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There is no verified formula for getting an AI system to recommend a doctor. Dr. John Spencer Ellis has described review presence, consistent practice information, authority signals and expertise-focused content as factors he believes may matter for AI visibility, but the available evidence does not establish that these factors cause recommendations or bring in new patients. The practical foundation is more certain: keep public information accurate, invite genuine reviews fairly, and handle criticism without exposing patient details.
What Ellis says about AI visibility—and what remains unproven
In a LinkedIn post, Ellis frames the question this way: “Are patients actually asking AI who the best doctor is—and is it recommending you?” He associates possible AI visibility with review presence, consistent information across profiles, authority signals and content demonstrating expertise. These are his stated views, not a verified ranking formula. The available sources do not establish how AI services select or recommend doctors, how often patients rely on them for that purpose, or whether the listed factors change a practice’s visibility.
That distinction matters: a practice can improve the accuracy and usefulness of its public information without promising that an AI system will surface it. Treat any claim of guaranteed AI recommendations, better rankings or patient acquisition as unsubstantiated unless it is backed by transparent, independently verifiable evidence.
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Make reputation management a routine part of practice operations rather than a campaign aimed at producing a particular rating. Keep the practice’s public-facing details accurate and consistent, and make it easy for patients to share authentic feedback. Ellis’s LinkedIn post identifies consistency and expertise content as possible AI-visibility signals; that connection is not independently verified, but clear, current information is still useful to people evaluating a practice.
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- Review public practice details periodically so outdated or inconsistent information can be corrected.
- Use a consistent process to invite eligible patients to leave feedback, without screening people by their expected sentiment.
- Assign responsibility for monitoring reviews and escalating patient-specific concerns through an appropriate private channel.
- Keep any assessment of AI visibility separate from claims about clinical quality or guaranteed patient growth.
Invite authentic reviews without steering sentiment
Google’s Business Profile guidance allows businesses to ask customers for reviews reflecting genuine experiences and to share a review link or QR code. It says not to offer incentives, pressure people, or selectively ask only those likely to leave positive reviews. For a medical practice, apply the request process consistently rather than using it to solicit praise from chosen patients.
These rules concern Google reviews; other platforms may have their own policies. Before launching a campaign, check the current requirements for every platform the practice uses.
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Respond to criticism while protecting patient privacy
A public response can acknowledge a concern and invite further discussion without confirming that the reviewer is or was a patient. Do not mention or confirm appointments, treatment, diagnoses, or other health details. Google advises professional, brief replies that protect reviewer privacy and avoid personal attacks. If the issue needs individual attention, direct the person to a private contact channel without revealing private information in the public reply.
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For example, a practice could say: “We take concerns seriously and would welcome the opportunity to discuss this with you. Please contact our office directly.” This wording does not confirm a patient relationship or disclose care details. Have the practice’s compliance counsel review its response protocol for its circumstances.
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Report policy violations, not simply negative opinions
Google’s review-reporting process is for content that violates its policies. A review is not eligible for removal merely because it is negative or the practice disputes the account. Report content when there is a policy-based reason, and continue to handle any underlying concern through the practice’s normal process.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.How to assess reputation-management services
Ellis has also been associated in promotional material with Reputation Return and medical-practice reputation services. That is promotional context, not independent evidence that a service works; no verified referral program or terms were established. If considering any service, evaluate its actual workflow and evidence rather than relying on promises about ratings or AI visibility.
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- Review requests: Does it invite feedback consistently from eligible patients, or filter requests according to likely sentiment?
- Privacy and escalation: Are patient-specific concerns routed privately, with safeguards against inappropriate public disclosures?
- Coverage: Which platforms and practice profiles does the service monitor?
- Measurement: Are any AI-visibility outcomes defined and measured transparently, rather than guaranteed?
- Service terms: Are scope, contract terms and independent references clear and current?
The available information does not establish a vendor’s performance, current service scope or contract terms. Ask for those details directly and assess them before committing.
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