Highlights
- The dataset: This study is an analysis of over 80,000 AI source citations using prompts specific to the hospital industry. It analyzes AI responses from four AI models run in 12 countries over the course of Q2 2026.
- Wikipedia alone makes up 13% of ChatGPT's citations: That makes ChatGPT the most concentrated model.
- 89% of top sources differ between any two models: ChatGPT and Microsoft Copilot share exactly one top-20 domain, rankings.newsweek.com.
- 37% of Google AI Overview's citations are from institutional domains: Hospital and health-authority pages, the highest institutional share of any model.
- 54% of citations in non-English prompts stay in-country: More than double what globally branded software categories show.
Which sources should you target to get cited as a hospital brand?
The single most-cited domain is different for every model, and the concentration varies widely. ChatGPT is the most concentrated, en.wikipedia.org alone accounts for 12.5% of its citations, while Grok and Google AI Overview spread their citations across a longer tail of rankings sites, social platforms, and individual hospital pages.
| Model | #1 | #2 | #3 | #4 | #5 |
|---|---|---|---|---|---|
| ChatGPT | en.wikipedia.org (12.5%) | rankings.newsweek.com (3.8%) | todocanada.ca (1.5%) | es.wikipedia.org (1.4%) | clinicbarcelona.org (1.1%) |
| Microsoft Copilot | hospitalglob.com (5.1%) | zorgkaartnederland.nl (2.7%) | health.usnews.com (2.5%) | doctify.com (2.0%) | clinica-web.com.ar (1.6%) |
| Grok | rankings.newsweek.com (7.5%) | facebook.com (3.7%) | yelp.com (3.4%) | instagram.com (3.0%) | scimagoir.com (2.6%) |
| Google AI Overview | facebook.com (3.0%) | instagram.com (2.7%) | rankings.newsweek.com (2.1%) | quironsalud.com (1.6%) | m.yelp.com (1.6%) |
The character of each list is distinct: ChatGPT reads like an encyclopedia-plus-ranking digest, Microsoft Copilot like a stack of national hospital-finder directories, Grok like a rankings-and-social feed, and Google AI Overview like a blend of social profiles and official health-system pages.
How have AI source rankings changed over time in the hospital industry?
We split the observation window at its midpoint (early April 2026) and compared each top domain's share of citations in each half, ranking by share within each half rather than raw counts.
Healthcare rankings are strikingly stable. The top two sources, rankings.newsweek.com and facebook.com, held their #1 and #2 positions with essentially no change in share. The movement that did occur was modest: en.wikipedia.org climbed from #15 to #11 (+67% share) as ChatGPT's encyclopedic lean grew, and health.usnews.com edged up from #6 to #5 (+16%). On the other side, scimagoir.com slipped (#5 → #6, −32% share) and yelp.com cooled (#3 → #4, −25%). This is an observational snapshot over roughly seven weeks, read the movement as directional, and the headline is stability, not churn.
What type of content do AI models cite for hospitals and health systems?
The models differ not just on which domains but on what type of content they trust. We classified every cited domain into six categories. Healthcare stands apart from commercial software: institutional and editorial content dominate, while purely commercial pages take a back seat.
The read for a health-system marketer is direct: Google AI Overview rewards official institutional content most heavily, your own hospital and health-authority pages. ChatGPT and Microsoft Copilot lean on reference and editorial content (Wikipedia, news features, and health directories), so encyclopedic accuracy and press coverage matter there. Grok casts the widest net into editorial and user-generated content, review sites, social profiles, and forum threads.
Do AI models cite local-language content for hospitals and health systems?
Hospitals draw local citations far more than most categories we track. Across the six non-English markets we measured (German, French, Italian, Dutch, Swedish, Spanish), 53.9% of citations point to a local-country domain. Healthcare is delivered locally, patients want hospitals in their own city and country, and the AI models reflect that.
Swedish, Dutch, and Italian markets are the most locally grounded, more than two in three citations stay in-country. Spanish is the clear outlier on the low end at 35.8%, and it is also the largest non-English market: Spanish-language prompts span Spain, Mexico, and Argentina, and the models lean more on pan-regional and global .com health sites than on any single country's domains.
Which AI model relies most on local sources for hospitals and health systems?
The same prompt, asked in the same language, produces very different localization behavior depending on the model. Microsoft Copilot relies on local sources the most; Grok reaches for global and English sources most often.
Microsoft Copilot cites local sources almost exclusively in Italian and Dutch markets (98% and 97%) and stays above 70% in German, French, and Swedish. Google AI Overview leans heavily on local sources where it has coverage, over 80% in German, Italian, and Swedish, but returned no French or Dutch localization cells in this dataset, so those are omitted. Grok is consistently the least local, dropping to 31% in Spanish. ChatGPT's per-language figures rest on smaller cell counts, so read them as directional. A hospital targeting German, Dutch, or Italian patients gets the most local-source visibility through Microsoft Copilot and Google AI Overview.
Should hospitals and health systems optimize for each AI model separately?
Yes, decisively. When the four models answer the same hospital questions, their top-cited domains barely converge. We compared the 20 most-cited domains for each model and measured how much they share.
Only one domain, rankings.newsweek.com, the source behind Newsweek's "World's Best Hospitals" ranking, appears in all four models' top-20 lists. It is the closest thing the category has to a universally trusted reference. Everything else is contested. A hospital visible on one model can be absent from about 89% of the sources another model cites.
