How to Make AI Engines Like Your Brand

For twenty years, "getting found" meant getting found by Google. Keywords, backlinks, page speed . . . the whole familiar SEO toolkit. That toolkit still matters. But a growing share of the moments where someone decides what to buy, who to hire, or which brand to trust now happen inside a conversation with an AI model. That conversation runs on a completely different set of rules.

We call this discipline answer engine optimization (AEO), or generative engine optimization (GEO), depending on who's naming it that week. What it actually means is simple to state and harder to do: making your brand legible enough, consistent enough, and credible enough that when someone asks AI about your category, the model can confidently say your name.

The same instincts that rebuild brands, rebuild visibility

There's a useful parallel in how some of the biggest recent brand turnarounds actually happened. When Elliott Hill returned to Nike after the company's shares had fallen nearly 60% from their 2021 peak, he didn't commission a rebrand. He reorganized the company around sport categories and reinvested in what Adweek's Craig Elimeliah called "relentless brand storytelling". It re-centred Nike on the founding purpose that made it matter in the first place, most prominently through the "Why Do It?" campaign.

The instinct behind that turnaround — a clear, consistent, unmistakable version of what the brand actually stands for — is almost exactly the instinct that makes a brand legible to an AI model. Models don't reward cleverness or ambiguity. They reward brands that say the same true thing about themselves, clearly, and in enough places, that the pattern becomes unmistakable. The brands that have already done the hard work of building a coherent identity have a head start most of them don't know they have.

What AI models are actually reading

An AI model forming an opinion about your brand isn't reading your internal brand guidelines document. It's synthesizing an answer from whatever is publicly and consistently said about you across your own site, your press coverage, your customer reviews, your competitors' comparisons of you, and a long tail of pages most people wouldn't even consider as marketing.

That has a few key implications. Vague, aspirational language that sounds good on a homepage but says nothing specific gives a model nothing to repeat with confidence. Inconsistency between how you describe your brand in different places (your site, your reviews, your press releases) reads to an AI model as uncertainty. Silence is the worst position of all: a model has no reason to mention a brand it has nothing recent or specific to say about.

A five-minute audit worth running

Here's a simple test, and we'd genuinely encourage you to try it: open an AI assistant and ask it three things. What does this brand do? Who are its real competitors? Why should someone choose it over them? Read the answers carefully. Most brands find at least one of three things: the model gets something confidently wrong, the model has nothing to say at all, or the model's answer sounds nothing like how the brand actually wants to be understood.

None of those outcomes are permanent, and none require a rebuild. They tell you where the gap sits between how your brand sounds to a human and how it sounds to the systems increasingly standing between you and your customers.

Why this is a strategy problem, not a technical one

It's tempting to treat AEO as a technical add-on, but the brands getting real traction are treating it as what it actually is: a way to understand and influence how your customers perceive your brand. That's why we treat this as an extension of brand strategy, not a separate discipline bolted onto it. You need to establish what is unique and true about your brand, say it consistently, and say it in enough places that repetition becomes reputation. The only thing that's changed is who, or what, is doing the listening.

Sources

• Brands Beloved by People Risk Being Invisible to AI, Craig Elimeliah, Adweek, 2 April 2026