AI Training vs. AI Search Crawlers: Does Blocking AI Training Crawlers Hurt Your AI Referral Traffic?

The AI Crawler Dilemma: Can Publishers Block Training Without Sacrificing Traffic?

Publishers are caught in an uncomfortable position. AI companies are crawling websites to train their models, effectively using publisher content as free training data. Meanwhile, AI-powered search tools are becoming significant traffic drivers that publishers can't afford to ignore.

The question keeping publishers up at night is simple: Can you block AI training crawlers to protect your content while still allowing AI search crawlers to maximize referral traffic? Or does blocking training crawlers make AI systems less likely to recommend your site?

The answer is messier than anyone would like. For publishers looking for a comprehensive overview of their options, our complete guide to AI crawlers covers whether to block, allow, or optimize for maximum revenue.

Need a Primer? Read this first:

• The Shift to AI Search: Understand how AI-powered search is changing the discovery landscape for publishers
• Understanding Keyword Rankings: Foundation for SEO strategy that complements AI search optimization

Understanding the Two Types of AI Crawlers

Before diving into strategy, it helps to understand what we're actually dealing with. AI companies deploy crawlers for two distinct purposes, though the line between them isn't always clear.

• Training crawlers scrape content to feed into large language model development. Your articles, guides, and resources become part of the AI's knowledge base. You don't get paid for this. You often don't even get credited.
• Search or retrieval crawlers access your content in real time to power AI search features. When someone asks an AI assistant a question, these crawlers fetch relevant pages to inform the response. This is where your traffic opportunity lives.

The following table breaks down the major AI crawlers and their purposes:

The "separation level" column is where things get interesting. OpenAI offers the cleanest distinction. Google's approach is murkier. Perplexity uses the same crawler for everything.

The Strategic Problem Nobody Wants to Talk About

Here's the uncomfortable truth that AI companies aren't rushing to clarify: being part of the training data might make AI systems more likely to cite you.

Think about it from the AI's perspective. If a model "knows" your brand, recognizes your content style, and has internalized your expertise through training, you're a familiar source. When that same model retrieves real-time search results, it may favor sources it already trusts.

This isn't confirmed with hard data. AI companies aren't exactly transparent about how their recommendation algorithms weight trained knowledge versus real-time retrieval. But the logic holds up.

Blocking training crawlers while allowing search crawlers might work perfectly for pure retrieval-based AI search. The AI fetches your page, reads it, and cites it. Simple.

But for systems that blend trained knowledge with real-time search, you could be making yourself less "memorable" to the AI. You're an unknown quantity competing against sources the model already knows intimately. Publishers who want to take the opposite approach might consider strategies to get AI tools to actively cite your website instead of blocking them.

Google's Approach: Clear as Mud

Google offers Google-Extended as an opt-out mechanism for Gemini AI training. The company states that blocking this crawler prevents your content from training Gemini models while maintaining your presence in traditional search and AI Overviews.

Sounds great on paper. The reality is more complicated.

Google hasn't fully disclosed how AI Overviews source their information. These summaries likely draw from a combination of trained knowledge and real-time retrieval. If your content was already ingested before you blocked the crawler, that knowledge persists in the model.

Additionally, Google's documentation on this topic has evolved multiple times. What they say today might not reflect how the system actually works tomorrow. This uncertainty is just one reason why future-proofing your content strategy for the AI era requires flexibility rather than rigid rules.

The practical implications for publishers:

• Blocking Google-Extended should not affect traditional search rankings or visibility
• AI Overview citations may or may not be affected depending on how Google weights trained versus retrieved content
• Historical content that was already crawled remains in trained models regardless of current blocking settings

Related Content:

• Complete Guide to AI Crawlers: Comprehensive overview of whether to block, allow, or optimize for AI crawlers
• How to Get AI Tools to Cite Your Website: Strategies to maximize AI referral traffic instead of blocking
• Using Cloudflare to Block AI Crawlers: Step-by-step setup and configuration instructions
• Future-Proofing Your Content Strategy: Build flexibility into your approach as the AI landscape evolves

OpenAI's Cleaner Separation

OpenAI provides the most straightforward crawler separation in the market. GPTBot handles training data collection. OAI-SearchBot powers SearchGPT and ChatGPT's web browsing features.

This means publishers can configure their robots.txt to block GPTBot while allowing OAI-SearchBot:

User-agent: GPTBot
Disallow: /

User-agent: OAI-SearchBot
Allow: /
 

This configuration theoretically lets your content appear in ChatGPT search results without contributing to model training. It's the closest thing to having your cake and eating it too.

