AI Readiness benchmark for Medical Devices

Across 190 audited domains we have classified as Medical Devices, the median AI Readiness score is 38 out of 100. That is 1 points below the median for all 30,738 audited domains in the corpus (39).

How the scores are distributed

Half of the 190 audited Medical Devices domains score between 33 and 44. The corpus-wide interquartile range, across all 30,738 audited domains, is 32 to 45.

Which factors this industry fails most often

The rubric scores 19 factors. A factor counts as failed here when a site scores below 50 out of 100 on it. The last column is how many audits each rate was calculated from. Question Coverage & FAQ Presence and Media Accessibility are not scored on every kind of page: a rankings table or a paginated index has no question to answer and no image to caption. Citation-Worthiness, E-E-A-T Signals and Question Coverage & FAQ Presence lean on English-language patterns, so on a page written in another language they are scored out of a smaller total. Those rows therefore leave out every audit of a page the factor was not scored on the same scale, and every audit that did not record enough about the page for us to tell. Every other row counts every audit in this industry that scored the factor.

Where Medical Devices diverges from everyone else

Relative to the whole corpus, this industry is distinctively weak on Question Coverage & FAQ Presence (+7 points), E-E-A-T Signals (+6 points), Answer Box Potential (+5 points).

It is distinctively strong on Trust & Brand Signals (-8 points), Mobile Optimization (-6 points), AI Discoverability (-4 points).

Question Coverage & FAQ Presence: fails on 92% of the 63 Medical Devices audits it was measured on

Covering the sub-questions users actually ask is the single strongest diagnosed lever: contextual gaps and intent divergence explain most zero-citation failures. FAQ formatting by itself is not the lever; answering the questions is.

E-E-A-T Signals: fails on 95% of the 65 Medical Devices audits it was measured on

No study tests author bios as a causal AI-citation lever; the real authority channel is off-site brand footprint. On-page bylines and dates are kept as best-practice hygiene at reduced weight.

Answer Box Potential: fails on 73% of the 190 Medical Devices audits it was measured on

The real mechanism is passage self-containment: heading-scoped sections that stand alone match retrieval chunking, and fixing context-severed passages measurably cuts retrieval failures.

Audited Medical Devices sites with a public report card

Each of these sites has a public AI Readiness report card from a real audit. Scores are point-in-time; the card shows what was measured and when.

Browse every audited site in the public audit archive.

See the full ranked list of 28 Medical Devices sites →

How to read this

• What the sample is. The 190 domains we have audited and classified as Medical Devices. That is a sample of the industry, not a census: it is the set of sites our crawler has reached and scored, and it carries whatever bias that selection has.
• Rubric version 2026-08-13. Every figure here comes from audits scored on this single rubric generation. Scores from different generations measure different things, so they are never mixed. Compatible generations: 2026-08-13.
• Why there are no company names. These are aggregates. We do not publish which domains sit at the bottom of a distribution, and the queries behind this page cannot return a domain name.
• Publishing floor. We publish an industry only once it reaches 100 audited domains, and a factor's failure rate only once 30 audits in the industry count toward that factor. Below either floor the number would move with a handful of sites, so we withhold it.
• What the audit can and cannot see. This audit measures citation readiness: how easily AI engines can crawl, extract, and quote these pages. It cannot see the off-site brand footprint (mentions, reviews, third-party coverage) that gates whether AI engines retrieve a brand at all; Kuroma's visibility scans and off-site signals track that side. Read the full methodology.

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