Benchmark preparation

Healthcare AI Search Visibility Benchmark 2026

Original research on how healthcare and medical brands appear across Google, AI Overviews, ChatGPT, Gemini, Claude, Perplexity, and high-intent patient search.

Key findings

Quotable findings without unsupported claims.

The public page is designed for journalists, analysts, newsletters, and industry operators. Findings stay tied to the benchmark sample and collection window.

65% vs 13%

Claude and ChatGPT ask clarifying questions in nearly two-thirds of healthcare queries, while Gemini does so just 13% of the time.

There is a massive divergence in how conversational models approach medical queries. Claude (65%) and ChatGPT (63%) try to narrow down the user's symptoms or needs, whereas Gemini (13%) tends to provide immediate, generalized answers.

73%

ChatGPT recommends consulting a healthcare professional in 73% of its responses, the highest among the tested models.

ChatGPT leads in pushing users toward professional medical help (73%), compared to Claude (63%) and Gemini (55%).

50%

Claude provides a structured list of criteria for selecting a healthcare provider in half of its responses.

When users ask healthcare questions, Claude is the most likely to offer a checklist for choosing a doctor or specialist (50%), compared to ChatGPT (40%) and Gemini (38%).

39%

Local proximity is mentioned as a key factor in 39% of AI responses across all models.

Location matters in healthcare AI search, with Claude emphasizing local proximity the most (48%) compared to ChatGPT (38%) and Gemini (33%).

Martial Notarangelo
Research leadMartial NotarangeloFounder, Authority Specialist

This benchmark is researched and maintained in-house. For the underlying data, methodology detail, or an on-record comment for your story, reach the research lead directly.

Sector intelligence

The Healthcare search & AI landscape, measured.

Two proprietary datasets, refreshed on a set cadence: curated search-demand intelligence across every healthcare service we cover, and a controlled study of how ChatGPT, Claude and Gemini actually advise healthcare buyers. Every figure is citable — anchors are stable.

Observed signal110.9M/mo
Monthly searches tracked across 25 healthcare services (2,088 curated keywords)
Measured · 2,088 keywordsAuthority Specialist keyword intelligence, 2026-07-02
Observed signal$6.18
Median cost-per-click a healthcare business pays to BUY one visit that organic authority earns for free
MeasuredAuthority Specialist keyword intelligence, 2026-07-02
Observed signal12/100
Median ranking difficulty — how contested the sector's keywords are (lower = more winnable with authority)
MeasuredAuthority Specialist keyword intelligence, 2026-07-02
Demand monitor · 12 monthsTracked market momentum
Live dataset
Opening index89.6M
Latest index110.6M
12-month change+23.5%

How AI models advise healthcare buyers — 2026-07 edition

Observed signal17%
AI models rarely name specific healthcare providers, doing so in only 17% of responses on average.
Measured · N=120 responsesAuthority Specialist AI Study, 2026-07 — 40 standardized questions × 3 models
Share of answers recommending to hire a professional, by model
  • ChatGPT72.5%
  • Claude62.5%
  • Gemini55%
Behavior matrixModel-by-model evidence
Measured

Measured behavior across 40 healthcare buyer questions (2026-07). Reading: % of responses exhibiting each behavior.

Measured behavior across 40 healthcare buyer questions (2026-07). Reading: % of responses exhibiting each behavior.
BehaviorChatGPTClaudeGemini
Recommends hiring a professional73%63%55%
Suggests DIY first25%20%18%
Names specific providers15%15%20%
Gives price or cost info13%30%20%
Tells to check reviews18%20%8%
Tells to verify credentials20%10%8%
Mentions case studies / portfolio5%3%0%
Mentions local proximity38%48%33%
Gives selection criteria40%50%38%
Warns about red flags8%20%15%
Asks a clarifying question63%65%13%
Recommends multiple quotes8%15%0%

AI Recommendation Index — where healthcare ranks across 14 industries

The ARI is the average rate at which ChatGPT, Claude and Gemini recommend hiring a professional, per industry. A named, quarterly-tracked index — cite it as “Authority Specialist AI Recommendation Index”.

Evidence register14 measured records
Select a column to sort
1Legal71.7%
2Healthcare63.3%
3Automotive62.5%
4Beauty60.8%
5Home Services60.8%
6Real Estate52.5%
7Financial Services43.3%
8Fitness43.3%
9Professional Services39.2%
10Education34.2%
11Manufacturing32.5%
12Technology28.3%
13Ecommerce14.2%
14Hospitality12.3%

Where the demand concentrates

Evidence register5 measured records
Select a column to sort
dentist16.5M$8.6929/100
pharmacy13.2M$1.7626/100
doctor13.1M$5.6829/100
urgent care8.7M$3.7714/100
dental practice7.1M$8.0510/100

About this benchmark

What the Healthcare benchmark measures.

This report measures how visible healthcare and medical brands are across AI-generated search and recommendation environments, with attention to mentions, recommendations, citations, source quality, sentiment, trust evidence, and hallucination risk.

Visibility

Mention, recommendation, and top-three presence

Measures whether AI systems recognize brands organically and where they appear inside generated recommendations.

Citations

Source and citation audit

Separates brand-owned websites, directories, media, review platforms, regulatory sources, and uncited assertions.

Trust

Authority evidence and risk signals

Checks whether public evidence supports safer descriptions, comparisons, and recommendations in high-intent searches.

AI-visible brands

Most visible brands in this benchmark sample.

Rankings are only shown when verified public data exists. The language is intentionally visibility-based, not a claim that one company is objectively better than another.

Evidence register10 measured records
Select a column to sort
1Zocdoc1915.8%
2Healthgrades1815%
3Yelp108.3%
4Google Maps97.5%
5Psychology Today65%
6Healthcare Bluebook54.2%
7Vitals54.2%
8Google54.2%
9Aetna43.3%
10Open Path Collective43.3%

Extracted verbatim from 120 stored AI responses (2026-07 edition). Mention frequency in stored AI responses. A mention is not an endorsement.

Methodology

A controlled snapshot, not an absolute ranking.

Results are framed as observations from a defined sample and collection window. AI outputs can vary by model version, location, personalization, retrieval mode, and time.

Step 01Company dataset

Build a clean industry list covering national brands, mid-market players, organic challengers, specialists, and emerging entities.

Step 02Prompt set

Group prompts by recommendation, comparison, trust, alternative, informational, local, and high-value buyer intent.

Step 03AI response capture

Collect model outputs with consistent prompt wording, collection dates, country context, and search mode notes where available.

Step 04Human QA

Review brand matches, citation URLs, sensitive claims, hallucination flags, and public wording before publication.

Downloads

PDF, CSV, charts, and methodology assets.

Public downloads become active only when the underlying benchmark data and citations are ready for reuse.

PDF

PDF report

Public report formatted for journalists, analysts, and internal stakeholders.

Pending
CSV

CSV summary

Summary table for verified benchmark metrics and public ranking fields.

Pending
ZIP

Chart pack

Reusable PNG/SVG chart assets with attribution and canonical source links.

Pending
HTML/PDF

Methodology

Collection window, prompt categories, model setup, scoring rubric, and limitations.

Pending

Resources

Browse every Healthcare resource.

Service frameworks, authority playbooks, and implementation resources for healthcare and medical brands. Expand to see the full library, all reachable directly from this page.

Show all 104 resources
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