What Does AI Recommend When Someone Asks About Your Category?

Here’s an exercise worth doing — but you need to do it correctly or the results will mislead you. Open ChatGPT, Perplexity, or Gemini and type a category-level prompt the way a buyer who has never heard of you would: “What are the best platforms for [your category]?” or “Which companies are considered leaders in [your space]?”

The catch: if you’ve ever discussed your company in that chat session, or if the AI has been exposed to your brand through your prior interactions, you may get a skewed result. To get a genuinely neutral read, you need to either open a fresh incognito browser window with no login, use a colleague’s account they’ve never used to discuss your company, or — better yet — ask someone outside your organization entirely to run the same prompts and report back what they see. What you’re testing isn’t whether AI knows who you are. You already know it does. You’re testing whether a buyer who has never encountered your brand would have it surfaced to them — and how it’s characterized relative to competitors. That’s a very different question, and it requires a genuinely cold session to answer honestly.

How AI Decides What to Recommend

AI systems don’t pull vendor recommendations from a curated database. They synthesize them from the vast landscape of digital content they were trained on — and increasingly from real-time retrieval of current web content. That means your visibility in AI recommendations is a direct reflection of your visibility in the sources AI trusts most: authoritative press coverage, reputable review sites, analyst mentions, industry publications, and the volume and quality of content that discusses your brand substantively.

This is the core insight behind why search presence is one of the five pillars of the TRUST framework: the signals that drive Google rankings — authoritative backlinks, domain authority, EEAT signals — are the same signals that feed AI recommendation systems. Building genuine search authority and building AI visibility are largely the same investment.

AI isn’t looking at your homepage or your marketing materials. It’s looking at what independent, authoritative sources say about you. It’s aggregating the external validation signals that collectively form a picture of your brand’s credibility — and synthesizing that picture into a recommendation or a characterization.

The LLM Visibility Gap

There’s a meaningful gap right now between companies that show up reliably in AI recommendations and those that don’t — and it’s not always correlated with which product is actually better or which company has been around longer. It’s correlated with which brand has the richer, more authoritative digital footprint.

Brands that have invested consistently in earned media, original research, industry recognition, and genuine thought leadership tend to appear in AI answers. Brands that have relied primarily on paid channels, generic SEO content, and self-published marketing materials often don’t. The reason is simple: the eternal power of trust signals lies precisely in their independence. AI recognizes and weights independent validation over self-promotion, because that’s what credible sources do.

Why the Answers Look the Way They Do

When you run those AI prompts and read the results, you’re reading a snapshot of the external validation landscape in your category as AI currently understands it. The companies that appear most prominently and most favorably tend to share a few characteristics: depth of media coverage in authoritative publications, active and well-reviewed profiles on the review platforms that matter in their space, analyst recognition, and visible thought leadership presence. If your brand doesn’t appear, or appears less prominently than competitors you know you outperform, that gap is entirely explainable by differences in external validation investment — not product quality.

The companies that are absent or poorly characterized typically have the opposite profile: minimal earned media, thin review site presence, no analyst recognition. Understanding what makes people trust online reviews and leveraging that knowledge to build a systematic review presence is one of the most direct investments in AI recommendation visibility available.

What Closing the Gap Looks Like

You can’t directly optimize for AI recommendations the way you’d optimize for a Google ranking. What you can do is build the kind of authoritative, third-party-validated digital presence that AI systems are designed to recognize and trust. That means earning coverage in publications your buyers read. It means having a meaningful presence on review platforms that matter in your category, including the platforms like Capterra and others specific to your market. It means publishing original research and insights that get cited, linked to, and discussed by others.

The specific tactics for building each of these signal types are what we’ll cover over the next six weeks. But the starting point — the foundation for everything that follows — is doing the audit we described at the beginning of this post. Understanding exactly where your brand stands in AI recommendations today is the prerequisite for building a strategy to improve it.