We Scanned 220 Websites for AI Visibility — 43% Got an F
We analyzed real scan data from 220 websites to find out how AI-ready the average site is. The results: most sites fail basic AI visibility checks, and the fixes are simpler than you think.
The bottom line: We analyzed 220 real website scans from our free AI visibility checker. The average score is 53 out of 100 — a D+ grade. 43% of sites scored an F. Most failures come from missing llms.txt files, weak structured data, and content that AI models can't extract. The good news: the top fixes take less than an hour.
Methodology
This data comes from 220 scans run through LLMGeoKit's free scanner between January and March 2026. Each scan tests 7 dimensions of AI visibility: robots.txt, structured data, metadata, content structure, llms.txt, citation signals, and extractability. Scores range from 0-100 with letter grades A through F.
1 The Overall Numbers
Across 220 scans, the picture is clear: most websites are not ready for AI assistants. ChatGPT, Gemini, Claude, and Perplexity are becoming primary discovery channels, but the average website scores barely above half marks.
Only 7 out of 220 websites earned an A grade. Meanwhile, 94 sites — nearly half — scored below 50, earning an F. The gap between AI-optimized and AI-invisible is enormous.
2 Grade Distribution: The Bell Curve Skews Low
Here's how the 220 sites break down by letter grade:
| Grade | Score Range | Sites | Percentage |
|---|---|---|---|
| A | 90-100 | 7 | 3.2% |
| B | 75-89 | 16 | 7.3% |
| C | 60-74 | 40 | 18.2% |
| D | 50-59 | 40 | 18.2% |
| F | 0-49 | 94 | 42.7% |
The distribution tells an important story. Only 10.5% of sites score B or above. That means roughly 9 out of 10 websites have meaningful gaps in how AI assistants can discover, understand, and recommend them.
What this means for you
If you fix even the basics — robots.txt, structured data, and metadata — you'll likely jump from the F/D cluster into C or B territory. The bar is low because almost nobody is optimizing for AI visibility yet. Early movers have a real advantage.
3 The Most Common Failures
Across all 220 scans, certain patterns repeat. These are the dimensions where sites lose the most points:
Where most sites fail
- llms.txt — 90%+ of sites have no llms.txt file at all
- Citation signals — Missing author names, publication dates, or canonical URLs
- Extractability — No FAQ sections, no data tables, no definitions that AI can quote
- Structured data — Missing or minimal JSON-LD markup
Where most sites pass
- Robots.txt — Most sites allow crawling (though few explicitly allow AI bots)
- Metadata — Title tags and meta descriptions are generally present
- Content structure — Basic heading hierarchy usually exists
The pattern is clear: websites have the SEO basics covered, but the AI-specific layers are almost universally missing. llms.txt, structured citation signals, and extractable content blocks are the three biggest gaps.
4 Score Distribution by Bucket
Breaking scores into quartiles reveals where the bulk of websites cluster:
The largest cluster (118 sites) falls in the 51-75 range. These are sites that have some SEO foundation but haven't taken the AI-specific steps. They're one optimization sprint away from a meaningful jump. The 39 sites scoring 0-25 typically have fundamental crawling or structural issues that block AI assistants entirely.
5 What A-Grade Sites Do Differently
The 7 sites that scored 90+ share specific characteristics that separate them from the rest:
| Dimension | A-Grade Sites | F-Grade Sites |
|---|---|---|
| Robots.txt | Explicitly allow GPTBot, ClaudeBot | Default allow or block all bots |
| Structured Data | 3+ schema types (Organization, Article, FAQ) | None or only basic WebSite |
| llms.txt | Present with detailed content guidance | Missing entirely |
| Citations | Author, date, canonical on every page | Missing on most pages |
| Extractability | FAQs, data tables, definitions throughout | Walls of text, no structured blocks |
The difference isn't content quality — it's content structure. A-grade sites don't necessarily have better writing. They have better markup, better metadata, and content formatted in ways that AI models can parse and quote directly.
6 The 30-Minute Fix List
Based on the most common failures across 220 scans, here are the highest-impact fixes ranked by effort:
| Fix | Time | Expected Score Impact |
|---|---|---|
| Add an llms.txt file | 10 min | +5-10 points |
| Add JSON-LD Organization schema | 5 min | +3-5 points |
| Add author + date to key pages | 10 min | +3-7 points |
| Add FAQ section to top landing pages | 15 min | +3-5 points |
| Explicitly allow AI bots in robots.txt | 2 min | +2-3 points |
Learn how to implement each fix
We have step-by-step guides for every item on this list: creating an llms.txt file, adding JSON-LD structured data, setting up citation signals, and making content extractable.
7 Why This Matters Now
AI assistants are becoming the first touchpoint for business decisions. When someone asks ChatGPT "What's the best tool for X?" or "Which company should I use for Y?", the AI's answer depends on what it can find, understand, and cite from the web.
43% of websites are invisible to this process. They lack the structural signals AI models need to recommend them. As AI usage grows, the gap between AI-visible and AI-invisible businesses will translate directly into lost leads, lost sales, and lost market share.
The companies that optimize now — while the bar is still low and the competition hasn't caught on — will have a compounding advantage that gets harder to close over time.
Check your score. Run a free AI visibility scan to see where your website stands across all 7 dimensions. It takes 30 seconds, no signup required.