AI Search Visibility Data: What 875,000+ Site Audits Reveal About How Websites Perform in AI Search
The statistics below are drawn from the SearchScore database of 875,000+ website audits. Each site was scored across 8 categories covering technical foundations, content quality, brand authority and AI platform readiness. The full analysis is available in the SearchScore SAVI Report, April 2026.
Key Statistics
71% of websites score below 50 on AI search visibility.
The average GEO score across 875,000+ audited sites is 34 out of 100. Only the top 3% score above 80. Most websites were built for traditional search and have not adapted to AI citation criteria.
71% of UK websites score below 50 for AI search visibility.
Only 1.1% reach the Strong tier (71+). Not a single UK website in the database has achieved AI-Ready status (86+). The UK performs slightly above the global average but the gap remains significant.
63% of websites have zero schema markup.
On-Page Structure is the weakest scoring category across all audited sites, averaging just 23.1 out of 100. Without structured data, AI engines cannot parse what a page's content means or whether to trust it.
Source: SearchScore SAVI Report, April 2026
Technical foundations are strong (average 70.1/100) but content quality is weak (average 36.9/100).
Most sites handle HTTPS, sitemaps and crawlability well. Where they fail is content structure: author bios, bylines, fact-checking sources and extractable answer passages.
Source: SearchScore SAVI Report, April 2026
Average brand authority score: 32.5 out of 100.
Most sites lack external validation signals. Wikipedia presence, LinkedIn company pages, consistent directory listings and third-party reviews are missing for the majority of audited sites.
Source: SearchScore SAVI Report, April 2026
Average AI platform readiness: 34.1 out of 100.
IndexNow adoption, Bing Webmaster verification, answer-first content structure and Perplexity-specific access signals are rare. Most sites have done nothing to prepare for AI-specific search platforms.
Source: SearchScore SAVI Report, April 2026
97% of website visitors leave without converting.
The average conversion rate across audited sites is under 3%. The most common failures: no live chat or exit-intent capture, weak above-the-fold messaging, missing trust signals.
Source: SearchScore SAVI Report, April 2026
Fewer than 1% of websites have an llms.txt file.
Of those that do, most are under 100 words. Sites with a comprehensive llms.txt score approximately 15 points higher on AI citability on average.
Source: SearchScore SAVI Report, April 2026
Sites implementing the top 5 fixes see an average score increase of 22 points within 30 days.
Citation visibility follows within 60 to 90 days as AI engines re-index updated content. The fastest-moving sites prioritise robots.txt access, schema markup, llms.txt, answer-first content and author bios.
Source: SearchScore SAVI Report, April 2026
The Wall Street Journal scores 12 out of 100 on AI visibility. Reddit scores 13.
A small business in Scotland scored 79. AI visibility does not correlate with brand size. It correlates with structural readiness: clean schema, extractable content and clear entity signals.
Source: SearchScore SAVI Report, April 2026
Category Averages
Every SearchScore audit scores a site across 8 categories. Here are the global averages from 875,000+ audits:
| Category | Average Score |
|---|---|
| Technical Foundations | 70.1 |
| Content Quality | 36.9 |
| On-Page Structure | 23.1 |
| Brand Authority | 32.5 |
| AI Platform Readiness | 34.1 |
| Crawler Access | 55.8 |
| Conversion & Trust | 41.2 |
| Overall GEO Score | 34 |
About This Data
These statistics are drawn from the SearchScore audit database, which contains results from 875,000+ website audits run between April 2025 and April 2026. Each audit evaluates a site across 8 scoring categories covering technical foundations, content quality, on-page structure, brand authority, AI platform readiness, crawler access, conversion and trust signals.
The full methodology is documented at searchscore.io/methodology/. The complete analysis with breakdowns by industry, country and site size is available in the SearchScore SAVI Report, April 2026.
You are free to cite these statistics with attribution to SearchScore. Please link to this page or the relevant SAVI Report. For press inquiries or custom data requests, contact the SearchScore team.
Frequently Asked Questions
What percentage of websites are invisible to AI search?
71% of websites score below 50 on AI search visibility out of 100, according to SearchScore analysis of 875,000+ site audits. The average GEO score is 34. Only the top 3% of audited sites score above 80.
AI invisibility is the norm, not the exception. The vast majority of websites were built for traditional search engine optimisation and have not been adapted for AI citation. Common blockers include blocked AI crawlers in robots.txt, zero schema markup, no llms.txt file and content that is not structured for extraction.
What is the average AI visibility score?
The average AI visibility score (GEO score) across 875,000+ audited websites is 34 out of 100.
Technical foundations average 70.1 out of 100, indicating most sites handle the basics (HTTPS, sitemaps, crawlability) reasonably well. But content quality averages just 36.9 and on-page structure averages 23.1, revealing that the content layer is where most sites fail AI citation criteria.
How many websites have schema markup?
63% of websites have zero schema markup, according to SearchScore data from 875,000+ audits. On-page structure averages just 23.1 out of 100, making it the weakest scoring category.
Schema markup (structured data) helps AI engines understand what a page's content means and whether it can be trusted. Without it, AI systems rely on guessing, which reduces citation accuracy and frequency. Sites with comprehensive schema markup score significantly higher on AI citability.
How quickly can AI visibility scores improve?
Sites implementing the top 5 AI visibility fixes see an average score increase of 22 points within 30 days, according to SearchScore data.
Citation visibility typically follows within 60 to 90 days as AI engines re-index updated content. The fastest-moving sites prioritise robots.txt access, schema markup, llms.txt, answer-first content and author bios. Crawler access fixes can take effect almost immediately; content restructuring takes longer as it requires re-crawling.
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