AI Search Site Audit: Technical Checks for Crawlability and Retrieval
An AI-search site audit should begin with ordinary web hygiene. If important pages are blocked, orphaned, duplicated, canonicalized incorrectly or difficult to fetch, no layer of “GEO tactics” compensates for that foundation.
Check access controls
Review robots.txt, authentication, bot-protection layers and CDN rules. Decide intentionally which crawlers to allow. For ChatGPT search visibility specifically, OpenAI documents OAI-SearchBot as the user agent associated with surfacing sites in ChatGPT search.
Confirm canonical and index signals
Important pages should have self-consistent canonical URLs, no accidental noindex directives and stable public URLs. Remove staging-domain canonicals and mixed-domain structured data.
Audit internal discoverability
Every important page should be reachable through navigation, hubs, contextual links or breadcrumbs. Orphan pages are difficult for both users and crawlers to discover.
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See Current Semrush Options →Inspect structured data for truthfulness
Use schema to identify the site, organization, articles, breadcrumbs and other visible entities where appropriate. Do not add ratings, prices, authors or product facts that are not actually present and supported.
Review content extraction quality
Important definitions, comparisons and facts should exist in HTML text rather than only inside images or client-side interactions. Tables should be readable on mobile and meaningful without visual decoration.
Use automated checks as a starting point
Semrush currently includes AI-search checks within Site Audit. Treat tool findings as a prioritized inspection list, then verify important issues manually.
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Semrush combines AI brand visibility, competitor research, prompt research and AI-search auditing in one workflow.
Check Current Semrush Pricing →Related reading
Sources & verification
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