service, or business…” .
So, is it legal to use AI to write reviews? Not reviews that pretend to come from a customer. A review from a person who does not exist is banned . A review from a person who never had a real experience with your practice is banned . The FTC named AI-generated fakes explicitly . It does not matter who typed the prompt. If the reviewer is not real, or the experience is not real, the review breaks the rule.
Asking for reviews the right way
Here is the part many practice owners miss. The same regulation carves out normal requests. Paragraph (d) of 16 CFR 465.2 says that “paragraphs (b) and (c) of this section do not apply to: (1) Reviews or testimonials that resulted from a business making generalized solicitations to purchasers to post reviews or testimonials about their experiences” . In plain words: asking your customers in general to share their experience is expressly carved out of those two paragraphs . You can ask. You can ask everyone. AI can help you send those requests consistently. That is the answer to “how do I get more Google reviews”: ask, broadly and consistently, and make it easy to say yes.
What you cannot do is pay for a mood. 16 CFR 465.4 states: “It is an unfair or deceptive act or practice and a violation of this part for a business to provide compensation or other incentives in exchange for, or conditioned expressly or by implication on, the writing or creation of consumer reviews expressing a particular sentiment, whether positive or negative, regarding the product, service, or business that is the subject of the review” . So, can you offer patients something in exchange for a review? Not if the offer is tied, openly or by implication, to the review expressing a particular sentiment . The word “implication” is doing a lot of work there. Read it twice.
This is not legal advice. Talk to your own counsel before you build any incentive into your review process.
Replying without breaking HIPAA
Can a dentist respond to a patient review under HIPAA? A reply can be written. But it must confirm nothing about the person. Not the visit. Not the treatment. Not the insurance. Not even that they are a patient.
HHS has already enforced this against a dental practice. The HHS Office for Civil Rights settled with New Vision Dental in California “over the impermissible disclosure of patient protected health information (PHI) in response to online reviews” . OCR described the problem directly: “The violation involves the provider’s inappropriate use of social media to respond to patient reviews, disclosing protected health information. This practice is illegal under HIPAA” . The outcome: “New Vision Dental paid $23,000 to OCR and agreed to implement a corrective action plan (CAP)” .
Here is the kind of reply we would write, as our own example: “Thank you for taking the time to write this. We read every review and take all feedback seriously. If there is anything you would like to discuss, please call our office directly.” It confirms nothing about the person. It invites the conversation offline. It works for a five-star review and a one-star review.
Should you use AI to reply to reviews? AI can draft. A human must check every reply for patient details before it goes live. The draft is the easy part. The check is the job. And do not let the tool make you sound like a tool. The same BrightLocal vendor survey found that “Templated or generic responses make 50% of consumers unlikely to choose a business” . Specific about your practice, silent about the person. That is the line.
The business lesson
Sources
Sources are listed in their original language.
- 1Federal Trade Commission, “Federal Trade Commission Announces Final Rule Banning Fake Reviews and Testimonials”, 14 August 2024. https://www.ftc.gov/news-events/news/press-releases/2024/08/federal-trade-commission-announces-final-rule-banning-fake-reviews-testimonials
- 2Electronic Code of Federal Regulations, 16 CFR 465.2, “Fake or false consumer reviews, consumer testimonials, or celebrity testimonials” (accessed 28 October 2026). https://www.ecfr.gov/current/title-16/chapter-I/subchapter-D/part-465/section-465.2
- 3Electronic Code of Federal Regulations, 16 CFR 465.4, “Buying positive or negative consumer reviews” (accessed 28 October 2026). https://www.ecfr.gov/current/title-16/chapter-I/subchapter-D/part-465/section-465.4
- 4Federal Trade Commission, “FTC Announces Crackdown on Deceptive AI Claims and Schemes”, 25 September 2024. https://www.ftc.gov/news-events/news/press-releases/2024/09/ftc-announces-crackdown-deceptive-ai-claims-schemes
- 5HHS Office for Civil Rights, “HHS Civil Rights Office Enters Settlement with Dental Practice Over Disclosures of Patients’ Protected Health Information” (New Vision Dental), 14 December 2022. https://www.hhs.gov/hipaa/for-professionals/compliance-enforcement/agreements/new-vision/index.html
- 6BrightLocal (vendor survey), “Local Consumer Review Survey 2026”, 2026. https://www.brightlocal.com/research/local-consumer-review-survey/
- 7BrightLocal (vendor survey), Rosie Murphy, “Nearly Half of Consumers are Asking AI for Business Recommendations”, 10 March 2026. https://www.brightlocal.com/research/lcrs-ai-trust/