With tools like ChatGPT, Claude, and Perplexity popping up all over the digital landscape, AI is quickly becoming a central part of how people search and interact online. Behind the scenes, these tools rely on AI bots — automated web visitors that access and collect content to help large language models (LLMs) learn, answer questions, or complete tasks.
As these bots become more active across the web, there’s a major decision every web team needs to consider: Do you let these bots access your website or block them?
In this post, we’re breaking down the different types of AI bots, how they work, what they do on your site, and how to decide whether to welcome them — or shut the door.
The 4 Types of AI Bots (and Why They Matter)
Not all AI bots are crawling your site for the same reason. While some are collecting data to train AI models, others are just visiting one page in response to a user query. Understanding the differences can help you make smarter decisions about how to manage them.
AI Data Scrapers
What they do: These bots quietly crawl websites to collect content used for training LLMs. The information they gather becomes part of the model’s foundational knowledge and is not updated in real time. If your site wasn’t part of that initial scrape, the model likely knows very little about it.
Why it matters: Once your content is scraped and used for training, it becomes part of the model’s memory. That data can’t be removed or unlearned later, which is why these bots are central to the discussion around blocking AI access.
Popular bots: GPTBot, ClaudeBot, Google-Extended, Bytespider, CCBot
How they access your site: These bots run independently and tend to visit automatically, irregularly, and without notice. The exact frequency and selection criteria aren’t publicly known, though factors like content density or authority could influence crawl patterns.
AI Assistants
What they do: These bots make one-time visits to specific pages, pulling in live content to help improve the AI’s response. This process is called Retrieval-Augmented Generation (RAG), where the AI combines what it already knows with real-time information from your page.
Why it matters: These bots don’t index your whole site or use your content to train models. They only access a page if a user directly asks the AI to pull in that specific URL, so the visit is temporary and triggered by someone’s prompt, not automated crawling.
Common bots: ChatGPT-User, Claude-User, DuckAssistBot, Gemini-Deep-Research
How they access your site: AI Assistants visit your site instantly when prompted by a user request. Think of them as on-demand readers rather than automated crawlers.
AI Search Crawlers
What they do: These bots work like modern search engine crawlers, scanning and indexing your content so it can appear in AI-generated answers. By building searchable indexes, they help connect static training data with real-time information, powering the links, citations, and references included in AI responses.
Why it matters: If your site is indexed by these bots, it has a chance to show up as a cited source in tools like ChatGPT, Claude, or Perplexity. No indexing usually means no citation. Some AI tools pull this information from traditional search engines like Bing or Google, while others rely on their own proprietary search indexes.
Popular bots: Claude-SearchBot, OAI-SearchBot, Applebot, Amazonbot, PerplexityBot
How they access your site: These bots may crawl your site periodically, or their visit might be triggered by a user request. The frequency and criteria for crawling aren’t always clear, and crawling behavior may vary by platform.
AI Agents
What they do: These bots are activated by users to complete specific, goal-oriented tasks, like booking travel or researching products. Rather than crawling the web, they use tools like ChatGPT’s Agent Mode to interact with multiple websites, navigating step-by-step on the user’s behalf.
Why it matters: They behave more like real users than traditional bots, clicking through and making decisions as part of a task workflow. As these tools grow in popularity, websites may see more bot hits from agents acting on behalf of users, not search engines.
Common bots: ChatGPT Agent, GoogleAgent-Mariner, NovaAct
When they visit: Agents don’t crawl your site automatically, but they do generate bot hits when they visit pages to complete a user-initiated task. Each visited page in the process can result in a bot hit, depending on how many steps the agent takes.
Real-World Examples: How AI Bots Interact with Your Content
Understanding how each bot behaves is easier when you can see it in action.. Below are examples of how AI Data Scrapers, Assistants, Search Crawlers, and Agents interact with real web content.
AI Data Scrapers in Action
In the examples below, you can see how an AI model behaves when it relies solely on pre-existing training data. This typically happens when web search is turned off or is unsupported by the model. In that case, any response it gives is based only on data scraped prior to its last training update.
If your site wasn’t crawled in time, or if your content was updated after the model’s last training cycle, it won’t be reflected in responses until a future version of the model is released.
Example 1: Training Data Cutoff Date
This shows the AI providing its official knowledge cutoff (January 2025) and explaining that recent events may not be reflected accurately in its answers.
Example 2: How the Knowledge Cutoff Impacts the Answer
Here, I asked who won “Best Picture” at a recent Academy Awards. The AI couldn’t answer because the event happened after the model’s last training window. Since no real-time web search was enabled, the AI defaulted to its limited memory.
AI Assistant in Action
Below is what happened when I gave the AI a specific URL to reference. Instead of guessing based on training data, the model made a one-time visit to the page to improve its response, resulting in a bot hit.
Example: AI Assistant Fetches a Webpage to Answer a User Question
Here, I shared a link to the official Oscars webpage. The AI assistant visited the URL, retrieved live content, and included accurate, current details in its response. This behavior reflects how AI assistants temporarily access webpages when prompted.
AI Search Crawler in Action
In the examples below, you can see how LLMs use search-indexed content to enhance their answers and cite sources. These results come from web content that has been crawled and indexed ahead of time.
