AI bots are now everywhere, quietly crawling the web, collecting information, and feeding it into the large language models that power tools like ChatGPT, Claude, and Perplexity. In fact, more than half of all internet traffic in 2025 now comes from AI crawlers, not humans or even traditional search engines. Yet almost none of that activity appears in Google Analytics, Search Console, or your SEO tools.

If you want your site to show up in AI search results or be referenced inside LLM-generated answers, you need to know if, when, and how these crawlers are accessing your content.

This guide explains exactly how to detect LLM bot traffic, why it behaves differently from Googlebot, and what you can learn from it to improve your AI visibility.

Why LLM Bots Behave Differently Than Traditional Crawlers

AI crawlers are trying to understand your content so it can be used inside an AI answer not ranked in a search engine.

That means their behavior is very different than traditional search engines.

LLM Bots	Traditional Search Crawlers
Care about meaning, context, and high-value info	Care about crawling your whole site for indexing
Often skip sitemaps and navigation	Rely heavily on sitemaps and URLs
Don’t always render JavaScript well	Can render complex JS frameworks
Crawl irregularly or only when users trigger it	Crawl on fixed schedules
Send almost no referral traffic	Send consistent referral traffic

This shift means traditional SEO signals don’t guarantee visibility in AI systems. You need a deeper understanding of how LLMs actually crawl your content.

How to Detect AI Bot Visits on Your Site

The tricky part? AI bots rarely appear in analytics tools. That’s because analytics only shows traffic that runs JavaScript allowing the tracker script to load. Many LLM bots don’t run JS.

But don’t worry, I will show you how to spot them.

Server Logs: The Most Accurate View of AI Bot Activity

Your server logs capture every request to your site. That makes them the most reliable way to identify LLM bots, especially those that don’t identify themselves clearly.

Look for key information such as:

• User-agent strings
• IP addresses
• Timestamps
• The exact pages they accessed
• Whether requests were successful or blocked

You can quickly filter for AI-related bots by running:

grep -E 'GPTBot|ClaudeBot|PerplexityBot|ChatGPT-User|OAI-SearchBot|Google-Extended' access.log

This is the best way to know exactly who’s crawling what.

CDN Logs: Clean, Organized Bot Data Without the Noise

If you use Cloudflare, Fastly, Akamai, or another CDN, their logs (and dashboards) often give cleaner insight into bot behavior.

Cloudflare’s AI Crawl Control, for example, shows:

• Total requests from AI crawlers
• Which pages they crawl most
• How often they hit errors
• Which bots are ignoring your robots.txt

It’s particularly useful for spotting disguised crawlers using Chrome-like user-agent strings.

AI Bot Tracking Tools: Easy, Real-Time Monitoring

If you want something plug-and-play, dedicated tools can help:

• Dark Visitors
• LLM Bot Tracker (WordPress)
• Scalenut AI Traffic Monitor
• Conductor AI Bot Analytics

These tools automatically recognize LLM user agents and give you at-a-glance dashboards showing which bots are most active and what parts of your site they’re interested in.

Log Analysis Tools

For large sites or advanced teams:

• Screaming Frog Log File Analyzer
• Botify
• OnCrawl
• Splunk, Elastic, Sumo Logic

These tools are ideal when you need to process millions of log lines or match crawl patterns to SEO performance.

The AI Bots You Should Be Watching

Today’s LLM ecosystem includes dozens of crawlers, but these are the big ones that matter most:

Bot	Who Runs It	Why It Crawls
GPTBot	OpenAI	Used for training and updating ChatGPT
ChatGPT-User	OpenAI	Real-time browsing when a user asks ChatGPT for info
OAI-SearchBot	OpenAI	Powers ChatGPT Search
ClaudeBot	Anthropic	Model training
Claude-Web	Anthropic	For real-time citations
PerplexityBot	Perplexity	Used for AI search
Google-Extended	Google	Feeds Gemini model training
Applebot-Extended	Apple	Supports Apple Intelligence
Bytespider	ByteDance	LLM dataset collection
CCBot	Common Crawl	Open-source training dataset
Amazonbot	Amazon	Alexa and AWS AI models
DeepSeekBot	DeepSeek	Reasoning model training
Meta-ExternalAgent	Meta	LLaMA training

And keep in mind: some AI crawlers don’t identify themselves at all, instead disguising their traffic behind normal browser headers.

What to Look For in Your AI Crawl Data

LLM crawling activity can reveal surprising insights — not just about bots, but about how machine learning systems interpret your site.

Which Pages Matter Most

The pages AI bots crawl most often are likely the ones:

• Influencing answers inside ChatGPT, Claude, and Perplexity
• Considered authoritative by models
• Feeding real-time citations and in-chat recommendations

If important content is missing from bot activity, it may mean LLMs can’t access it.

Where LLM Crawlers Struggle

AI bots are less forgiving than search engines. They often struggle with:

• Heavy JavaScript
• Slow-loading pages
• Complex redirects
• Weak internal linking
• Missing schema markup

Server logs can expose crawl failures long before they impact AI visibility.

How Often Bots Visit (and Why That Matters)

Tracking patterns over time helps you understand:

• How much each AI system relies on your content
• Whether your AI visibility is increasing or declining
• Which bots show the most consistent interest
• Whether your blocking rules are actually working

A 30–90 day baseline is ideal.

Your Crawl-to-Referral Ratio (Spoiler: It’s Probably Terrible)

Most AI crawlers consume massive amounts of content but send almost no visitors back.

For example:

• Claude: ~38,000 crawled pages for every 1 visitor sent
• Perplexity: ~194:1
• Google Search: ~1:1

This ratio helps decide which bots to allow — and which may not be worth the server load.

How to Control What LLM Bots Can Access

If you want to allow (or block) specific bots, you’ll manage that in your robots.txt.

Let GPTBot in:

User-agent: GPTBot
Allow: /

Block Claude:

User-agent: ClaudeBot
Disallow: /

But here’s the catch:

Robots.txt is optional.
Some bots respect it — others completely ignore it.

If you need strict enforcement:

• Use Cloudflare AI Crawl Control
• Add firewall rules
• Block specific IP ranges

Future standards like Content-Usage: ai=n are emerging, but adoption is still inconsistent.

A Simple, Practical Plan for Website Owners

If you want to get a clear picture of your LLM bot visibility, here’s the most straightforward approach:

• Get access to your server or CDN logs
• Filter for known AI user agents
• Use a tool like Dark Visitors for real-time tracking
• Establish a 30–90 day baseline
• Fix 4xx/5xx errors impacting crawler access
• Add schema markup and improve internal linking
• Optimize JavaScript-heavy pages
• Decide which bots to allow or block
• Review AI crawler activity monthly This is the new foundation of AI search optimization — something more sites will need to prioritize in the coming months.

Final Thoughts

AI tools are quickly becoming the primary way people discover information online. Your site’s presence inside ChatGPT, Claude, and Perplexity isn’t a mystery — it’s driven by how well LLM bots can crawl, interpret, and access your content.

Traditional SEO tools won’t tell you any of this.
Your server logs and AI crawler analytics will.

Think of it this way:

In the age of LLMs, log files are the new impressions.