The Medtech AI-Visibility Report: 160 FDA Brands, Measured

When a hospital procurement lead, a distributor, or a surgeon wants to know which company to trust for a device today, a growing share of them no longer start with Google, a trade show, or a colleague. They start by asking an AI — ChatGPT, Google's AI Overview, Perplexity. And the AI answers with a short list of names.

So we asked a simple question with an uncomfortable answer: of the companies that actually make the world's medical devices, who does the AI name — and who does it leave out?

To find out, we did something that, as far as we can tell, no one has published before. We took the U.S. FDA's full Registration & Listing database — the definitive record of who manufactures and exports medical devices into the world's largest market — rolled it up to 160 of the largest, most established device and diagnostics brands across 15 sectors and 18 countries, and measured exactly how often each one is mentioned and cited in AI answers. The result is the clearest picture we've seen of how AI visibility actually works in medtech. It is not flattering, it is not random, and almost every part of it is a direct instruction for how to win.

The short version: AI visibility in medtech is a winner-take-most power law. The top 10 brands capture 58% of all AI mentions. Where you're based and what category you sell in predict your visibility better than how good your product is. And — most importantly — the AI almost never builds its answer from your website. It builds it from YouTube, PubMed, Wikipedia, and a handful of clinical authorities. That last fact is the whole SEO game.

How we measured it

A quick note on method, because the discipline is the point. We started from FDA Registration & Listing data, then deliberately cleaned it: we rolled regional subsidiaries up to their parent brand (so "GE Medical Systems China" counts as GE HealthCare), and we excluded contract sterilizers and logistics firms, which dominate the raw "most listings" ranking but aren't brands anyone searches for. We verified every company's real website domain, then used DataForSEO's LLM Mentions data to count each brand's mentions and citations across Google AI Overview and ChatGPT (English, U.S.), measured in June 2026.

Because every domain is verified, a score of zero means real invisibility — not a company we failed to find. AI visibility is a moving target, so treat the exact numbers as a high-resolution snapshot, not a permanent ranking. The patterns, however, are stable and they are large.

Finding 1: AI visibility is winner-take-most

The first thing the data tells you is that AI visibility is not spread around. It is brutally concentrated.

Across all 160 brands, there were 234,507 AI mentions. The top 10 brands took 58.3% of them. The top 20 took 75.8%. The median brand — a real, large, FDA-registered manufacturer — earned just 152 mentions, while the leader, Thermo Fisher Scientific, earned 55,249. That's a 360× gap between the median and the top, inside a list that contains only big companies.

At the other end, 6.2% of these major brands have zero AI mentions, and 16.2% have fewer than five — effectively invisible to a buyer who asks AI to recommend a vendor.

The SEO conclusion: in an AI answer, there is no "page two." The model surfaces a handful of names and stops. That makes visibility a winner-take-most asset — and it means the goal is not to "rank well" but to become one of the few entities the model reliably associates with your category. Being FDA-registered, or even being large, does not buy you a seat. Visibility is earned one piece of indexed evidence at a time.

Finding 2: The map of who's invisible is a map of geography

When we sort the same 160 brands by headquarters country, the gap stops looking like a coincidence and starts looking like a fault line.

The median U.S. brand earns 853 mentions, with not a single one of our 58 U.S. brands at zero. The median German brand earns 235, Swiss 389, French 867. Then the curve falls off a cliff: the median Japanese brand earns 60, the median Korean brand 7, and the median Chinese brand 2 — with more than a quarter of Chinese brands at exactly zero. Of the ten fully-invisible brands in the entire dataset, nearly all are Chinese or Korean manufacturers — companies like Weigao, Sansure, Orient Gene, Haier Biomedical, and Angelalign that are large, capable, and completely absent from the AI answer layer.

This is not a quality gap. Many of these companies clear the same FDA bar as their Western peers and out-manufacture most of them. It is a visibility gap — the same "manufacturing won, branding lost" story playing out across China's medtech exporters.

The SEO conclusion: the AI answer layer currently rewards the brands that Western clinical and editorial ecosystems have been talking about for years. For a challenger — especially an Asian exporter — that's not a wall, it's the largest open opportunity in the industry. The incumbents backed into their visibility through decades of third-party coverage. A challenger can build the same footprint deliberately, and far faster, because almost no one in the long tail is competing for it yet.

Finding 3: Your category sets your starting line

Visibility also clusters hard by sector — and not in the way most people would guess.

A few patterns stand out. Diversified giants dominate because they show up in answers to dozens of different questions. But after them, the leaders are categories where independent authorities already do a lot of talking — respiratory, neurology, orthopedics — while highly fragmented or consumer-facing categories sink: the median dental brand earns 52 mentions, the median aesthetics brand just 20. In-vitro diagnostics is the most revealing of all: it's bimodal. The giants (Thermo, Roche, QIAGEN, Agilent, Bio-Rad) are some of the most-cited names in the entire study, while smaller IVD makers cluster at zero. The category average hides two completely different worlds.

