AI Crawler

An AI crawler is a bot that visits web pages on behalf of a large language model or AI search product, rather than on behalf of a traditional search engine index. The pages it collects either train a model or feed a live response, and which of those two jobs it's doing changes how a website should treat it.

The two jobs AI crawlers do

Training crawlers — GPTBot from OpenAI, Google-Extended from Google — collect content that becomes part of a model's training data. Once collected, that content shapes how the model answers questions generally, not just for one specific query. There's a long lag between a training crawler's visit and any visible effect; the content becomes part of the model's general knowledge the next time it's retrained, which could be months away.

Grounding crawlers work differently and faster. PerplexityBot is the clearest example: it visits pages in real time, at the moment a user asks a question, to pull current information into that specific response. A page visited by a grounding crawler this afternoon can show up in an answer this evening. This is also why freshness matters more for grounding-crawler visibility than for training-crawler visibility — see content freshness for the mechanics.

Google itself runs a version of both. Its standard crawler feeds the search index; Google-Extended specifically feeds Gemini's training; and AI Overviews draw on a mix of the live index and the Gemini model at generation time.

Configuring robots.txt for AI crawlers

Most robots.txt files say nothing explicit about AI crawlers, which means the crawlers default to whatever the general Allow/Disallow rules say. That's often fine, but it's an unexamined default rather than a decision. To make it a decision, add explicit rules:

User-agent: GPTBot
Allow: /

User-agent: PerplexityBot
Allow: /

User-agent: Google-Extended
Allow: /

Or, to block a specific crawler — for instance if a business is uncomfortable with its content feeding a competitor's model training set:

User-agent: GPTBot
Disallow: /

Blocking has a cost, though. A business that disallows GPTBot is opting out of any chance of being cited in ChatGPT's answers that rely on that crawl. For most local businesses trying to build AI visibility, the calculation favours allowing the crawlers, not blocking them.

A common mistake: confusing robots.txt with llms.txt

Robots.txt controls access — which crawlers may fetch which pages. llms.txt is a newer, separate file that gives AI systems a curated summary of what's on a site and where to find it, closer to a sitemap written for a language model than an access control list. A site can have a wide-open robots.txt and no llms.txt at all, or a tight robots.txt and a detailed llms.txt — they solve different problems, and businesses that set up one and assume it covers the other end up with gaps.

Another mistake is disallowing AI crawlers by accident through an overly broad rule meant for something else — a Disallow: /*?* pattern intended to block tracking-parameter URLs, for example, can inadvertently catch pages an AI crawler would otherwise index.

India context

Most Indian business websites — built on WordPress, Wix, or a basic custom template without much SEO attention — ship with a default robots.txt that says nothing about AI crawlers one way or the other. That's a gap rather than a strategy. Adding explicit Allow rules for the major crawlers is a five-minute technical fix with no downside for a business trying to build citation presence in ChatGPT, Perplexity, or Gemini, and it's one of the few AEO actions that requires no ongoing maintenance once it's done.

A Jaipur-based hospitality group running fifteen properties across Rajasthan, for example, would want GPTBot and PerplexityBot explicitly allowed across every property's subdomain or subdirectory, since a traveller asking Perplexity "which heritage hotels in Jaipur have pools" depends on PerplexityBot having actually crawled each property page.

Related terms and next steps

AI crawlers are the access layer beneath everything else in AEO — see llms.txt for the curated-summary layer, RAG for how grounding crawlers' output gets used at answer time, and grounding for the underlying mechanism. Angryturtle's llms.txt Setup Service handles both the robots.txt configuration and the llms.txt file together, since most clients need both done at once rather than one at a time. For the broader discipline this sits inside, see Answer Engine Optimization and AEO Services.