AI Crawlers: Which Bots Visit Websites and What Are They Looking For?

AI crawlers are changing how websites are discovered, analysed and used across the internet. Alongside traditional search engine bots, websites now receive visits from automated systems operated by OpenAI, Anthropic, Google, Perplexity and other organisations developing artificial intelligence services. Some collect information for AI model training, while others support search results or retrieve content to answer individual questions. Understanding these differences matters for website owners, marketers and SEO specialists. In 2026, managing AI crawlers means knowing which bots access a website, what information they collect and how their activity can affect content visibility, server resources and control over published material.

What Are AI Crawlers and How Do They Work?

An AI crawler is an automated program that visits websites to retrieve publicly accessible information for artificial intelligence systems. Its basic operation resembles that of a traditional search engine crawler: it requests a webpage, reads the available content and may follow links to other pages. However, the information collected can serve different purposes. Rather than contributing exclusively to a search index, it might support AI training, improve search responses or provide factual information for an answer generated in real time.

AI crawlers generally encounter the same website elements as other automated visitors, including headings, paragraphs, hyperlinks, product descriptions, tables and structured data. They may also request PDF documents, images or other publicly available resources, depending on their capabilities. A website’s HTML structure helps automated systems identify where information appears and how different sections relate to one another. Content hidden behind authentication, inaccessible through ordinary requests or dependent on unsupported scripts may be harder for certain crawlers to retrieve.

Not every visit from an AI-related user agent represents the same activity. Automated training crawlers may collect material for later processing, search crawlers discover information that could become relevant to future queries, and user-triggered agents retrieve particular pages when somebody asks an AI assistant a question. These distinctions influence how website owners should interpret traffic logs and configure access. A request from a training bot does not establish that the material will be used for model training, just as a visit from a search bot does not guarantee that the page will appear in an AI-generated answer.

The Main Types of AI Crawlers and Their Purposes

Training crawlers collect web material that may contribute to developing or improving language models. GPTBot, operated by OpenAI, and ClaudeBot, operated by Anthropic, belong to this category. Another important example is CCBot, operated by Common Crawl, which collects publicly accessible webpages for an open web archive. Common Crawl is not exclusively an AI training service, but its datasets can be used by researchers and organisations developing machine learning systems. These crawlers may revisit websites periodically, although their schedules and selection criteria differ.

AI search crawlers perform a different function. OAI-SearchBot supports website discovery for ChatGPT search features, while Claude-SearchBot helps Anthropic improve search results. PerplexityBot serves a comparable discovery role for Perplexity. Their purpose is to make online information available for search-related functions rather than simply assemble training datasets. This distinction gives publishers an opportunity to make different access decisions: a website can potentially permit discovery for AI search while restricting specific bots associated with model training.

User-triggered agents form a third category. ChatGPT-User, Claude-User and Perplexity-User may retrieve pages in response to requests from people using their respective services. Unlike broad automated crawlers, their activity can be connected to a particular information request. For example, somebody asking an assistant to compare product specifications might cause the service to retrieve relevant product pages. These agents do not all follow identical access rules, and some user-initiated requests may be treated differently from routine crawling. Their activity should therefore be assessed separately from scheduled indexing or data collection.

Which AI Bots Visit Websites in 2026?

Several technology companies operate identifiable AI crawlers, often with separate user agents for different tasks. A user agent is the name supplied by a requesting program when it contacts a website. It can help administrators recognise automated traffic in server logs, although the name alone does not prove that a request genuinely came from the organisation it claims to represent. The most relevant bots for many publishers belong to OpenAI, Anthropic, Google and Perplexity, with Common Crawl also playing a significant role in distributing publicly available web datasets.

OpenAI identifies GPTBot, OAI-SearchBot and ChatGPT-User as distinct agents. GPTBot collects information that may be used to improve generative AI models, whereas OAI-SearchBot supports discovery for ChatGPT search. ChatGPT-User handles certain requests initiated by users. Anthropic makes a similar distinction between ClaudeBot, Claude-SearchBot and Claude-User. Perplexity identifies PerplexityBot for search-related crawling and Perplexity-User for user-initiated retrieval. These separate identities matter because blocking one category of bot does not necessarily restrict every service operated by the same company.

Google requires particular attention because its AI-related content controls work differently. Googlebot remains central to discovering and indexing webpages for Google Search, including content that may appear in AI Overviews or AI Mode. Google-Extended, meanwhile, is a robots.txt control token rather than a separate crawler sending requests under that name. It allows publishers to restrict certain uses of their content for Gemini model training and related grounding functions without directly affecting ordinary Google Search inclusion. Consequently, website owners should not expect to find requests labelled Google-Extended in their server logs.