The SEO conclusion: in categories where guidelines, journals, and clinician explainers already exist, the established names inherit AI visibility almost for free — and the cost of entry for a newcomer is high. But in fragmented, commoditized, or consumer-facing categories, there is a genuine content vacuum. No incumbent owns the AI answer because no one has built the authoritative, machine-readable explanation of the category yet. That vacuum is the cheapest visibility a challenger will ever buy.

Finding 4: AI doesn't read your website — it reads everyone else's

Here is the finding that should change how every medtech marketing team spends its next dollar.

When an AI assembles an answer about a medical-device category, it cites sources. We captured the domains it pulled from across all 160 companies' answers and counted them. The result is stark.

The most-cited source by a wide margin is YouTube, with 130 citations. Then PubMed and PubMed Central — peer-reviewed and clinical literature — with nearly a hundred between them. Then Wikipedia, ScienceDirect, the Cleveland Clinic, Amazon, Reddit, Instagram, Mayo Clinic. Company-owned websites barely register: across the entire dataset, even Thermo Fisher's own site was cited just 6 times, Stryker's 4 times, Boston Scientific's 4, GE HealthCare's 3, Medtronic's 2.

Read that again. The companies the AI recommends are not the companies whose websites it reads. It recommends them because their products, evidence, and reputation are documented all over the third-party web — in videos, in the medical literature, in encyclopedias, on the sites of clinical authorities — and the model stitches that distributed footprint into an answer.

The SEO conclusion — and the through-line of this entire report: a beautiful website is necessary but radically insufficient. You do not win AI visibility by optimizing your homepage. You win it by being present and cited where the model actually looks: a real video presence on YouTube; peer-reviewed and clinical evidence indexed in PubMed; an accurate, well-sourced Wikipedia and knowledge-graph entity; coverage on authoritative third-party health and clinical sites; and, yes, the messy social and community surfaces (Reddit, Amazon reviews) where buyers compare notes. AI visibility is not on-site SEO. It is the deliberate construction of an off-site evidence footprint. This is what Generative Engine Optimization (GEO) actually means in practice — a discipline we go deeper on in our GEO guide for medical devices.

What the data says to do: a medtech GEO playbook

Put the five findings together and they stop being observations and become a sequence of moves. None of this requires being Medtronic. It requires being deliberate.

1. Pick the vacuum, not the mountain. Don't fight Thermo Fisher for "best lab analyzer." Find the fragmented, under-explained sub-category in your space — the one with real buyer demand (the AI search volumes here run into the millions) but no authoritative source the AI can cite. That's where a challenger becomes the answer fastest.

1. Build the evidence the model reads — off your own site. Get peer-reviewed studies and clinical content into PubMed-indexed venues. Publish clear, factual product and procedure explainers on YouTube. Make sure a correct, well-cited Wikipedia/knowledge-graph entity exists for your company and your flagship products. These are the citations the AI is already pulling.

1. Earn third-party authority coverage. The Cleveland Clinics, the clinical reference sites, the trade media — these are the domains the model trusts. Press and contributed content aimed at those sources does double duty: it reaches humans and it feeds the machine.

1. Don't ignore the messy surfaces. Reddit, Amazon, and YouTube comments are in the citation set because that's where real buyers talk. Showing up honestly in those communities is now part of search strategy, not separate from it.

1. Make your own site machine-legible anyway. It's the smallest slice of the citation pie, but it's the slice you fully control — structured, answer-shaped content (clear FAQs, specs, comparisons) gives the model something clean to quote when it does come to you.

1. Measure it like a metric, not a vibe. Every claim in this report is a number we pulled with the same tools we'd use for your company. You can't manage AI visibility you don't measure — track which questions surface you, which competitors the AI names instead, and which source domains feed those answers.

The bottom line

The medical-device industry built the most rigorously regulated supply chain on earth — and then quietly let a new layer, the AI answer, start deciding who gets recommended. Our data shows that layer is concentrated, geographically lopsided, category-dependent, and — crucially — fed almost entirely by sources that are not your website. The brands winning it are not necessarily the best manufacturers; they're the best-documented ones across the web the AI reads.

That's a daunting fact if you're invisible today. It's a generational opportunity if you move before your competitors understand the game. The visibility gap is wide, it is measurable, and unlike product development, it can be closed in months, not years.

If you want to know exactly where your company stands — which questions surface you, which competitors the AI recommends instead, and which sources you'd need to win — we can run the same measurement on your brand. It's the first thing we do, and it's the difference between guessing and knowing.