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AI Crawler

An AI crawler is an automated client that fetches web pages for an AI company’s products: to collect content for model training, to index pages for AI search answers, or to open a page at the moment a user asks an assistant about it. Each one names itself with a product token that robots.txt rules can address.

  • Industry term

By QueryRev ResearchPublished Updated6 min read

Why it matters.

The three jobs carry different stakes, and the vendors document them as separate agents. OpenAI runs GPTBot for content that may be used in training, OAI-SearchBot to surface sites in ChatGPT’s search features and ChatGPT-User for pages a person asks about, and states that each robots.txt setting is independent of the others[1]. Perplexity draws the same line between PerplexityBot, which surfaces and links sites in its search results, and Perplexity-User, which visits a page to help answer a question[2]. Refusing a training crawler asks that content stay out of future training; refusing a search crawler keeps the site out of that engine’s answers.

Fetchers that act for a user sit partly outside robots.txt. OpenAI says that because ChatGPT-User acts on a user’s request, robots.txt rules may not apply, and Perplexity says Perplexity-User generally ignores them[1][2]. A site that wants to refuse those requests has to do it at the server or the firewall, and gives up the reader who asked about the page.

Some tokens are not crawlers at all. Google-Extended has no user agent string of its own: Google crawls with its usual agents and reads the token only as a control over whether content may be used to train Gemini models and to ground answers in Gemini Apps, and it has no effect on inclusion or ranking in Google Search[3]. Google’s AI features in Search, AI Overviews and AI Mode, follow the robots.txt rules for Googlebot[4].

Sites treat the crawlers very differently. In QueryRev’s study of AI crawler access, the three most often blocked by name are Bytespider at 9.5% of the sites read, CCBot at 9.4% and GPTBot at 9.2%[5]. The most blocked of them is the one whose purpose the study found no documentation for: a rule is written against a name, so it pays to know what the name does.

How it is measured.

In two places: the rules and the requests. For the rules, read robots.txt on every host the site serves and work out, for each product token, which group applies and which paths it closes. For the requests, read the server logs by user agent: which crawler fetched which URLs, how often and with what status. A crawler that robots.txt allows and a firewall refuses with 403 is blocked all the same, which is why Google’s checklist for its AI features asks that crawling be allowed in robots.txt and by any CDN or hosting infrastructure[4].

Verify before you count. A user agent string is easy to copy, so OpenAI and Perplexity publish the IP ranges their agents use, and Perplexity recommends matching both the user agent and the address[1][2]. A request that calls itself GPTBot from an address outside OpenAI’s list is not GPTBot.

Read the rule that applies, not only the one that names the crawler. A crawler with no group of its own follows the catch-all group, so in QueryRev’s study the share of sites that keep GPTBot from the whole site rises from 9.2% by a group naming it to 11.6% by whichever group applies[5].

Measured by

  • Rule per crawler
  • Requests and status codes
  • Verified addresses

A worked example.

Sample data: an invented site, to show the method.

A furniture retailer reads one week of server logs for the AI agents it cares about. GPTBot, ChatGPT-User and PerplexityBot fetched pages and got 200. OAI-SearchBot got 403 on every request: a bot rule at the CDN, added during a scraping incident, that nobody connected with search.

A fifth agent called itself GPTBot but came from an address outside OpenAI’s published ranges, so it is set apart as unverified. One fix follows: allow OAI-SearchBot at the CDN, then read the logs again a week later.

One week of AI crawler requests

What to do, step by step.

  1. List the AI crawlers that matter to you by their documented purpose: training, search, or a fetch on a user’s request. Decide each one on its own.

  2. Allow the search crawlers of the AI surfaces you want to appear in unless there is a reason not to, and decide training as a separate question.

  3. Write a group only for a token you treat differently from the rest, and check that each named group repeats the catch-all rules it should keep.

  4. Check the layers in front of robots.txt: CDN bot settings, firewall rules and hosting defaults can refuse a crawler that robots.txt allows.

  5. Read server logs by user agent each month, verify the addresses against the published ranges, and compare what was fetched with what the rules allow.

  6. Read the vendors’ crawler pages again whenever you review the rules: tokens and purposes change, and a list written last year can miss a new agent.

Mistakes to avoid.

  • One rule for every AI crawler. Training, search and user fetches have different costs. A single block list written to stop training also removes the site from AI search answers.

  • Trusting the user agent string. Anyone can send it. Count a request as a vendor’s crawler only when its address is in the vendor’s published ranges.

  • Blocking Google-Extended to leave AI Overviews. Google-Extended governs Gemini training and grounding in Gemini Apps, not Search. AI Overviews and AI Mode follow the rules for Googlebot and the snippet controls.

  • Reading robots.txt and stopping there. A CDN or a firewall can refuse a crawler before it reads the file. The server logs show what the rules cannot.

How QueryRev treats it.

QueryRev reads crawler access beside the AI answers it tracks: for each AI surface, whether its search crawler may fetch the page that should be cited, with the robots.txt line that decides it. A page closed to the crawler that would cite it becomes a finding with that rule quoted, and changing the rule is a change to the site like any other, approved and written to the Change Ledger. The figures above are from QueryRev’s study of AI crawler access.

Questions people ask.

Does blocking AI crawlers hurt Google rankings?

Blocking other companies’ AI crawlers has no effect on Google Search. Google-Extended, Google’s own AI token, is not used for ranking and does not change whether a page is included in Search. Blocking Googlebot does, because classic results, AI Overviews and AI Mode all rely on it.

How do I know if an AI crawler visited my site?

Search the server logs for the crawler’s product token in the user agent, then check that each request came from an address in the vendor’s published IP list. Analytics tools that run in the browser often miss crawlers, because crawlers do not run the tracking script.

Should I block AI crawlers?

Decide by purpose. Refusing a search crawler removes the site from that engine’s answers; refusing a training crawler asks that content not be used for training, without changing that vendor’s search; a fetch on a user’s request may not follow robots.txt at all.

Sources and citation.

Primary sources only: the search engines, the AI vendors, standards bodies and QueryRev’s own research. Each is cited in the text by its number.

  1. Overview of OpenAI CrawlersOpenAI ·

  2. Perplexity CrawlersPerplexity ·

  3. Google’s common crawlersGoogle Crawling Infrastructure ·

  4. AI features and your websiteGoogle Search Central ·

  5. State of AI crawler access, October 2026QueryRev Research ·

Cite this definition

A suggested citation. Its link goes to the definition, whose anchor does not change.

QueryRev Research. “AI Crawler.” QueryRev AI glossary, 18 October 2026. https://queryrev.com/glossary/ai-crawler#definition

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