This indexed content appears when users prompt the AI with a query that benefits from real-time or citation-based enhancements.
Example 1: Claude Uses Web Search to Build an Answer
I enabled web browsing on Claude and asked it to perform a live search to answer a question about the 2025 Oscars. The answer included current information pulled from the web, along with visible citations pointing to external sources.
Example 2: ChatGPT Includes Indexed Results in its Response
Here, ChatGPT used its search mode to gather real-time web results. The upper portion shows AI’s written answer. The lower portion lists the sources that were used to build the reply.
Example 3: ChatGPT Pulls From Google-Indexed Content
Backlinko tested whether ChatGPT uses Google Search to power its answers. After creating a fake SEO term and allowing Googlebot (but no other crawlers) to access the page, they found that ChatGPT cited the content, confirming it was using Google’s index.
AI Agent in Action
In the examples below, we follow how an AI agent carries out a task. In this case, the task is booking a flight. Unlike AI assistants that fetch a single page, agents perform multi-step interactions across multiple websites. Each step along the way may trigger a separate bot hit.
Example 1: The Task Begins with a Travel Request
I told the AI I want to book a flight from ORD to LAX. This prompt initiated the agent workflow, setting the stage for a sequence of automated actions.
Example 2: Agent Prepares its Workspace
Before interacting with external websites, the agent set up its environment to carry out the task. This signaled that the agent was ready to take over and process without additional user input.
Example 3: Agent Navigates to an External Website
In this step, the agent visited Google Flights to begin searching for flights. This resulted in a measurable bot hit, just like with a human user loading the page.
Example 4: Agent Completes the Booking Steps
The agent continued filling out details like destination, date, and more, just as a user would. Every page visited or form submitted may result in further bot hits on different parts of the site.
Should You Block AI Bots?
This is one of the biggest questions site owners are asking today, and honestly, the answer depends on how you use your content.
Reasons to Block
Blocking bots might make sense if your content is sensitive, proprietary, or you just want more control.
- Protecting proprietary or premium content
- Preventing unauthorized use in AI models
- Avoiding potential traffic loss from AI answers replacing site visits
- Preserving your business edge
Reasons to Allow
That said, there are some solid arguments for leaving the door open:
- Getting more visibility in AI-powered search results
- Earning referral traffic from citations or direct links
- Creating a smoother experience for people using AI tools to research your brand
If your goal is reach and exposure, this route might work in your favor, especially in industries where brand awareness matters.
Finding the Middle Ground
If you’re not ready to fully block or allow AI bots, there are ways to strike a balance. These approaches are often case-by-case and depend on your content strategy.
- Selective Access: Allow LLMs to crawl public or evergreen content while blocking premium, proprietary, or sensitive pages.
- Time-Delayed Access: Give bots access to older content while keeping recent or time-sensitive data private.
- API Integration: Integrate with AI platforms through APIs that offer more control and potential monetization.
- Bot-Specific Rules: Block certain bots (like GPTBot for training) while allowing others (like Applebot for search indexing).
How to Control LLM Access via Bot Blocking
If you’ve decided to block (or selectively allow) access, the next step is executing that technically. Here are three common ways to do it:
Option 1: Block Training Bots Only
Some bots — like OpenAI’s GPTBot or Anthropic’s ClaudeBot — are specifically used to collect training data for LLM models. These can be blocked via your robots.txt file without affecting bots used for citations or real-time assistance.
Option 2: Block All LLM Bots
To prevent all LLM-related access, including models acting as search crawlers, assistants, or agents, you can block all known bots through robots.txt.
Just be aware: Blocking all bots may reduce your visibility in AI-enhanced search results (like Perplexity), ChatGPT responses that cite sources, or even tools like Siri that depend on Applebot.
Option 3: Use a Security Layer
Edge security tools allow you to block specific AI bots at the request level before they even reach your server. This is useful for bots that ignore robots.txt files or when you need more granular control.
Cloudflare, for example, offers a built-in bot management feature that requires minimal setup.
AI Bot Reporting: Interpreting the Data
A crucial part of managing your site’s AI visibility is understanding how AI bots interact with your content. It’s not just about whether bots are visiting, but which types, how often, and why.
By segmenting traffic by bot name and function, you can uncover whether your content is being used to train models, fuel AI-powered search indexes, or support real-time assistant queries.
Trends by Bot Function
In the example below, we see that AI search crawlers are driving most of the activity, while data scrapers are far less active. That tells us this site is more likely being cited in AI-generated responses than being used to train models.
Trends by Specific Bot
Now, if we cross-reference that data with the actual bots, we can see that Applebot is performing the most crawling to build up their search index for tools like Siri, Safari, etc. Most of the ChatGPT crawling comes from their AI-Assistant bot, which means users are likely telling ChatGPT to access specific webpages.
Take Control of Your AI Visibility
AI has introduced a new layer of complexity (and opportunity) for content and SEO strategy. Visibility no longer just happens through search engines. It happens through scrapers, assistants, agents, and real-time AI results.
Whether your goal is protection, exposure, or a smart blend of both, LOCOMOTIVE can help you understand your bot activity and create a strategy that aligns with your goals.
Connect with our team today to get started.