The catch? SearchGPT is still relatively new, and we don't have long-term data on how blocking GPTBot affects citation rates. The systems may be technically separate, but they likely share some underlying infrastructure and preferences.

Perplexity and the Blended Problem

Perplexity represents the messier end of the spectrum. The company uses PerplexityBot for both training and search retrieval. There's no clean separation available.

Block PerplexityBot, and you opt out of everything. Allow it, and your content feeds both training and search.

For publishers concerned about content protection, this is an all-or-nothing choice. Given Perplexity's growing user base and its position as a primary AI search destination, blocking entirely means sacrificing a meaningful traffic source.

Not sure where your site currently stands? Our AI Crawler Protection Grader analyzes how well your website blocks AI crawlers from scraping your content.

Practical Crawler Configuration Strategies

Given the uncertainty, publishers have three main strategic options. Each involves different tradeoffs between content protection and traffic potential.

Option 1: Maximum Protection

Block all AI training crawlers while allowing only confirmed search-only crawlers.

User-agent: GPTBot
Disallow: /

User-agent: CCBot
Disallow: /

User-agent: Google-Extended
Disallow: /

User-agent: OAI-SearchBot
Allow: /

User-agent: Googlebot
Allow: /

This approach prioritizes content protection but may reduce your "familiarity" to AI systems over time. For detailed implementation instructions, our guide to using Cloudflare to block AI crawlers walks through setup and configuration step by step.

Option 2: Maximum Exposure

Allow all AI crawlers to maximize both training inclusion and search retrieval.

This approach bets that being deeply embedded in AI training data will lead to more citations and referrals. You sacrifice content protection entirely.

Option 3: Selective Middle Ground

Block only the crawlers with clear training-only purposes while allowing those with search components.

This balanced approach blocks CCBot and Google-Extended while allowing GPTBot (for potential familiarity benefits) and all search crawlers.

The following table summarizes each strategy:

What Publishers Should Actually Do

The honest answer is that nobody has perfect information here. The AI landscape changes weekly. Companies update their crawler policies without fanfare. What works today might not work in six months.

That said, here's a practical framework for making decisions:

• Start with your priorities. If content protection matters more than maximizing every possible traffic source, lean toward blocking training crawlers. If traffic growth is the primary goal, lean toward allowing more access.
• Monitor your referral traffic. Set up proper tracking to understand which AI sources actually send traffic. This data will inform future decisions about crawler access.
• Stay flexible. Implement crawler rules that are easy to update. Review them quarterly as the landscape evolves.
• Accept uncertainty. There's no guaranteed way to optimize for AI citations while fully protecting your content. The systems aren't designed to offer that choice.

Traditional search optimization still matters too. Understanding keyword rankings and strategies for improving your search engine positioning remains foundational, even as AI reshapes the discovery landscape.

The Traffic You Get Still Needs to Pay

Regardless of how you configure your AI crawler settings, the traffic that does arrive needs to generate revenue. This is where your monetization strategy matters far more than crawler configurations.

Publishers obsessing over AI crawler settings while running suboptimal ad layouts are solving the wrong problem. A 10% increase in AI referral traffic means nothing if your page RPM is half what it should be.

The fundamentals still apply. Strong viewability drives higher CPMs. Balanced ad density protects user experience and session depth. Quality demand sources outperform generic programmatic every time. For a deeper dive into what to track, our guide to managing and monitoring your website ad revenue metrics covers the essential KPIs.

Understanding how to take control of your ad revenue through automated monetization can help ensure you're extracting maximum value from every session, regardless of traffic source.

Next Steps:

• AI Crawler Protection Grader: Analyze how well your site currently blocks AI crawlers
• Managing Your Ad Revenue Metrics: Ensure traffic from any source is properly monetized

Playwire: Maximizing Revenue From Every Traffic Source

The AI search landscape will keep evolving. Traffic sources will shift. What won't change is the need to extract maximum value from every visitor who lands on your site.

Playwire's RAMP Platform is built to help publishers maximize revenue regardless of where traffic originates. Our machine learning algorithms optimize yield on every impression while our yield operations team monitors performance around the clock.

Whether your traffic comes from traditional search, AI-powered discovery, direct visits, or social referrals, we help you turn those sessions into sustainable revenue. Quality, performance, and transparency aren't just buzzwords. They're the foundation of how we operate.

Ready to ensure your traffic is working as hard as it should? Reach out to learn how Playwire can amplify your ad revenue.