AI Crawlers: Definition, Function, and Why They Matter for Business

An AI crawler is an automated bot that browses websites to collect content, which AI companies then use to train models, power AI-based search, or answer user requests.

Over the past two to three years, AI has advanced very rapidly. AI-powered search engines and assistants are now where many people turn for answers, and that’s changing how content gets discovered and consumed. This means that behind the scenes, AI agent crawl bots are constantly pulling large volumes of content from websites to support these services.

The numbers are striking. In 2025, CDNetworks recorded around 1.64 million AI bot requests per day, 72.67% of which were related to data scraping and content retrieval. As the AI ecosystem keeps growing, AI crawlers will keep collecting content, whether or not a business is ready for it.

For this reason, it’s important for businesses to understand who is accessing their content and why. This article will cover what AI crawlers are, their functions, how they work, and the types of data they collect, so you can manage access to your company’s digital assets appropriately. Read on to learn more!

What Is an AI Crawler?

Put simply, it is a bot that crawls for AI, that automatically browses websites and online sources to collect data for AI systems, without needing direct human control.

AI crawl agents don’t only work to answer user requests; they also help train models. Nearly every AI company has its own crawlers, each with a different purpose, such as:

• GPTBot (OpenAI): For model training.
• OAI-SearchBot (OpenAI): For ChatGPT’s search feature.
• ClaudeBot (Anthropic): For model development.
• Claude-SearchBot (Anthropic): For AI-powered search.
• Claude-User (Anthropic): For retrieving content at a user’s request.
• PerplexityBot (Perplexity): For discovering content through search.
• Perplexity-User (Perplexity): For retrieving content at a user’s request.

AI Crawler Functions: What Are They For?

The main function of an AI crawler is to gather information at scale, so AI systems can learn from it, improve over time, and respond to user requests as effectively as possible. The data collected serves several purposes:

• Training AI models to understand language, images, or code.
• Improving the accuracy, relevance, and general knowledge of models.
• Keeping AI systems aligned with up-to-date, real-world information.
• Powering AI-based features, such as chatbots, text summarization tools, and recommendations.

Read also: What Is Answer Engine Optimization (AEO)? A Guide to Optimizing Business

Do AI Crawlers Matter for Businesses?

AI crawler activity can be a valuable asset for companies through content discovery and AI visibility. By accessing and processing website content, AI crawlers help their systems find relevant information to support the answers they generate, which in turn boosts brand visibility across AI platforms such as ChatGPT, Gemini, and Perplexity.

However, how much you benefit depends on which AI crawlers visit your site, why they’re crawling, and what access policies you have in place. Not all AI crawlers serve the same function, because some collect data purely to train AI models, while others retrieve information to support search and generate answers based on current sources.

Potential Risks and Concerns Caused by AI Crawlers

While AI crawlers offer opportunities to boost your business’s visibility on AI platforms, their activity can also bring risks. If not managed properly, it can raise concerns in the following areas:

• Infrastructure and user experience: AI crawler activity can trigger traffic spikes that strain servers and overwhelm systems. As a result, web pages load more slowly and user sessions often time out.
• Financial impact: High volumes of AI crawler traffic can push bandwidth usage past its quota, forcing companies to upgrade their infrastructure at a high cost.
• Analytics disruption and data integrity: Large amounts of invalid traffic can skew website metrics such as page views and bounce rate. Unreliable metrics then make it harder for companies to evaluate performance and make decisions.
• Impact on content and intellectual property: Content and data such as exclusive research, technical documentation, and user-generated content can become training material for AI systems that often fail to credit the original source.
• Risk of business information leakage: With the ability to extract data in depth, AI crawlers can give competitors detailed analysis and insight into a company’s business strategy and operations.

These risks may sound too dangerous to ignore. However, blocking all AI crawler traffic can backfire, because more and more customers and businesses are using AI platforms, and a business that opts out risks being left behind in the AI era.

On the other hand, letting all AI crawler traffic through will have the direct consequences described above. So, to adapt while also anticipating the risks, you need to manage AI crawler activity by weighing content accessibility, infrastructure needs, and business strategy.

How AI Crawlers Work

AI crawlers work in several stages. First, the crawl AI agents visit a predefined list of website addresses (URLs), then discover new pages through links and sitemaps.

Before reading a page, a compliant crawler checks the robots.txt file, which contains the website owner’s rules about which sections can and cannot be accessed. Keep in mind that robots.txt is more of a request than a barrier: it only works if the crawler’s operator chooses to respect it.

