The value of original content online is huge. Companies invested in content over decades, spending much time and money.
Then generative AI emerged and decided to use this content to train large language models (LLMs) and power their AI-driven services. AI scrapers silently scan websites across the internet, collecting content for free and without permission from website owners.
The content of your websites, mobile apps, and APIs is valuable and should be protected from unauthorized AI scrapers. When your content is used to feed AI models, it could ultimately reduce traffic to your site and generate profits for generative AI companies instead.
While some AI companies transparently identify their bots, others don’t, potentially monetizing your content without your permission or compensation.
Read this article to know what AI crawlers are, how to detect them, and how you should block them.
What Are AI Scrapers and Why Are They Collecting Your Content?
AI scrapers are automated tools that crawl websites to collect large volumes of text, images, and structured data. Unlike traditional search engine crawlers, these bots aren’t just indexing pages for ranking— they’re gathering raw material to train large language models (LLMs).
Anything you’ve ever posted online has almost undoubtedly been crawled and used as training materials for the generative AI. From news and product descriptions to blog posts, FAQs, and forum threads, publicly available content is valuable because it reflects how real people describe and advertise products, raise and answer questions, think and solve problems.
Even a cringey tween or outdated blog post is valuable data for AI bots, since the broader and more diverse the data, the better it is for generative AI models that use this data to learn about real life and generate natural responses.
For website owners, it means lost traffic and monetization possibilities.
The most prolific AI crawlers currently operating include:
- GPTBot (OpenAI)
Collects training data for ChatGPT-5 and future iterations. It is incredibly prolific but generally respects robots.txt instructions. - ClaudeBot (Anthropic)
Currently it is considered as one of the most aggressive AI crawlers. Cloudflare data in late 2025 indicated that Anthropic bots’ crawl-to-refer ratios range from 38,000:1 to over 70,000:1, meaning they crawl from 38,000 to 70,000 pages for every 1 user they respond. That means Anthropic crawls significantly more content than it refers back to publishers. - Bytespider (ByteDance)
Collects data for TikTok and Doubao, the ChatGPT competitor. It is one of the most aggressive bots, as it often ignores the crawl-blocking settings. - OAI-SearchBot
Belongs to OpenAI and is used to feed its SearchGPT features. Blocking this doesn't stop training; however, it will not deliver your site as a cited source in ChatGPT search results. - PerplexityBot
The crawler for Perplexity AI. It is mostly used on news and reference sites to provide real-time citations. - CCBot (Common Crawl)
A non-profit crawler that has been crawling the web for over a decade. It builds datasets used by numerous AI models. - Diffbot
An AI-native crawler that turns web pages into structured databases. It is frequently used by enterprise AI agents to understand e-commerce pricing and company data at scale.
Why Block AI Bots?
Artificial intelligence has many benefits for customers. It can improve society in many good ways, from solving everyday problems to helping to diagnose an illness or making predictions. However, business owners have legitimate concerns about the proliferation of AI.
AI bots could cause damage to business owners, including:
- Content monetization without compensation
AI crawlers scrape your content without permission or any compensation. They’re essentially using your original content to build products they profit from. Your site crawling becomes particularly harmful when:
You’ve invested significant resources in creating intellectual property.
Your business model relies on original content creation.
Your competitive advantage comes from unique digital resources. - Competitive disadvantage
AI bots trained on your content can generate similar results that compete with your business. That means that your business would use traffic, while AI-driven companies could get nearly identical material without an investment in research and development. - Content misrepresentation
AI bots could even cite your business. However, they could present outdated or inaccurate information in their responses, potentially damaging your brand reputation. - Increased server load and costs
High-volume AI crawling can significantly increase your server load, that could slow down your website for real users, increase your infrastructure costs, and consume bandwidth without additional business benefit. - Legal considerations
When AI crawlers use your content without permission, it could create additional problems, such as generated content that conflicts with brand values or content that violates copyright laws by reproducing content without permission.
Thus, many businesses want to detect and block AI crawlers that use their content to train AI bots.
Are AI Scrapers Legal Under GDPR and Global Privacy Laws?
Legality depends less on the act of scraping itself and more on what data is collected and how it’s used. Scraping purely non-personal, factual content is legally compliant. However, scraping personal data, such as names, emails, user-generated comments, and other identifiers without user consent does not comply with most privacy laws.
GDPR in Europe, CCPA in the US and similar frameworks require AI companies to comply with data privacy principles, including:
- AI companies must identify a lawful basis for processing personal data.
- AI companies must apply purpose limitation principles.
- AI companies must respect data minimization principles.
Public availability alone does not automatically remove these obligations. Ai scrapers that collect personally identifiable information (PII), must comply with data privacy laws and respect data privacy principles, even if content is publicly available online.
What Regulators Say About AI Training and Personal Data
As of early 2026, the regulatory grace period for AI has officially ended. Regulators in the EU and the US have moved from merely observing AI to enforcing strict rules, particularly regarding how personal data is harvested and used for training Large Language Models (LLMs).
