This article covers PR and AI-visibility strategy only. It contains no medical, legal or regulatory advice, and nothing here should be read as such. A healthtech company's own clinical, legal and regulatory advisors should review any specific claim before it goes public.
Patients are already asking AI chatbots about symptoms, treatments and conditions at a scale regulators are now tracking directly, and peer-reviewed research keeps finding the answers are unreliable on a meaningful share of questions. For a healthtech brand, that combination changes what AI visibility work actually needs to accomplish. It is not enough to get mentioned. The information an AI system surfaces about a condition, a treatment category or a company's own product has to be accurate, because the volume of people relying on it is no longer small enough to ignore.
Sources: KFF's poll published March 25, 2026, and Rock Health's 2025 Consumer Adoption of Digital Health Survey, both linked in the article.
How many people are actually asking AI chatbots about health?
About a third of US adults, and the number is still climbing. KFF's nationally representative poll, fielded in February and March 2026, found that 32% of adults have turned to AI chatbots for health information in the past year, roughly the same share that use social media for health information. Physical health questions drew more users (29%) than mental health questions (16%), and use skews young: adults under 30 are far more likely to have asked about mental health through AI (28%) than adults 50 and older (8%).
Rock Health's 2025 Consumer Adoption of Digital Health Survey, fielded in December 2025, found the same 32% figure and noted it had doubled from 16% a year earlier. Among people who use AI chatbots for health information, 64% engage with the tools at least weekly, and ChatGPT dominates: 23% of all survey respondents, and nearly three-quarters of AI health users, said they turn to ChatGPT specifically, compared with 5% using a provider-offered chatbot and 4% using a payer-offered one.
What happens after someone asks, and why does that matter for a brand?
Most people act on what they're told, and that is exactly the risk. KFF found that most people who asked an AI chatbot about mental health (58%) did not follow up with a professional afterward, compared with 42% who skipped follow-up after a physical health question. Rock Health found that after an AI health query, users most often go on to search for more information, change a behavior, or consult a provider. A meaningful share, in other words, treat the chatbot's answer as the end of the research process, not the start of one.
For a healthtech company, that means an AI system's description of your product, your condition category, or a competitor's product is not a marginal data point. It is frequently the only information a patient encounters before making a decision, which raises the stakes on accuracy well above where AI visibility for B2B brands typically sits.
How often do AI chatbots actually get health information wrong?
Often enough that two separate peer-reviewed studies in 2025 and 2026 converge on roughly the same answer. A BMJ Open study published May 15, 2026, based on 250 prompts run against five chatbots (ChatGPT, Gemini, Meta AI, Grok and DeepSeek) across cancer, vaccines, stem cells, nutrition and athletic performance in February 2025, found that 50% of responses were problematic: 30% lacked full context and 20% were rated highly problematic. Grok produced the most highly problematic answers, at 58%, while Gemini produced the fewest. Vaccine and cancer questions were handled best; stem cell, athletic performance and nutrition questions were handled worst.
A separate Mount Sinai study, published in Communications Medicine on August 2, 2025, tested six large language models against 300 physician-validated clinical vignettes, each seeded with a single fabricated detail, an invented lab result or a made-up diagnosis. Hallucination rates ranged from 50% to 82% across the six models, with chatbots confidently describing entirely fictional conditions. Even GPT-4o, the best performer, hallucinated in 53% of cases without any safeguard, a rate that fell to 23% once the prompt included a single line warning that the input might contain errors. The researchers were explicit that prompt-level fixes reduce the problem without eliminating it.
Does this mean healthtech brands should try to correct AI chatbots directly?
No, and trying is mostly wasted effort. There is no reliable, fast channel for a company to edit what a specific chatbot says about a specific condition or product, and the studies above show the problem is structural rather than something one company's complaint fixes. What a healthtech brand can control is the quality and consistency of its own public information, which is the raw material these systems draw from when they do get something right.
Earned media remains the strongest lever available: Muck Rack's May 2026 analysis of more than 25 million AI-cited links found earned coverage accounted for 84% of citations across ChatGPT, Claude and Gemini, versus roughly 0.3% for paid and advertorial content. A clinical outcome covered by a trade publication that checks claims before publishing, or a peer-reviewed study covered accurately by a health reporter, carries exactly the kind of third-party verification an AI system leans on, the same dynamic AI visibility for legaltech brands describes for a different category of high-stakes, easily-hallucinated facts.
What should a healthtech brand's public information actually say?
Specific, checkable facts stated the same way everywhere they appear: the exact clearance or approval status of a product, the exact clinical evidence behind an outcome claim, and the exact limitations of that evidence. Our guide for healthtech and digital health startups covers how to talk about regulatory status without overstating it in a press release; the same discipline applies to the FAQ pages, About pages and press kits that AI systems are more likely to pull structured facts from. A vague claim like "clinically proven" without a named study is the kind of gap a hallucinating model fills with an invented one, in the same way the BMJ Open and Mount Sinai studies found chatbots filling gaps with fabricated syndromes and lab values.
What belongs in a press kit applies directly here, with the clinical-evidence section given the same prominence a fintech company gives its regulatory status line: near the top, not buried in a footer disclaimer.
How should a healthtech brand think about the mental health gap specifically?
Carefully, because the data points to a real safety issue, not just a visibility one. KFF's finding that 58% of people who ask AI about mental health never follow up with a professional is the single most consequential number in this research for any healthtech company operating in behavioral health. A company in that space has a genuine public-interest reason to be visible with accurate, carefully worded information about when a chatbot answer is not a substitute for care, and earning coverage that makes that point is both good AI visibility practice and a defensible thing to be known for.
The direct answer, for anyone who read this far
AI visibility for healthtech brands runs on the same fundamentals as any other category, earned coverage, structured and specific public facts, consistency across every page, but the margin for error is smaller because the volume of people relying on the answer is large and growing. KFF and Rock Health both put chatbot use for health questions at roughly a third of US adults, and the BMJ Open and Mount Sinai studies both found chatbots getting meaningful shares of health questions wrong, sometimes by inventing conditions outright. Get the clinical and regulatory facts stated precisely and consistently everywhere they appear, earn coverage from outlets that verify before they publish, and treat the mental health follow-up gap as a reason to be visible with care, not just reach.
If you want help auditing how AI assistants currently describe your healthtech product or category, request a quotation and we will show you what is out there.