Next, the crawler sends a request to the server to fetch the page, reads its HTML code, and extracts key content such as text, headings, and links. Any new links it finds are added to the queue of pages to visit, so the same process repeats from one page to the next.

The results are then stored in large volumes and filtered according to their purpose. Some data goes into datasets for model training, some is indexed for AI-powered search engines, and some is passed directly into user conversations.

For crawlers that act on a user’s request, such as Claude-User, the process is shorter: the crawler fetches the URL the user asked for directly, without working through an initial list.

Read also: GEO & AEO KPIs: How to Measure AI Optimization Metrics

AI Crawlers vs Traditional Web Crawlers: What’s the Difference?

AI crawlers serve a broader range of purposes. Besides indexing, they also collect content to develop AI models, power AI-based search, and fetch pages when users request them.

On the other hand, traditional web crawlers, such as Googlebot, browse and index web pages so they can be found through search engines.

The relationship between the two tends to be mutually beneficial: search engines get content to display, while companies get discovered by potential customers through search results. To understand the differences between AI crawlers and web crawlers, take a look at the table below:

Read also: AI Referral Traffic: Definition, Benefits, and How to Measure It

Types of AI Crawlers

AI crawlers fall into several types, each with its own function and purpose. These include:

• AI training crawlers: Collect web content that may be used to develop or improve AI models, such as GPTBot and ClaudeBot. Businesses can restrict them if their content is copyrighted, exclusive, licensed, or commercially sensitive.
• AI search crawlers: Discover and index content for AI-powered search and answers. Examples: OAI-SearchBot, Claude-SearchBot. If blocked, your content may not appear in AI answers. OpenAI itself recommends that publishers allow OAI-SearchBot if they want their content to appear in ChatGPT search.
• User-triggered retrieval crawlers: Fetch page data only when a user asks, for example, when a user pastes a link into an AI assistant, so this type of crawler doesn’t browse the web continuously. Examples: Claude-User, Perplexity-User.
• Data scrapers and unverified crawlers: Crawlers with unclear identities and purposes. This type is the hardest to manage because it doesn’t always follow the rules or disclose its identity.

What Data Do AI Crawlers Collect?

In general, AI crawlers can access any public content found on a website. The type of data they collect depends on the crawler’s purpose. Some of the content and data commonly collected include:

• Page (body content): The main text, headings, lists, and links, which serve as the crawler’s primary source of information. Navigation menus, ads, and footers get read as well.
• Metadata: Information in a page’s head section, such as the title tag, meta description, and social media tags (Open Graph).
• Structured data: Data such as schema markup or JSON-LD. This type of data is invisible to visitors but readable by bots.
• CSS and JavaScript files: Crawlers can download them, but most AI crawlers don’t execute JavaScript. As a result, content that only appears after the page loads may not be read.
• Image metadata: Image files along with their file names and alt text. Crawlers generally don’t understand the content of an image directly, but other AI processes can analyze it later.
• Multimedia: Links to audio and video, along with metadata such as file names and transcripts.
• Other documents: Public files such as PDF, Word, text, and CSV files that can be reached through links can also be accessed by AI crawlers.

Read also: ChatGPT vs Claude: Comparison & Optimization Strategies for Business

Optimize Your Website to Get Cited and Recommended by AI

AI crawlers present two sides for businesses. On one hand, there are real risks such as server load and infrastructure costs, skewed analytics data, and content being used without attribution.

On the other hand, letting the right crawlers access your website can also benefit your business. One benefit is that your brand and content have a chance of earning AI mentions and citations, which raises the likelihood that potential customers will consider your business.

So the question is no longer “should we block or allow AI crawlers?” but rather “which crawlers should we allow, which should we restrict, and on what basis?”

Companies need to start adapting to this AI ecosystem, and the most practical first step is to take the FREE AI Visibility Audit by cmlabs. The audit is 100% free of charge, requires no contract, and takes only 3–5 business days.

Once the audit shows how your company appears in the era of AI search, you can use AI Search Optimization (GEO/AEO) services by cmlabs to boost your visibility across AI platforms such as ChatGPT, Claude, Gemini, and many more.

Every GEO and AEO strategy at cmlabs is tailored to its target platform, from the overall approach to how content is structured so AI can easily reference it. So don’t hesitate to contact our team to help your brand adapt to the AI ecosystem quickly and to learn more about cmlabs’ services.