Why Big Brands Are Winning in AI Search

I don’t know about you, but I’m freaking excited about AI search. 

I mean, I can finally talk to a machine using my vernacular, slang, and lazy Texan pronunciation, and still get answers to my questions.

And I can ask follow-up questions until I’m happy I have the information I want… no more clicking on links and doing the research myself.

We’re literally living a sci-fi dream.

But those clicks…that’s the smallest unit of internet currency. 

They’re the pennies that build the dollar.

And at this early stage in our understanding of AI output, we know big brands are winning… precisely because they’re big brands.

For those of us in SEO, we knew Google preferred big brands. 

But I never thought past solving that… I was so busy figuring out how I could help my clients compete in search against big brands that I failed to see how that big-brand advantage would translate into an advantage in the AI search era.

Now, LLMs trained on Google’s internet have learned that brands already mentioned regarding a topic (and that seem to be the experts on that topic) are still favored when answering user questions.

What I’m saying is that when you ask an LLM like ChatGPT or Gemini about the best running shoes, it remembers Nike; it doesn’t yet “discover” a new brand. It’s using the brand equity and influence that already exists.

So, right now, AI search isn’t yet the great equalizer. It’s more of a parrot, repeating the EEAT that a brand has already established across the web.

But that’s where I see the real opportunity.

Smaller brands can now grow equally by taking advantage of the same long-term trust signals that AI already recognizes.

And here's the kicker: AI search is still new. We're still learning how it works and where it's going.

That means jumping in now. Rethinking your site, content, and brand in AI terms will compound over time. 

The brands that move first won't just catch up. They'll define what "authority" looks like to the next generation of search.

I mentioned that small brands didn’t do SEO wrong and can potentially get cited or shown in AI-generated search results just as easily as a big brand, especially if they’re doing a great job of covering a topic. 

Well-covered topics build semantic authority. Semantic authority happens when AI, your audience, and your competitors all describe you the same way, because you've consistently shown up as the expert regarding a specific topic.

But that’s hard if they were unable to spend the time and budget to produce mountains of SEO optimized content in the Google algorithm era of search. 

So that’s really where the gap is…

Bigger brands aren’t always the better solution… they were just able to position themselves as semantic authorities through content production at scale, and Google favored that. 

For those of us in Content and SEO, we used the hub-and-spoke model to answer every question and angle of a topic we could think of, and then used a complex linking strategy to show the relationship between a page for a long-tail keyword or sub-topic and the main topic.

We also used labor (and cost) intensive strategies to get backlinks so we could (basically) prove to the Google algorithm that our site or page was the authority on a topic.

But LLMs don’t rely on backlinks because they understand lazy Southern accents, slang, pronunciations, and the way different people ask the same question. LLMs prioritize understanding intent over link graphs, which means authority can now be built through brand clarity and consistency, not just backlink volume.

So, I can ask an LLM a question my way and get the answer I expected, no matter how I ask it. That’s because LLMs will recognize semantic authority in natural language.

So, smaller brands now have an equal-sized digital footprint where they previously lacked one.

They can compete with a single cohesive strategy (content + brand alignment + multichannel distribution) instead of needing the scale and budget to publish mountains of content to achieve semantic authority.

That means intentionally appearing (repeatedly) in a structured and consistent way that reinforces who you are, what you do, and why you matter. 

You can do this by:

Because LLMs learn about you the same way people do: They become aware of you, look for you in multiple places, and start to instinctively recognize you, and then form an idea of who and what you are, and how you benefit them.

And THAT is why I start every new relationship with an AI-Search Readiness Audit.

Because rankings don’t matter anymore, your VISIBILITY is what brings recognition and direct traffic.

So, if you close that visibility gap now, you’re not just catching up, you’re building a signal AI can’t, and I argue, won’t ignore.

What sucks is that I haven’t found a reliable way to measure AI visibility. 

And not to sound crass, but I don’t believe anyone else has figured out measurement, either. Some of the big players say they have, and I’m looking at each, but so far, I’m unconvinced. 

Traditional metrics don't apply here, but that's exactly why early movers have an advantage. While everyone's chasing outdated KPIs, you can build the signal that AI will learn to prioritize.

Sure, we can track Share of Voice (SOV) across LLMs like ChatGPT, Gemini, or Perplexity, but those numbers only tell part of the story. Each AI model has different training data, update schedules, and sources of truth. So, you might “win” visibility in one model while being invisible in another.

I will say this, though: I feel SOV is a reliable indicator of who’s winning right now, as we talk about dethroning brands that capitalize on their legacy semantic authority.

But I have to acknowledge these are just my feelings. 

SOV’s reliability is supported by its growing use as a common measurement…right now.

But it’s not the silver bullet for repeatable, measurable visibility that turns into ROI.

And that’s why I’m excited to be here at the beginning of AI search. I missed the boat on SEO, and was lucky to learn, work with, and collaborate with some of the best.

So, the one metric we know works is brand clarity and recognition.

That means the LLMs, your audience, and competitors think of or describe you the same way you describe yourself.

To achieve this, you’ll need to prove you know the topics important to you inside and out, and that your messaging about yourself and those topics is cohesive across channels.

That’s how you’ll reinforce who you are and what you’re known for.

And that’s how I know you’ll grow your visibility in this new AI era.

So, yes, Sirs and Ma’ams, we’re tracking share of voice to determine semantic authority…for now. 

But the real work is digging into your site health, your content, and your brand to improve what visibility means to you.

Because clicks aren’t happening, and you don’t want to just show up in AI-generated answers, you want to be remembered and top of mind when someone has a question, needs help, or needs a solution.

Boiling all of this down, what I’m saying is this: AI search arrived years ago.

Most SEOs know this, too, even the ones like me, who were too in the weeds to pick their heads up and put two and two together.

So start letting go of thinking about ROI in terms of ranking, backlinks, and keywords, and measuring clicks.

Those days are gone. Now, it’s all about how much people (and LLMs) trust you and how well you do at staying top of mind.

And when AI models, customers, and competitors can all describe your brand the same way, you’ve achieved something that no update can erase: semantic authority.

THAT’s what big brands have, and it’s what smaller brands can build if they start now.

Remember this truth that a few others have finally called out: All AI is doing (right now) is rewarding those who were prepared to play on multiple fronts.

So if you’re a CMO or founder staring down declining organic traffic, don’t panic. You’re not late. You’re early enough to lead.

Start with your foundation: 

Then, extend that same clarity to every place your audience (and AI) might look for you.

If you do that, you won’t just survive the AI shift, you’ll help define it.

Start by auditing what AI already knows about you. Then fill the gaps.