Regulators have been clear on one point: public data does not mean it is free to use for any tasks. Several data protection authorities have emphasized that AI training is a distinct processing purpose that must be assessed on its own merits.
Regulators in the European Union: the AI Act is now law
Europe’s AI Act is the world's most comprehensive framework, regulating AI scrapers. In 2026, its transparency and Data Governance requirements regulate how generative AI could use personal data.
- Public Summaries (Article 10)
Companies training general-purpose AI must now publish a summary of the datasets used. - Copyright opt-outs
Under the EU Copyright Directive, AI bots must respect websites’ technical signals like robots.txt to opt out of AI training. It AI scrappers still use such data for AI training, regulators will consider using that data a violation of both IP and privacy laws. - High-risk data governance
If an AI is used for high-risk tasks, such as hiring or credit scoring, the data used to train it must be "relevant, representative, and to the best extent possible, free of errors."
The United States: California and the FTC Lead
While the US does not have federal AI law yet, California’s CCPA/CPPA and the FTC have created a de facto national standard.
- California’s opt-out right
As of the beginning of 2026, California residents have a specific right to opt out of Automated Decision-making Technology (ADMT). This includes the right to stop their Personal Information from being used to train AI systems. - Pre-use notices
Businesses in California must now provide a pre-use notice that explains exactly what data is being fed into an AI and what the intended output is. - The FTC’s power
The FTC could use its power to order companies to delete entire AI models if they were trained on data obtained through deceptive means, such as changing a Privacy Policy after the data was already collected, or collecting personal data without user consent.
Can a Privacy Policy Legally Block AI Training?
No, a Privacy Policy alone is not a suitable enforcement tool to block ai training. It is most commonly used to inform customers about your data collection and processing practices. A Privacy Policy can state your intentions, expectations, and restrictions for AI scrapers, but it does not stop AI bots from scraping your content. Most AI scrapers do not read or honor privacy policies in the way humans do.
However, a well-written policy can still matter regarding AI training using your data:
- It establishes your position if disputes arise.
- It supports contractual or legal arguments later.
- It demonstrates compliance to regulators.
The Limits of Consent When Content Is Publicly Accessible
User consent becomes complicated when content is openly published. Customers may consent to analytic cookies or other website trackers, but that does not automatically mean that they consent to third-party AI training uses. If users never interact directly with the AI companies and don’t provide consent for them to use their data, AI companies can’t rely on consent.
Even for site owners, relying on implied consent is risky. For AI developers, retroactively proving consent at scale is nearly impossible.
Since AI crawlers are prolific and even aggressive, regulators are paying close attention to AI scraping practices.
Websites use Consent Management Platforms (CMPs) to collect and manage cookie consent.
CookieScript CMP is valued by users. In 2025, CookieScript received the fourth consecutive badge in a row as the leader on G2, a peer review site, and became the best CMP on the market for a whole year!
CookieScript CMP can manage user consent in detail, performing the following tasks automatically:
- Scanning your website for cookies
- Providing a professional cookie banner
- Geo-targeting users and providing the right Cookie Banner, depending on local regulations
- Categorizing and adding descriptions to your cookies
- Maintaining a full history of user consents
- Allowing users to withdraw consent at any time
- Blocking third-party cookies by default until visitor consents
How AI Companies Interpret Website Restrictions Today
In practice, AI companies prefer to honor machine-readable signals. Robots.txt rules, meta tags, and IP-based controls are more likely to block AI scraper training on your data than legal texts present in a Privacy Policy page.
There is no universal standard yet on how to use publicly available content for AI training.
Some AI companies voluntarily respect no AI training signals. Others rely on interpretations of legitimate interest, public availability, or anonymization.
The lack of standards is definitely the problem.
How Website Owners Are Responding to LLM Data Collection
Responses vary widely. Some companies openly license their data to AI companies and even encourage AI crawlers to scrape their websites. Such businesses believe that AI bots could boost traffic to their sites thus, they try to make their websites LLM-ready.
Other businesses, especially publishers, want to keep their content just for themselves. They actively block scrapers and update their privacy policies to reflect AI-specific concerns.
Many are simply trying to understand what’s happening to their content for the first time.
What’s clear is that awareness is growing. Website owners are no longer assuming that bots are just search engines, that should be encouraged to scrap your site. AI bots try to use your content for monetization without permission or any compensation, so this could become a huge competitive disadvantage for your business. That shift in awareness is reshaping content strategy, competition, monetization, and compliance planning.
Technical Ways to Block AI Scrapers Beyond Legal Text
In 2026, the landscape of AI scraping has shifted from simple bots to autonomous Agentic AI that can mimic human browser behavior. Blocking these effectively requires a multi-layered technical approach. Common approaches include:
1. The machine-readable reservation layer
- Robots.txt
It’s the most commonly known format to rule targeting known AI user agents. - Text and Data Mining Reservation Protocol (TDMRep)
This is the high-integrity standard for 2026. It can be implemented via: - Well-Known Path
Host a file at /.well-known/tdmrep.json. This provides a structured way to say "No AI Training" that regulators and compliant crawlers like those from Adobe or European labs prioritize. - HTTP headers
Add TDM-Reservation: 1 to your server's response headers. This is faster than a file fetch and works for non-HTML files like PDFs and images. - AI-specific meta tags
Use the noai and noimageai tags. While not yet a universal standard like noindex, many ethical scrapers now scan for:
<meta name="ai-usage" content="no-training, no-summarization">
2. Infrastructure & edge defenses (WAF)
Sophisticated scrapers often ignore polite requests. At the network level, you can block AI scrapers by changing its User-Agent string.
