AI Search Statistics
AI search statistics.
The headline statistics from SearchScore's audit data, including the published State of AI Visibility Index (SAVI) built on a corpus of 850,000+ website audits, in one citable page. Every number below is a self-contained, sourced statistic you can quote, with a stable anchor link and its sample size and date stated. Updated July 2026. Next update: October 2026 (with SAVI Q3).
✓ 850,000+ sites audited ✓ 250+ signals per site ✓ Free to cite with attribution
63.8% of scored audits fall below 50 for AI visibility #
63.8%
63.8% of the scored audits in SearchScore's live corpus (July 2026) fall below 50 out of 100 for AI search visibility (GEO score): nearly 2 in 3 websites.
Source: the SearchScore live audit corpus, July 2026. Context: What is GEO? · How it is measured: Methodology
Only 0.015% of analysed sites reach 80+, the AI-Ready tier #
0.015%
Only 128 of the 850,000+ sites we've analysed are AI-Ready, a GEO score of 80 or above: about 1 in 6,600 (July 2026).
Source: the SearchScore live audit corpus, July 2026. Context: What is GEO? · How it is measured: Methodology
The average website scores 43.2 out of 100 for AI visibility #
43.2/100
The average GEO score across the scored audits in SearchScore's live corpus (July 2026) is 43.2 out of 100, well below the 50 mark that separates weak from workable AI visibility.
Source: the SearchScore live audit corpus, July 2026. How it is measured: Methodology
30.3% of interactively audited websites publish an llms.txt file #
30.3%
Across 6,944 websites audited interactively by SearchScore (July 2026), 30.3% publish an llms.txt file, the proposed standard for describing a site's key content directly to AI crawlers. In a sample of the 20,000 most recent audits from the wider live corpus (16,706 with signal data), adoption is 22.8%.
Source: SearchScore interactive audits (N = 6,944) and a recent live-corpus sample (N = 16,706), July 2026. Context: llms.txt examples · How it is measured: Methodology
Roughly 1 in 14 websites block at least one major AI crawler #
6.9%
Across 6,944 websites audited interactively by SearchScore (July 2026), 6.9% (roughly 1 in 14) block at least one major AI crawler, such as GPTBot, ClaudeBot or PerplexityBot, in their robots.txt file.
Source: SearchScore interactive audits, N = 6,944, July 2026. Context: What is GEO? · How it is measured: Methodology
52.2% of interactively audited websites have no Organization schema #
52.2%
Across 6,944 websites audited interactively by SearchScore (July 2026), 52.2% publish no Organization structured data (JSON-LD), the schema markup AI engines use to identify who is behind a website when deciding what to cite.
Source: SearchScore interactive audits, N = 6,944, July 2026. Context: Structured data for AI engines · How it is measured: Methodology
The SAVI Index reads 34/100 for Q2 2026, down from 41.4 in Q1 #
34/100
SearchScore's State of AI Visibility Index (SAVI) reads 34/100 for Q2 2026, down from 41.4 in Q1 2026, as the audited dataset grew from 350,000 to 850,000 sites and reached deeper into the long tail. Both readings are published index values from the quarterly SAVI reports.
Source: published index values, Q2 2026 SAVI Report · Index home: the SAVI Index
SearchScore has audited more than 850,000 websites #
850k+
SearchScore's SAVI corpus covers more than 850,000 website audits for AI search visibility, each scored against 250+ signals across 8 weighted GEO categories, and grows daily.
Source: published corpus figure, Q2 2026 SAVI Report; live-corpus counts from the SearchScore audit database, July 2026. How it is measured: Methodology
Greater London accountancy firms average 52.8/100 for AI visibility #
52.8/100
SearchScore's June 2026 benchmark of more than 150 Greater London accountancy firms found an average AI visibility (GEO) score of 52.8 out of 100, with only four firms scoring above 70.
Where these numbers come from.
The statistics on this page come from two related sources, and each one states which. The published SAVI figures (the 850,000+ audit corpus and the quarterly index values) are report-level numbers from the Q2 2026 SAVI Report. The full scoring methodology and verification rules are published at /savi/methodology/. The per-signal rates are computed directly from SearchScore's live audit database, and each is quoted with its own sample size and date: score-distribution figures cover every scored audit in the live corpus, while signal-level rates (llms.txt, AI-crawler blocking, Organization schema) cover the 6,944 websites audited interactively through the free scan on this site, cross-checked against a recent live-corpus sample where stated.
Every audit uses the same automated pipeline that powers the free scan: it fetches the live page, robots.txt, llms.txt and sitemap, checks external authority and review signals, and scores the site against 250+ signals across 8 weighted GEO categories. No sites are excluded for being too small or too large, and no curation is applied.
The full measurement approach, including how each signal is collected and verified, is documented on the methodology page. The quarterly index built from this data, with tier distributions and category averages, is the State of AI Visibility Index (SAVI).
Updated July 2026. Next update: October 2026 (with SAVI Q3). These statistics are free to cite with attribution and a link. Suggested citation format: