The Hidden Influence of AI: Inside the Rise of Indirect LLM Traffic

Knotch Labs’ latest pilot data reveals how AI tools are quietly reshaping brand discovery – long before analytics can detect it.

What Marketers Are Missing about AI Traffic 

Over the past year, most discussions about AI’s impact on web traffic have focused on direct referrals – the small but growing number of visits from large language model (LLM) platforms like ChatGPT, Google’s AI Overviews, Gemini, and Perplexity.

Across Knotch clients, that direct AI referral traffic remains tiny – roughly 0.13% of total visits. But new data from Knotch Labs suggests this view is missing something much bigger: indirect LLM traffic. This is the traffic that results from consumers using LLMs as part of their discovery journey even if they didn’t click on a link provided to them by ChatGPT or Perplexity in order to get to a brand’s website.

In early surveys conducted across several Knotch client sites, representing more than 20,000 responses, visitors were asked a simple question:

“Before visiting this page, did you use any AI tools – such as Google AI Overviews, ChatGPT, or Gemini – to learn more about this topic or brand?”

The results reframed the conversation entirely.

35% of respondents said yes.

AI’s Trojan Horse Traffic

That 35% figure means that while only a handful of visits can be directly tied to LLM referrals, thousands more customers may have been influenced by them. Based on the total sample of 20,000 responses, that translates to roughly 7,100 people who interacted with AI tools before their visit.

In other words: traditional analytics are tracking the visible tip of an iceberg. The real behavioral change is happening below the surface, even if some of that signal reflects overreporting or confusion about what counts as “AI use.”

We’re calling this phenomenon Trojan Horse traffic. It’s a hidden stage in the customer journey where generative AI environments shape consumer curiosity, confidence, and intent, often in combination with other marketing touchpoints, before a click ever reaches your website.

Early behavioral data from directly attributed AI visits – which convert at above-average rates – hint that this wider, AI-influenced audience may be engaging in similar ways.

Curiosity Is the New Conversion Trigger

Among visitors who said they had used AI tools before arriving, 57% reported that those interactions encouraged them to learn more about the brand.

That’s a critical insight for marketers fighting through the “missing middle” – the long, uncertain period between awareness and decision-making. It suggests that AI is priming higher-intent visits, rather than simply routing traffic.

It’s warming up these audiences – nudging them toward engagement long before a retargeting ad or organic search click ever appears in analytics.

Why This Matters

Marketers have long known that attribution lags behind behavior. The same was true in the early days of mobile, then social, then influencer marketing. AI discovery is now repeating that cycle – and it’s a leading indicator of how consumer intent will form in the next wave of digital discovery.

These early signals suggest that LLMs aren’t just new referral channels – they’re becoming decision accelerators. Understanding their indirect impact may soon be as essential as SEO itself was a decade ago.

A Pilot Study, and a Directional Signal

It’s important to note: these findings come from a pilot dataset – a group of Knotch clients, all of which volunteered to test a new survey instrument designed to quantify AI influence on discovery behavior.

But even as a directional signal, the results are compelling. Across every participating brand, indirect AI influence was hundreds of times greater than what analytics could detect through referral logs.

Knotch Labs is now expanding the study to include additional brands across industries and funnel types to validate these patterns.

Metrics to Watch

As Trojan horse traffic becomes more measurable, marketers should prepare to track:

• AI Exposure Rate: % of visitors self-reporting AI use before arrival.
  
  
• AI Motivation Lift: % who say AI interactions increased curiosity or purchase intent.
  
  
• AI Path Efficiency: Session duration, steps-to-conversion, and CTA engagement among AI-exposed visitors vs. others.
  
  
• Channel Rebalancing: The share of direct, social, and search traffic that originates from Trojan horse traffic.
  
  

These metrics will define how LLM discovery gets integrated into marketing analytics over the next 12–18 months.

The Bottom Line

The story of AI discovery isn’t about volume yet – it’s about influence.

Direct LLM traffic may still be small, but the indirect effects are already measurable and material. AI is quietly shaping how consumers decide what to learn, what to trust, and ultimately, what to buy.

Marketers who start tracking this hidden layer now won’t just be reacting to the next algorithmic shift – they’ll be ahead of it.

Curious what happens after that moment of intent? We dig into how AI is twisting the paths to conversion in this piece: The customer journey was already warped – AI just made it weirder. 

Published November 5th, 2025