State of AI Visibility Index · Q3 2026
The benchmark for AI search visibility across the web.
A quarterly index measuring how visible the world's websites are to ChatGPT, Perplexity, Claude and Google AI Overviews, published in the SearchScore SAVI Report.
✓ 1,000,000+ sites benchmarked ✓ 250+ signals per site ✓ Recomputed every edition
A single benchmark for the state of AI search visibility.
Each site in the SearchScore dataset is given a GEO Score from 0 to 100, based on 250+ AI search visibility signals across 8 weighted categories. SAVI aggregates those GEO Scores into a single index value plus a set of headline statistics for each reporting period:
- The average GEO Score across the dataset
- The tier distribution – how many sites are Invisible, Low, Emerging, Strong, or AI-Ready
- The average score in each of the 8 SAVI categories
- The size of the gap between technical health and AI visibility
- Notable outliers – well-known brands scoring poorly, small businesses outperforming household names
SAVI sits alongside the SEO Score and CRO Score that SearchScore measures for each site. Together they form a single audit. SAVI specifically benchmarks the AI visibility layer – the GEO layer – at industry scale.
250+ signals. Eight weighted categories. One index.
Each site's GEO Score is built from 250+ signals across the categories below. SAVI aggregates the same way. The weights are calibrated against citation behaviour observed across ChatGPT, Perplexity, Claude and Google AI Overviews in the SearchScore benchmark.
| Weight | Category | What it measures |
|---|---|---|
| 21% | AI Citability | How directly content answers AI queries – quotable statistics, answer-first content, structured citations. |
| 17% | Brand Authority | External entity signals: Wikipedia, LinkedIn, social presence, third-party mentions. |
| 17% | Content Quality | E-E-A-T signals: author bios, bylines, contact info, sourced claims. |
| 12% | Technical Foundations | Crawlability, HTTPS, sitemaps, canonical tags. |
| 10% | AI Platform Readiness | IndexNow, Bing verification, Perplexity and ChatGPT crawler access. |
| 8% | On-Page Structure | JSON-LD schema markup – Organisation, Service, Article. |
| 8% | Topical Authority | Content hub depth, internal linking, structured headings. |
| 7% | User Experience | OpenGraph, Twitter Cards, RSS, video and multi-platform reach. |
The real web. No curation. Recomputed every edition.
Each reporting period, SAVI is computed from the GEO Scores of every site in the SearchScore benchmark at that point in time. No sites are excluded for being too small or too large. No curation is applied. The dataset is the real web as submitted to SearchScore by users running free audits.
This methodology produces a deliberately tough picture. Across the Q3 2026 benchmark of 1,000,000+ sites, only 0.022% score AI-Ready (GEO 80+), about 1 in 4,600, and no site has yet reached the Verified tier (GEO 90+); the highest score recorded to date is 86.6. The dataset reaches deep into the long tail, where most AI-readiness work has never been done.
SAVI is recomputed every edition. The methodology is fixed. Year-on-year comparisons will be valid from Vol. 1 (Q1 2026) onwards.
Note: tier bands were recalibrated to 20-point steps this edition; the methodology behind each score is unchanged. The full scoring methodology, band definitions and verification rules are published at /savi/methodology/.
Five tiers from invisible to AI-Ready.
Every site in the benchmark sits in one of five tiers based on its GEO Score. The tier distribution is one of SAVI's headline outputs each edition.
| Tier | GEO Score | What it means |
|---|---|---|
| AI-Ready | 80 – 100 | AI engines reach for this site first. <1% of the dataset. |
| Strong | 60 – 79 | Cited reliably for relevant queries. |
| Emerging | 40 – 59 | Cited occasionally; structurally improvable. |
| Low Visibility | 20 – 39 | AI engines rarely surface this site. |
| Invisible | 0 – 19 | Functionally absent from AI search. |
Across the Q3 2026 dataset, 216 of 1,000,000+ sites are AI-Ready – 0.022%, about 1 in 4,600. On the fixed index panel, 34.17% sit in Invisible or Low Visibility.
Built by Ronnie Huss. Introduced in our HackerNoon essay.
The SAVI methodology was developed by Ronnie Huss, founder of SearchScore, who introduced it publicly in his essay on HackerNoon (2026).
Each SAVI Report edition uses this citation format:
Press and researchers citing SAVI itself – not a specific report edition – should cite this page:
Every edition of SAVI, on record.
New: our cross-edition analysis reads several of these editions side by side. The finding holds at every scale – in every edition to date, well under 1% of sites measure AI-Ready, and the Q3 2026 corpus reads 0.022%, about 1 in 4,600.
- Sector UK Law Firms, 2026 – 9,487 firms audited New
- Sector UK Veterinary Practices, 2026 – 1,977 practices audited
- Sector UK Care Homes, 2026 – 2,307 homes audited
- Sector UK Aesthetic Clinics, 2026 – 1,567 clinics audited
- Sector UK Dentists, 2026 – 3,399 practices audited
- Sector UK Accountancy, 2026 – 1,038 firms audited
- Vol. 3 Q3 2026 – Nobody Has Cleared The Bar Current
- Vol. 2 Q2 2026 – The AI Visibility Gap Is Getting Wider
- Vol. 1 Q1 2026 – First Reading: The State of AI Visibility
- UK UK Edition, Q2 2026
- Sector Birmingham Accountants
- Sector Manchester Accountants
- Sector London Accountants
- Region West Midlands, 2026