NMC Section 6 — doctor advertising rules inside ChatGPT Ads
A ChatGPT Ad is still an advertisement, and a doctor's name inside a sponsored conversational response is still governed by the same Section 6 restrictions that apply to a hoarding or a Google ad — with one added wrinkle: the copy can be rephrased by a model before a prospective patient ever reads it. This page sets out what Section 6 actually says, how it maps onto conversational ad copy specifically, the violations ICG catches most often, and the checklist every healthcare ChatGPT Ads push runs against before it goes live.
What the rule actually says
The National Medical Commission's Registered Medical Practitioner (Professional Conduct) Regulations, 2022 replaced the older Indian Medical Council (Professional Conduct, Etiquette and Ethics) Regulations, 2002, but carried forward the substance of the advertising restriction that used to sit at clause 6.1 into what is now generally referenced as Section 6 of the 2022 code. In plain language, the provision restricts a registered medical practitioner from soliciting patients through advertisements — whether placed personally, through an agent, or through an institution acting on the doctor's behalf — and specifically bars claims of special skill, superior results, or comparative superiority over other practitioners or institutions. A doctor is permitted to maintain factual, professional information: name, registered qualifications, specialty, and consultation timings, in a form comparable to what has traditionally been allowed on a clinic signboard or visiting card.
The distinction the regulation draws is between information and solicitation. A directory listing that states a doctor's MBBS, MD, and specialty is information. A sponsored placement that states the same doctor has "the highest success rate in Delhi NCR" or "treats patients other hospitals gave up on" is solicitation dressed as information, and that is precisely the category Section 6 exists to prevent. The rule does not distinguish by medium — it was written with print and signage in mind, but its language ("advertisement in any form") extends without modification to a website, a search ad, a social post, or a sponsored response inside a conversational AI tool, because the regulation defines the restricted act by its content and intent rather than by the channel carrying it.
It is worth being precise about enforcement, since the practical risk differs from the letter of the rule. Section 6 obligations bind the registered doctor, and complaints are typically adjudicated by the relevant State Medical Council, which can issue a warning, order withdrawal of the advertisement, or in serious or repeat cases initiate disciplinary proceedings that can affect registration standing. A hospital or clinic brand placing the ad is not itself NMC-registered, but in ICG's experience State Medical Councils and complainants alike treat the institution as the responsible publisher when a doctor is named in ad creative the institution paid to distribute, which is why this page treats brand-level and doctor-level compliance as one review, not two.
How it applies to conversational-ad copy specifically
A Google Search ad or a Meta feed ad is a fixed unit. A compliance reviewer reads the headline, description, and sitelinks once, signs off, and that exact text is what every viewer sees until the campaign is edited. That single-review model has worked for Indian healthcare advertising compliance for two decades because the surface area is finite and static.
A ChatGPT Ad breaks that assumption in three specific ways. First, the sponsored response is generated inline as part of a model-produced answer, which means the platform's rendering layer can rephrase, summarise, or truncate the advertiser-submitted copy before a user reads it — a compliant submitted line can, in principle, surface in a paraphrased form the advertiser did not directly write. Second, the ad frequently sits inside a multi-turn conversation where the user's follow-up question ("is Dr. [Name] the best for this in Gurgaon?") pulls the model toward exactly the comparative-superiority framing Section 6 prohibits, even if the original ad text never used that language — and if the advertiser has supplied structured data (FAQ schema, Person schema, a knowledge-base feed) that the model draws on for that follow-up, the compliance surface extends to that structured data, not just the ad unit itself. Third, attribution runs on conversation-completion rather than a single click, which means the compliance-relevant "advertisement" a regulator or ASCI reviewer would examine is arguably the whole conversation thread the sponsored response initiated, not one static line of copy.
The practical consequence for a healthcare brand is that a ChatGPT Ads compliance review cannot stop at the submitted ad creative. It has to cover the landing page the ad routes to, any FAQ or doctor-profile schema that page exposes (since that is exactly the machine-readable content a model is likely to draw on for a follow-up answer), and the brand's own on-page claims about named doctors — because all of that becomes fair game for the conversation the sponsored response opens. ICG's review process, described below, treats the ad, the landing page, and the structured data behind it as one compliance unit for this reason.
Common violations and how to avoid them
In reviewing ChatGPT Ad and landing-page drafts across ICG's healthcare accounts, the same handful of violation patterns recur, almost always introduced by a well-meaning marketing team trying to differentiate a doctor rather than by any intent to breach the code. Anonymised examples below show the pattern and the fix — none reference a real client, doctor, or hospital.
"Dr. [Name]'s IVF success rate of 68% is among the highest in North India — book your consultation today."
Ties a specific outcome percentage to a named practitioner and frames it as comparatively superior. Also raises an ART Act 2021 issue independent of NMC Section 6, since IVF success-rate advertising carries its own restrictions.
"Our fertility team includes MD-qualified reproductive specialists. Consultations are available this week — speak to our care coordinator to understand your options."
A second recurring pattern is the "most experienced" or "senior-most" superlative attached to a named consultant — phrasing marketing teams reach for reflexively because it reads as a natural differentiator in any other industry. In healthcare advertising governed by Section 6, any superlative implying rank against peers is restricted regardless of whether it is provably true; a doctor genuinely may be the most experienced surgeon on staff, but publishing that comparison in paid advertising is still the act the regulation prohibits.
"Consult Dr. [Name], Delhi's most experienced bariatric surgeon with over 5,000 successful procedures."
"Our bariatric surgery programme has performed over 5,000 procedures. Meet the team and discuss your eligibility."
Institutional volume claim retained (factual, verifiable); comparative and named-individual framing removed.
A third pattern is specific to the conversational surface: a landing page's FAQ schema answering "Who is the best [specialty] doctor in [city]?" with a named-doctor answer, written to help the page rank for that exact conversational query. This is one of the more subtle violations because the offending content sits in structured data rather than visible ad copy, and it is precisely the kind of content a ChatGPT follow-up turn is likely to surface verbatim. ICG's checklist explicitly scans FAQ and Person schema for this pattern, not just the visible page text, for exactly this reason.
A fourth pattern is patient testimonials that praise a named doctor's skill or promise similar results — "Dr. [Name] gave me my life back, the best surgeon I could have asked for." Because the advertising effect on a prospective patient is identical whether the words come from the doctor or a quoted patient, ICG applies the same named-practitioner and outcome-claim scan to testimonial copy as to first-party ad copy, and either anonymises the testimonial to the institution or removes the named-doctor reference before it is used in any paid placement.
What "clean copy" looks like inside a ChatGPT Ad for this domain
Clean copy for a healthcare ChatGPT Ad follows a simple test: strip out any claim that would fail on a printed hoarding under the old IMC code, and what remains should still read as a complete, useful answer to the conversational query it is responding to. That second half matters — an ad stripped down to nothing but a phone number performs badly in a conversational auction that rewards relevance and completeness. The goal is factual density, not vagueness.
"[Brand] Orthopaedic Centre, Gurgaon — NABH-accredited, dedicated joint-replacement unit performing both unilateral and bilateral knee replacement, cashless empanelment with major insurers. Book a consultation to review your X-rays and discuss suitability."
Institutional accreditation, service-line specificity, and insurance detail are all factual and verifiable — none require a comparative or outcome claim to be persuasive.
"[Brand] Fertility Centre — team of MD/DGO reproductive medicine specialists, on-site embryology lab, transparent per-cycle pricing available on request. Speak to a fertility counsellor about your specific case."
Qualifications stated factually (MD/DGO), no named-doctor outcome claim, no comparative language against other clinics, ART Act pricing-transparency norm respected by offering pricing "on request" rather than a headline number.
Note what both examples deliberately omit: no doctor's personal success rate, no "best in the city" framing, no "guaranteed" language. What they include instead — accreditation, service-line depth, insurance or pricing transparency, a specific and low-friction next step — is exactly the kind of factual density that performs well in a conversation-completion attribution model, because it answers the user's actual underlying question (can this place solve my problem, credibly) without needing a superlative to do it. Clean copy and high-performing copy are not in tension here; the superlative is usually the weakest, least differentiating line in the ad anyway.
ICG's compliance checklist before every ChatGPT Ad push
Every healthcare ChatGPT Ads campaign ICG manages passes the same documented checklist before submission, regardless of tier. The checklist is stored against the client account with a dated sign-off, so a review trail exists if a State Medical Council or ASCI enquiry is ever raised against a live campaign.
Every ad variant, landing-page headline, and FAQ/Person schema entry is checked for a named doctor paired with any claim, superlative, or outcome statement.
"Best," "most experienced," "highest," "No. 1," and comparable phrasing are flagged wherever they appear, whether attached to a doctor or the institution.
Percentage or numeric outcome claims are checked against source and, if retained at all, are stripped of any named-individual attribution.
Any patient quote naming a specific doctor is anonymised to the institution or removed before use in paid placement.
ASCI Chapter III, DPDP 2023 consent language, the ART Act (fertility), DCGI/UCPMP 2024 (pharma-adjacent), and AYUSH rules (where relevant) are checked alongside Section 6, since a single ad often triggers more than one overlay.
The destination page and its structured data are re-checked against the same rules, not just the visible ad text, since either can feed a model's follow-up answer.
The completed checklist, flagged items, and the removed or amended language are logged and dated before the campaign is submitted to the platform.
What happens if you're audited
A Section 6 complaint most commonly begins one of two ways: a competing practitioner or hospital files a formal complaint with the relevant State Medical Council, or a member of the public flags the advertisement to ASCI's Consumer Complaints Council. Neither route requires the advertisement to have caused demonstrable harm — an advertisement that is simply non-compliant on its face is enough to trigger a review.
Once a complaint is registered, the State Medical Council typically issues a notice to the named registered practitioner asking for an explanation, and separately may ask the advertising institution to withdraw the creative pending review. Outcomes range from a formal warning and mandatory withdrawal for a first, minor infraction, up to referral for disciplinary proceedings against the doctor's registration in serious or repeat cases — the latter is rare for a single ad-copy infraction but is the standing risk the regulation is designed to hold in reserve. ASCI's process runs in parallel and independently: its Consumer Complaints Council can uphold a complaint under Chapter III and direct that the creative be modified or withdrawn, and ASCI decisions are published, which carries its own reputational cost regardless of the NMC outcome.
The single factor that most affects how smoothly an enquiry resolves is documentation. A brand that can show a dated compliance checklist, the specific claims reviewed and removed before the ad went live, and a named sign-off is in a materially stronger position than one that has to reconstruct its review process after the fact — both with the regulator and, practically, with its own leadership trying to understand how the exposure happened. That documentation trail is the reason ICG treats the checklist in the previous section as a permanent campaign record rather than an internal working document that gets discarded once the campaign launches.
Get your ChatGPT Ads copy reviewed before it goes live
ICG's healthcare ChatGPT Ads practice builds every campaign compliance-clean against NMC Section 6, ASCI Chapter III, DPDP 2023, and the relevant vertical overlay from the first draft — not as an afterthought.