- JA4 TLS Fingerprinting
Modern Web Application Firewalls (WAFs) like Cloudflare or Akamai now use JA4 fingerprinting. This identifies the specific handshake of a Python library (like requests or playwright), even if the bot claims to be a standard Chrome browser. - AI labyrinth (honeypots)
You can set up trap links visible only to bots (e.g., display: none; for humans). If an IP accesses these, blacklist these bots instantly. Advanced versions feed these bots infinite recursive loops of nonsensical data, exhausting the scraper's token budget and compute resources. - Rate-limiting on semantic density
Instead of just blocking high request volumes, block based on the type of request. AI scrapers often hit content-heavy pages (articles, documentation) while ignoring utility pages (login, settings). Monitoring this ratio helps detect AI-driven intent.
3. Controlling agentic protocols (MCP & A2A)
In 2026, AI agents interact via protocols like Anthropic’s MCP (Model Context Protocol) or Google’s A2A (Agent-to-Agent). These agents look for a map of your site to understand how to use it.
- Restricting agent.json
Agents often look for /.well-known/agent.json to understand your site's API or structure. Deleting this file or restricting access to it prevents autonomous agents from learning how to scrape your database. - Proof of personhood (PoP)
Implement Cloudflare Turnstile or hCaptcha. Unlike old CAPTCHAs, these use private access tokens that allow verified humans through without a click, but force unverified agents to solve complex cryptographic puzzles that are expensive for them to run.
Practical Steps to Reduce AI Scraping Risk in 2026
If you want to reduce exposure without overreacting, focus on realistic steps:
- Monitor your traffic regularly
Monitor server logs for unusual crawler behavior, like sudden spikes in traffic from unusual sources, or systematic requests for large amounts of content. - Take a layered approach
Don’t rely on a single method. Combine multiple approaches for maximum effectiveness. You can start with robots.txt for well-behaved bots, then add HTTP headers for additional signaling, and implement technical barriers where feasible. - Use AI-Specific Extended Tokens
Instead of blocking all bots, target the specific AI training flags. - Update your blocking strategy
AI crawlers continuously evolve their techniques. Regularly update your blocking methods by being informed about new AI crawlers, or by updating your robots.txt with newly identified user agents. - Deploy "No-AI" Meta tags
Add "No-AI" Meta tags to your <head> to signal to scrapers that analyze HTML metadata. - Implement selective access or licensing
Not all bots are harmful. Allows legitimate search engine crawlers and bots that benefit your business like SEO bots or social media link previewers. Make sure not to block actual users. - Implement defensive protection layer
For your most valuable intellectual property, use technical traps that make scraping expensive and difficult. Use AI bot challenges like Cloudflare Turnstile or hCaptcha. Create ghost links that are invisible to humans but attract bots. Use tools like Nightshade or Glaze to poison images by adding invisible pixel-level noise to your images. - Implement legal protection
Beyond technical measures, consider legal protection. Update your privacy policy and terms of service to explicitly prohibit unauthorized data scraping for AI training. Include clear statements about AI training restrictions. - Implement TDMRep
In 2026, the Text and Data Mining Reservation Protocol is the gold standard for legal opt-outs in Europe. - Implement API-first strategy
Serve your most valued data via a secured API rather than raw HTML. This allows you to charge AI companies for access while blocking unauthorized scrapers.
Blocking AI scrapers entirely may not be realistic, but reducing risk, clarifying intent, and maintaining compliance absolutely is.
Frequently Asked Questions
Why block AI crawlers?
Blocking AI crawlers helps protect your original content from generative AI companies that could use your content without permission or compensation to train AI models that may compete with your business, misrepresent your content, increase server load and costs, or profit from your intellectual property without your knowledge.
Can I block AI scrapers and still license my content?
Yes. Many publishers implement blocking by default while selectively allowing access to licensed partners.
Does blocking AI scrapers affect my Google search rankings?
Blocking AI crawlers like GPTBot, ClaudeBot, or Bytespider does not affect your Google Search rankings. These bots are separate from Googlebot, which indexes content for search results.
How effective is robots.txt at blocking AI scrapers?
Robots.txt is effective against reputable AI companies like OpenAI, Google, and Anthropic that respect the protocol. However, it relies on voluntary compliance. More aggressive bots like Bytespider (ByteDance) may ignore robots.txt entirely. You need to take a layered approach and implement defensive measures to protect your content from such bots.
How to block ChatGPT?
To block OpenAI’s GPTBot, which feeds ChatGPT, from crawling your site, add this code line to your robots.txt:
User-agent: GPTBot
Disallow: /