How many sources does each AI model cite per answer?
The four models differ enormously in how many sources they pull into a single answer. Grok is the most source-hungry by far, averaging 38.8 sources per response; ChatGPT is the most economical at 4.6, an 8.4x gap.
ChatGPT not only cites the fewest sources per answer, it cites sources at all in only a fraction of its healthcare responses, 211 of its 1,710 responses carried any citation. For a health-system marketer, source count is opportunity: Grok's wide net means many chances to be cited per answer, but each citation carries less weight; ChatGPT's narrow, infrequent citing means few slots and very high stakes for each one.
Context
This analysis draws from Temso's AI visibility monitoring platform, which tracks how brands appear in AI model responses across ChatGPT, Microsoft Copilot, xAI Grok, and Google AI Overview. The dataset covers hospitals-and-health-systems prompts across twelve markets (US, UK, Canada, Australia, Germany, France, Italy, Netherlands, Sweden, Spain, Mexico, Argentina) and six non-English languages plus English, collected over roughly seven weeks from mid-March to late April 2026.
It measures what AI models cite, not the accuracy of any answer, the click-through value of a citation, or the causation behind any ranking movement. These findings reflect citation behavior for hospital-related prompts in the monitored markets and may not generalize to all institutions, prompt types, or other verticals.
Methodology
How we measured this
We analyzed over 80,000 cited source links extracted from 5,724 AI model responses to hospitals-and-health-systems prompts, collected between 2026-03-10 and 2026-04-27 across twelve countries and seven languages. A "citation" is a single web source that a model referenced in answering a prompt; we counted only sources flagged as actually cited, not merely retrieved. Domain categories (institutional, editorial, commercial, UGC, reference) were assigned from a global domain registry. Cross-model overlap was measured on each model pair's top-20 most-cited domains, shared domains divided by combined unique domains, and the extreme-pair difference was statistically significant (z = 2.51, p = 0.012). Temporal analysis split the observation period at its midpoint and compared domain rankings by within-half share.
Sample sizes exceeded recommended thresholds for every reported finding; the localization subset covers over 50,000 citations in non-English prompts. Localization is measured by a country-code-domain (ccTLD) proxy, a German-language article on a .com domain counts as non-local, so the true local-content rate is likely somewhat higher than reported, and excludes English-language prompts, which sit overwhelmingly on generic domains. ChatGPT cited sources in only 211 responses, so its per-language localization splits are directional; where a model returned no citations for a language (Google AI Overview in French and Dutch), the cell is omitted rather than estimated.
Frequently asked questions
Do different AI models cite the same hospital sources?
No, overwhelmingly not. Any two of the four models share on average just 11.4% of their top-20 domains, so about 89% of the sources one model trusts are absent from another's top tier. Only rankings.newsweek.com, the source behind Newsweek's "World's Best Hospitals" ranking, appears across all four lists.
Which AI model cites the most sources per answer?
Grok, by a wide margin, about 39 sources per healthcare response, versus roughly 12 for Google AI Overview and Microsoft Copilot and just 5 for ChatGPT. That is an 8.4x spread between the most and least source-hungry models.
Which single domain matters most in healthcare AI answers?
It depends on the model. ChatGPT concentrates 12.5% of its citations on Wikipedia; Microsoft Copilot leads with hospitalglob.com; Grok with rankings.newsweek.com; Google AI Overview with facebook.com. rankings.newsweek.com is the only domain trusted by all four.
What type of content gets cited most for hospitals?
Institutional and editorial content lead, this is a category built on official hospital sites, health-authority pages, and news features, not vendor marketing. Google AI Overview sends the most citations to institutional sources (37%), ChatGPT leans on reference content like Wikipedia (22%), and Grok casts the widest net into editorial and user-generated content (35% and 21%).
Do AI models cite local-language content in non-English markets?
Strongly, yes. Across six non-English markets, 53.9% of citations use a local-country domain, more than double what globally branded software categories show. Healthcare is delivered locally, and the models follow. Swedish, Dutch, and Italian markets are the most local (68–72%); Spanish is the least (36%).
Which model is best for reaching non-English hospital audiences?
Microsoft Copilot and Google AI Overview. Microsoft Copilot cites local sources 97–98% of the time in Italian and Dutch markets, and Google AI Overview stays above 80% where it has coverage. Grok is consistently the least local. A hospital targeting German, Dutch, or Italian patients gets the most local-source visibility through Microsoft Copilot.
Did the hospital source rankings change over the period studied?
Barely. rankings.newsweek.com and facebook.com held the top two spots with essentially no change in share. The modest movers were en.wikipedia.org (#15 → #11, +67% share) and health.usnews.com (#6 → #5), while scimagoir.com and yelp.com cooled. We read the movement as directional given the short window.
What should a hospital or health-system marketer do with this?
Optimize per model, and optimize per market. Winning Google AI Overview rewards strong official institutional content (your own hospital and health-authority pages); winning ChatGPT and Microsoft Copilot requires accurate reference and editorial presence (Wikipedia, news features, health directories); winning Grok depends on reputation across social and review platforms. Because healthcare is intensely local, in-country domains and local-language content are essential outside the US, far more so than in global software or travel categories.
