A channel almost nobody is measuring
Health systems track referral patterns, campaign attribution, payer mix and market share by service line. Almost none of them can answer a simpler question: when someone asks an AI assistant where to go for care, how often does our organization come up?
of medical practices reported having no strategy for AI search visibility. Among the 35% who said they did, many described general AI adoption rather than anything search-specific — so the genuinely unaddressed share is higher still. The barriers respondents named were time, money, staffing, IT support, and ownership.
MGMA Stat poll, 218 respondents, June 2026
Ownership is the real problem. In most organizations, nobody's job description includes this yet.
AI Share of Discovery
When patients and buyers ask AI about the services your organization provides, what proportion of those answers does your organization appear in — and who appears instead?
| Service line | Presence rate | Recommended | Leading competitor |
|---|---|---|---|
| Women's Health | 38–45% | 31% | Competitor A — 36% |
| Orthopedics | 34–41% | 22% | Competitor A — 61% |
| Cardiology | 14–20% | 9% | Competitor B — 54% |
| Oncology | 8–13% | 4% | Academic center — 72% |
| Behavioral Health | 4–9% | 2% | Competitor C — 44% |
Illustrative summary for a regional health system in a single metro market. Ranges reflect measured variance across runs, platforms and model versions. Presence rates are absolute and do not sum across organizations.
This is not a search conversation. It is a market share conversation.
A chief financial officer cannot act on the observation that your generative engine optimization needs work. A chief financial officer can act on the finding that your organization appears in 11% of oncology discovery conversations while the academic center across town appears in 72% — in a service line where you have just invested in capacity.
Healthcare AI search optimization is not one problem
Each of these is a different question, with a different competitive set and a different economic consequence. Most organizations have a very different position in each.
Patient Discovery
“Are patients finding our orthopedic program, or the competitor's?”
Whether someone searching AI for a physician, practice, hospital, service line or procedure finds you — across orthopedics, cardiology, women's health, fertility, oncology, ophthalmology, dermatology, surgery, behavioral health and specialty practice.
Service Line Visibility
“Best hospital for joint replacement in South Florida.”
A completely different retrieval problem from “tell me about Hospital X.” An organization can hold enormous institutional authority and still be effectively invisible at the individual service line — which is where patients actually search, and where the margin actually sits.
Healthcare B2B Discovery
“Companies that help hospitals reduce surgical cancellations.”
For medtech, digital health, healthcare AI and healthcare services companies: when a hospital executive asks AI which companies solve a problem, are you part of the answer? Category presence at the top of the buying cycle is pipeline.
Reputation and Authority
“Is what AI says about us actually accurate?”
Healthcare is not a commodity category. Clinical credibility, institutional reputation, physician authority, research and third-party validation shape the answers — and so do the errors, which propagate silently until someone measures them.
Measured at six levels
Averaging across these destroys the finding. A system operating in four markets has four different pictures, and a strong organizational position routinely hides a weak service line.
- Organization — How the institution as a whole is represented and recommended.
- Service line — Position within each individual clinical program.
- Physician — Individual provider discovery and credential accuracy.
- Procedure — Specific treatments and interventions patients search by name.
- Geographic — Market by market. Geography defines the competitive set.
- Competitive — Named competitors, plus organizations appearing that you had not counted as competitors.
Eight dimensions, not three tactics
Generic answer engine optimization advice reduces to content, schema and links. Healthcare has a different substrate — a dense network of directories, registries, ratings bodies and credentialing sources that generative systems draw on far more heavily than they draw on your website.
- Clinical Authority — Demonstrated expertise, published research, trial participation, specialty depth.
- Institutional Authority — Organizational reputation, accreditation, rankings and system standing.
- Service Line Authority — Depth and specificity of evidence at each clinical program, distinct from brand.
- Physician Expertise — Provider credentials, bios and profiles, and their consistency across every source.
- Third-Party Validation — Ratings bodies, directories, reviews, press and professional recognition.
- Content Authority — Substantive, answer-shaped content on owned properties that models can retrieve and cite.
- Entity Clarity — Consistency of name, address, specialty taxonomy, affiliation and service listings across the directory substrate. Usually the most fixable finding, and frequently the largest.
- AI Search Visibility — The measured outcome: presence, recommendation and citation across all four platforms.
The first seven are inputs. The eighth is the result. That relationship is what turns an assessment into a roadmap: a weak Share of Discovery always traces to specific dimensions, and those dimensions have owners inside your organization.