What Information Do AI Crawlers Look for on Websites?

AI crawlers can retrieve many types of public information, but the value of individual elements depends on the purpose of the visit. Editorial websites provide articles, explanations, author information and references. E-commerce websites contain product names, prices, descriptions, availability details and comparison tables. Business websites may offer opening hours, addresses, service descriptions and contact information. For search-related retrieval, accurate answers to identifiable questions are particularly useful because they can help an AI service respond to a user’s immediate information need.

Information quality also influences how useful retrieved content can be. A detailed product page containing current specifications, clearly stated prices and practical usage information offers more factual material than a page dominated by generic promotional claims. Similarly, an article identifying its sources, publication date and author provides context that readers and automated systems can assess. Clear headings, descriptive links and well-organised paragraphs make relationships between topics easier to recognise. However, no particular formatting technique guarantees that a crawler will select a page or that an AI service will cite it.

Freshness matters most when information can change quickly. A restaurant’s opening hours, a product’s availability or a company’s current service conditions may become inaccurate within weeks. Crawlers can retrieve updated content, but they do not necessarily revisit every website immediately after a change. Pages containing conflicting dates, outdated figures or inconsistent descriptions may therefore create problems when information is reused. Publishers should make meaningful updates when facts change, maintain consistent details across important pages and avoid changing publication dates merely to make old material appear recent.

How to Monitor and Control AI Crawlers on Your Website

Managing AI crawler access begins with understanding the website’s objectives. A publisher seeking greater visibility in AI-assisted search may choose to allow recognised search crawlers while restricting automated collection for model training. Another organisation may prioritise limiting access to proprietary research or expensive-to-produce content. These decisions should be made separately for each relevant service because a single universal rule may unintentionally block useful discovery. Website administrators also need to consider ordinary search visibility, the behaviour of user-triggered agents and the possibility that unwanted automated traffic will ignore published restrictions.

The standard starting point is the robots.txt file, normally available at the website’s root address. This file communicates crawling preferences through instructions associated with particular user agents. For example, a publisher can disallow GPTBot while continuing to permit OAI-SearchBot. Anthropic provides separate controls for ClaudeBot and Claude-SearchBot, and Google offers the Google-Extended token for specific AI content uses. These instructions are intended for compliant crawlers, not as a security barrier. Private information must remain protected through authentication and appropriate server-side access controls rather than relying on robots.txt.

Technical monitoring provides evidence of how bots actually interact with a website. Server access logs can show requested URLs, timestamps, response codes, user agents and source IP addresses. Repeated requests to product categories, articles or documentation sections may reveal which parts of a website attract automated traffic. However, user-agent strings can be falsified, so suspicious or important requests should be checked against published IP ranges or other verification methods. Google Search Console provides useful information about Google’s crawling and search performance, but it is not a complete record of visits from independent AI crawlers.

Practical Steps to Improve AI Search Visibility Without Losing Control

The first priority is ensuring that valuable public content is accessible and understandable. Important pages should return successful server responses, contain meaningful information in readable HTML and be reachable through ordinary internal links. Descriptive page titles, logical headings and consistent navigation help automated visitors understand a website’s organisation. XML sitemaps can support URL discovery, although submitting a page does not guarantee crawling or inclusion in search results. Websites relying heavily on JavaScript should also check whether essential content is available to the crawlers they intend to permit.

Content improvements should address genuine visitor needs rather than speculative ranking shortcuts. Original research, practical examples, verified figures and clearly explained comparisons give readers information that cannot be obtained from interchangeable summaries. Author credentials, transparent sourcing and accurate business details can strengthen credibility where relevant. Structured data may clarify supported information about products, organisations or articles, but it should accurately reflect visible content. Creating an llms.txt file is not a requirement for inclusion in Google Search AI features, and its presence should not be treated as a substitute for established SEO practices.

AI crawler management is ultimately an ongoing editorial and technical responsibility. Website owners should periodically review access logs, confirm that robots.txt instructions reflect their current preferences and check whether important content remains accurate and accessible. They should also distinguish between bot visits, actual citations in AI answers and measurable referral traffic, since these are separate outcomes. Allowing an AI search crawler creates an opportunity for discovery, not a promise of visibility. A sensible approach in 2026 combines selective access controls, reliable website maintenance and genuinely useful content that answers real questions.