Signal Harbor Weekly: June 18, 2026

Signal Harbor

Welcome back to Signal Harbor Weekly.

Most conversations about AI visibility start with a company's website.

How should we structure our content?

What schema should we add?

Which keywords should we target?

How should we optimize for AI search?

Those questions matter.

But a recent study suggests they may not be the most important questions.

THE FINDING

Researchers compared how traditional search engines and major AI platforms retrieve information across a wide range of queries.

What they found challenges one of the biggest assumptions in digital marketing.

In traditional search, your website is often one of the primary assets competing for visibility.

In AI search, the picture looks very different.

For many commercial and B2B queries, systems such as ChatGPT and Claude rely heavily on third-party sources when constructing answers.

Industry publications.

Review sites.

News coverage.

Expert commentary.

Independent comparisons.

In other words:

AI systems often care more about what others say about your company than what your company says about itself.

THE SHIFT

Traditional SEO taught businesses to focus on their own domain.

AI search appears to be shifting attention toward the broader information ecosystem surrounding a company.

A buyer evaluating software may never encounter your homepage first.

Instead, the AI may rely on:

• An industry review site

• A third-party comparison article

• A trade publication

• An analyst report

• A community discussion

Those sources help shape the AI's understanding of your category and the companies within it.

That means a technically perfect website is not always enough.

If the sources an AI trusts do not mention your company or do not understand your company correctly, you may struggle to appear in the final answer regardless of how much effort you invest into your own website.

THE EXECUTIVE QUESTION

This creates a different strategic question.

Instead of asking:

"How do we optimize our website for AI?"

Leaders may need to ask:

"Which sources does AI trust when discussing our category?"

Because those are not necessarily the same thing.

The challenge isn't simply visibility.

It's understanding the ecosystem of sources that influence AI recommendations.

THE SIGNAL

This finding has influenced how we think about AI visibility at Signal Harbor.

Many companies already know their website analytics.

Many know their search rankings.

Far fewer understand which third-party sources are shaping AI-generated answers about their category.

That's why we're increasingly focused on mapping what we call a company's citation ecosystem:

• Which sources AI trusts

• Which sources appear repeatedly

• Which sources influence recommendations

• Where competitors are gaining visibility

• Where important information gaps exist

Before a company can improve how AI systems interpret its business, it must first understand what information those systems are relying on.

THE TAKEAWAY

The AI era may not belong to the companies with the most optimized websites.

It may belong to the companies that understand and influence the broader information ecosystem around their business.

The winners won't just be the companies that publish the most content.

They'll be the companies that become the sources AI systems trust when decisions are being made.

And for many organizations, that shift has already started.

Sebastian Miller
Co-Founder, Signal Harbor
signalharborconsulting.com
sebastian.miller@signalharborconsulting.com
402-306-2213

Source

Chen, M., Wang, X., Chen, K., & Koudas, N. (2025). Generative Engine Optimization: How to Dominate AI Search. arXiv:2509.08919. University of Toronto.

Research Note

The ideas in this issue are informed by peer-reviewed research, public studies, and Signal Harbor's ongoing analysis across major AI platforms. As this field develops, Signal Harbor will continue evaluating new research and refining how AI recommendation performance should be measured.

Signal Harbor Weekly helps business leaders understand how AI systems represent, recommend, and influence buying decisions.