Published, versioned and replicable
AI systems are non-deterministic. The same question returns different answers across runs, sessions, locations and model versions. Any visibility figure produced from a handful of screenshots will not survive a second look — which is why ours is produced under a protocol anyone can audit.
- A minimum of five runs per question, per platform, in fresh unauthenticated sessions with personalization disabled.
- Four platforms — ChatGPT, Google AI Mode and AI Overviews, Gemini, and Perplexity.
- Every run stamped with platform, model version, timestamp and geographic setting.
- Three measures reported separately — presence, recommendation and citation — never combined into a single score.
- Results reported as ranges, with measured variance disclosed rather than smoothed away.
- The full question set published in every report, so any party can re-run it.
The complete specification — definitions, question construction, sampling, scoring rules, calculations, reporting requirements and stated limitations — is published openly and versioned. Read the AI Share of Discovery Protocol →
One thing the measure is not: Share of Discovery reflects how retrievable and well-described an organization is. It is not a measure of clinical quality, and it should never be read as one.
Read by audience
The pillar states the problem and the measure. These four pieces take it into a specific room — practice, hospital, measurement team, or B2B seller — and link back here and to the protocol.
AI Search Visibility
MGMA found 55% of practices have no AI search strategy
The headline figure is the one being quoted. The finding underneath it is more useful — and it explains why almost nobody has solved this yet.
Patient Discovery
How AI search is changing how patients find hospitals and physicians
A channel that barely registered two years ago now influences more patient provider decisions than Google search does. Almost no health system is measuring it.
The Measure
Can AI find your hospital? Measuring AI Share of Discovery
A definition, a calculation, and an argument about why most AI visibility reporting does not survive a second look.
Healthcare B2B Discovery
When hospital executives ask AI which healthcare companies to consider, does yours appear?
Sixty-nine percent of B2B buyers changed vendor from what they had planned, based on what an AI assistant told them. In healthcare, where buying cycles are long and shortlists form early, that number should be alarming.
The Healthcare AI Share of Discovery Assessment
Twenty-five to fifty strategically selected questions, measured across all four platforms, scored against your named competitive set and reported at the levels that matter to your organization.
- Visibility rate by service line
- Competitor share of AI answers
- Brand and domain citation rate
- Source and citation landscape
- Topics your organization owns
- Topics competitors own
- How AI currently describes you, including inaccuracies
- Authority gaps across the eight dimensions
- Entity consistency findings across the directory substrate
- Prioritized opportunities, with internal owners identified
Assessments are also available as a recurring quarterly measure. Because model behavior shifts month to month, the trend line frequently carries more strategic information than any single baseline.
Common questions
What is healthcare AI search optimization?
Healthcare AI search optimization is the practice of measuring and improving how a healthcare organization appears in answers generated by AI systems such as ChatGPT, Google AI, Gemini and Perplexity. It differs from traditional search engine optimization because these systems synthesize an answer and name a small number of organizations, rather than returning a ranked list of links. It is also referred to as generative engine optimization, answer engine optimization, or AI search visibility.
What is AI Share of Discovery?
AI Share of Discovery is a measure of how often a healthcare organization appears in AI-generated answers to discovery questions, relative to its competitive set. It is reported alongside presence rate, which is the absolute percentage of answers in which an organization appears, and citation rate, which is how often the organization's own domain is used as a source. The three are reported separately because they carry different commercial meaning.
How is AI search visibility measured?
Under a published protocol: a fixed set of questions is run a minimum of five times each across four platforms, in fresh unauthenticated sessions with geography controlled and model versions recorded. Each answer is scored for presence, recommendation and citation using documented rules. Results are reported as ranges with the measured variance disclosed, and the full question set is published so the measurement can be independently reproduced.
Is this the same as SEO?
No. Traditional SEO works toward position in a ranked list of links. AI search visibility concerns whether an organization is named at all in a synthesized answer, and which sources that answer is constructed from. In healthcare the sources are distinctive — provider registries, directories, ratings bodies, payer listings and credentialing data carry substantially more weight than a marketing website does.
Which organizations is this for?
Hospitals and health systems measuring service line and market position; medical practices and physician groups measuring patient discovery; and medtech, digital health and healthcare services companies measuring category presence among hospital executive buyers.
Does a higher Share of Discovery mean better care?
No, and the distinction matters. Generative systems assemble answers from available text, not from outcomes data. An organization may hold a strong Share of Discovery and weak clinical performance, or the reverse. This is a visibility measure only, and every report produced states that explicitly.
Find out where you appear
A Share of Discovery assessment shows you where your organization is being found, where competitors are being recommended instead, and which signals are producing those answers.