AI engines classify medical content as YMYL — E-E-A-T standards are stricter than ever. This guide explains how doctors, clinics, and healthcare professionals can improve their visibility in ChatGPT, Perplexity, and Google without compromising credibility.
Healthcare professionals face a unique dual challenge in the 2026 digital landscape:
The good news: the E-E-A-T criteria Google requires for medical SEO are exactly the same signals that build AI visibility. Optimising for one automatically optimises for the other.
Google added the first "E" (Experience) to EEAT criteria in December 2022. For medical content, this means:
For LLMs, this signal translates into the professional's name appearing in medical publications, mentions in health press, and LinkedIn or PubMed profiles attesting to their clinical background.
Medical expertise criteria for SEO and LLMs are identical:
Authority is built through external mentions:
Trust signals are particularly important for LLMs in the medical domain:
When a user asks an LLM a medical question ("which back specialist in London?" or "which clinic do you recommend for knee surgery?"), the model applies maximum caution:
Every doctor or healthcare professional who publishes content or is referenced on your site needs a dedicated author page including: professional photo, degrees and specialisations, medical registration number, hospital/practice affiliation, links to PubMed/Google Scholar publications, Schema.org Person with medical properties (medicalSpecialty, affiliation).
Schema.org offers specific types for healthcare: MedicalOrganization for clinics/hospitals/group practices, Physician for individual doctors, MedicalSpecialty for specialisations, MedicalCondition and MedicalTreatment for condition-specific pages. These tags allow LLMs (and Google) to precisely understand your speciality, location, and accreditation.
Medical articles must follow a rigorous format: clearly identified author with link to author page, publication date AND last revision date, medical sources cited (with links to PubMed, NICE, WHO), medical disclaimer at the bottom, peer review mentioned if applicable.
Medical review platforms (Google Reviews, Zocdoc, Docplanner) are sources that Perplexity and Bing Copilot actively crawl. A volume of positive reviews on these platforms improves your visibility in Perplexity responses for local medical searches, feeds AggregateRating schema, and builds trust (T of Trustworthiness) in LLMs' eyes.
The strongest authority signal for medical AI visibility remains citation in recognised third-party sources: publications in indexed medical journals, interviews in health media, participation in official guidelines from your college or specialist association, mention in medical comparison platforms or health reference sites.
ChatGPT is very cautious about direct medical recommendations. It generally refers to directories (Zocdoc, NHS Choices) or official resources. Doctors with a strong presence in medical publications or press interviews are more likely to be mentioned. The goal is to be perceived as a reference in your speciality, not to be recommended as a commercial service.
Not without rigorous human review. Google penalises AI-generated medical content that is not reviewed, validated, and signed by a qualified healthcare professional. For medical content, AI should be a drafting aid — validation and sign-off by a doctor remains indispensable.
The signals are largely identical. The difference is that for LLMs, presence on third-party sources (press, medical directories, PubMed) is even more determinative than for Google SEO. LLMs rely heavily on these sources to validate that a professional is trustworthy.
In 2026, the two fields converge. A well-executed E-E-A-T strategy simultaneously improves your Google SEO and your LLM visibility. The ideal is a partner who understands both Google YMYL requirements and how AI engines work — the optimisations are largely shared.
Alan Schouleur is the founder of AISOS, a platform specialising in measuring and optimising brand visibility in AI engines (ChatGPT, Perplexity, Gemini, DeepSeek).