Do AI Crawlers Respect robots.txt the Same Way Googlebot Does?

Robots.txt has been the standard way to tell crawlers what they can and can’t access since 1994. Googlebot has followed it reliably for decades, so most teams assume every crawler behaves the same way. AI crawlers mostly follow the same protocol, but “mostly” is doing real work in that sentence, and the differences matter if you’re trying to control what ends up in AI answers.

The short answer

Yes, the major AI crawlers, GPTBot, ClaudeBot, PerplexityBot, and Google-Extended, all check robots.txt before crawling and generally respect a Disallow rule addressed to them by name. That part is consistent with how Googlebot behaves.

Where it diverges is compliance guarantees, recrawl behavior, and what blocking actually accomplishes. Those differences change how you should think about robots.txt as a GEO control, not just an SEO one.

Compliance is a company policy, not a protocol requirement

The robots.txt standard, formalized as RFC 9309 in 2022, is a voluntary convention. Nothing in the protocol forces a crawler to obey it. Googlebot’s reliability comes from Google’s own stated policy and reputational incentive to follow the standard it helped establish, not from any technical enforcement mechanism.

AI companies have made similar public commitments. OpenAI documents GPTBot’s behavior and says it respects robots.txt. Anthropic does the same for ClaudeBot. Perplexity states that PerplexityBot honors robots.txt for crawling, though the company has faced public scrutiny over whether some of its real-time fetching behavior, separate from the crawler, follows the same rules as consistently.

The practical takeaway: treat each crawler’s compliance as a company-specific policy you should verify, not a guarantee that comes bundled with the protocol itself.

Google-Extended is not Googlebot

This is the single most common point of confusion. Google-Extended is a separate user-agent token that controls whether Google can use your content to train Gemini and populate AI Overviews. It has no effect on your regular Google Search ranking.

User-agent: Google-Extended
Disallow: /

A site can run this rule, stay fully indexed and ranking normally in Google Search, and still be excluded from Gemini training data and AI Overview generation. Teams that don’t realize these are separate directives sometimes block Google-Extended thinking they’re just managing AI scraping in general, not realizing they’ve opted out of a specific and growing surface for citations. For more on the mechanics of checking this across crawlers, see how to check if GPTBot and ClaudeBot can actually crawl your site.

Recrawl cadence is not the same across crawlers

Googlebot recrawls high-value pages frequently, sometimes within hours of a change, because search freshness is core to Google’s product. AI crawlers don’t operate on the same clock.

Crawler	Primary use	Typical recrawl behavior
Googlebot	Search indexing	Frequent, often within hours to days for active pages
Google-Extended	Gemini training, AI Overviews	Tied to broader training cycles, not page-level freshness
GPTBot	Model training data collection	Periodic, tied to training data refresh cycles
ClaudeBot	Model training data collection	Periodic, tied to training data refresh cycles
PerplexityBot	Real-time retrieval and indexing	More frequent than training crawlers, closer to search behavior

The practical effect: if you update or unblock a page for GEO purposes, don’t expect the same near-immediate reflection you’d see in Google Search. A training crawler might not revisit for weeks, and even then, the content doesn’t show up in a model’s answers until the next training run or fine-tune, not the next crawl. Perplexity’s retrieval-style crawler behaves closer to a search engine, since it’s fetching content to answer live queries rather than to train a model.

Blocking a crawler doesn’t undo what a model already knows

This is the part robots.txt can’t touch. If GPTBot crawled your site in 2024 and that content became part of a training run, adding a Disallow rule today stops future crawling. It does not remove what the model already learned. The information persists in the model’s weights until a future version is trained on a fresh dataset that excludes you, which is entirely outside your control and not something robots.txt can influence.

This matters most for brands trying to correct outdated information. If a model describes your pricing or positioning incorrectly based on stale training data, blocking the crawler now doesn’t fix the existing error, and can actually make it worse by preventing the model from ever recrawling the corrected version.

What to actually do with this

A few practical moves follow from these differences:

• Separate your Google Search strategy from your Google-Extended decision. They’re independent controls. Decide each on its own merits.
• Don’t expect robots.txt changes to show up in AI answers quickly. Budget weeks to months, not days, depending on the crawler and whether the content needs a new training cycle to matter.
• If you’re trying to correct stale brand information, keep crawlers open, don’t block them. Blocking access is the wrong move when the goal is getting a model to learn something new about you.
• Verify behavior with server logs, not just intent. A crawler stating it respects robots.txt is a policy, not a live confirmation that it’s behaving that way on your specific site today.

Robots.txt is still the right first lever to pull for AI crawler access. It’s just not the same lever, with the same guarantees or the same timeline, that you’re used to with Googlebot.