Brand Strategy · Search · AI Visibility
We spent two decades mastering the art of being found. Then the rules changed — quietly, completely, and without a press release.
I remember the exact moment I realized the ground had shifted under our feet. I was sitting across from a CMO — a sharp one, someone who had built and scaled two consumer brands from scratch — and she said something that stopped me cold: “We rank number one on Google for our main keyword. Traffic is up. But leads are down thirty percent. I don’t understand what’s happening.”
I understood completely. And I also knew that explaining it to her would require me to dismantle almost everything she believed about how search worked.
That was eighteen months ago. Since then, I’ve had some version of that conversation in nearly every client engagement I’ve taken on. The terminology has evolved — from SEO to AEO to GEO, acronyms multiplying faster than anyone can trademark them — but the underlying disruption is the same. Search, as we knew it, is over. And brand visibility has moved to an entirely different battlefield.
The world we built everything on
For the better part of two decades, SEO was the closest thing marketing had to a reliable science. You identified the keywords your customers were searching. You built content around those keywords. You earned backlinks, structured your pages, loaded your metadata, and — if you did it well — you climbed the rankings and traffic followed. It was systematic. Measurable. Gameable, even, though Google kept changing the rules to stop the gaming.
And as a brand strategist, I spent years translating SEO logic into brand logic. What does it mean for your brand when 70% of your discovery happens through a keyword? What does it do to your identity when you’re optimizing every piece of content for a search algorithm rather than for a human being? These were the tensions I worked with every day, trying to make sure the brands I advised didn’t become hollow keyword machines — technically visible but emotionally empty.
Then something started changing around 2022, and it accelerated so fast that most of the industry is still catching its breath.
The first tremor: AEO and the rise of the answer
Answer Engine Optimization didn’t arrive with a fanfare. It crept in through featured snippets — those little boxes at the top of Google results that answered your question so completely you never needed to click anything. Then it grew through knowledge panels, voice search results, and Google’s increasingly conversational interface.
The insight behind AEO was deceptively simple: search engines were no longer just indexing pages. They were beginning to answer questions directly. And if your content wasn’t structured as an answer, it might rank just fine while being completely bypassed by the very mechanism that was increasingly deciding what users actually saw.
I watched brands struggle with this transition in real time. They’d invested heavily in long-form SEO content — beautifully written, deeply researched, carefully optimized — and watched helplessly as Google began surfacing a three-sentence extract from a competitor’s FAQ page instead. The question wasn’t who wrote better content. The question was who had structured their content so an algorithm could grab it, trust it, and present it as the answer.
For brand strategy, this created a peculiar challenge. Brands are built on nuance, on story, on differentiation that rarely fits in a featured snippet. But the medium was demanding compression. The medium was demanding certainty. And in that gap between brand depth and algorithmic simplicity, a lot of brand identity started getting lost.
“Ranking number one stopped meaning what it used to mean. The real question became whether you were the answer — and whether that answer sounded like you, or like everyone else trying to win the same snippet.”
Then came the earthquake: GEO and the generative shift
If AEO was a tremor, Generative Engine Optimization is the earthquake. And like most earthquakes, you don’t fully grasp its scale until you’re standing in the aftermath.
What happened, simply put, is this: the search box is no longer just a search box. When someone types a question into ChatGPT, Perplexity, Google’s AI Mode, or a dozen other platforms that have launched in the past two years, they aren’t getting a list of links. They’re getting a synthesized answer — drawn from multiple sources, assembled in real time, delivered in fluent prose. The platform doesn’t send them to your website. It absorbs your content, digests it, and speaks on your behalf.
Let that sink in for a moment. An AI is now frequently the intermediary between your brand and your potential customer. It decides what to say about you. It decides whether to mention you at all. And it does this millions of times a day, across queries your marketing team will never see and can’t directly control.
The numbers are staggering in a way that still makes my head swim. ChatGPT alone now handles over 2 billion queries every day, and studies suggest roughly 65% of those qualify as search behavior — people looking for information, recommendations, comparisons, answers. Google’s AI Overviews now appear in over half of all Google searches. Meanwhile, Gartner projected a 25% drop in traditional search engine volume by 2026 specifically because of AI chatbots and virtual agents pulling users away from the classic results page.
And here’s the data point that should make every CMO rethink their reporting dashboards: Ahrefs found that when an AI Overview appears on a Google results page, the click-through rate for the top-ranked organic result drops by 58%. Not 5%. Not 15%. Fifty-eight percent. You can be sitting at position one, having done everything right by every SEO standard ever written, and still lose the majority of the clicks you used to earn.
The brand problem nobody is talking about loudly enough
Here’s where I have to put on both hats — the journalist’s and the brand strategist’s — and tell you what’s actually at stake, because the conversation in most marketing circles is still too focused on tactics and not focused enough on identity.
When an AI synthesizes an answer about your brand, it’s not reading your brand guidelines. It’s not honoring the voice you spent years developing. It’s drawing from whatever sources it has indexed and trusted, and it’s presenting a version of your brand story that you did not write and cannot fully preview before it reaches your customer. That’s not a hypothetical. That’s happening right now, at scale, across every industry.
I’ve audited how several major AI platforms describe clients of mine, and the results are consistently humbling. Sometimes the descriptions are accurate. Sometimes they’re outdated. Occasionally they’re just wrong — conflating a brand with a competitor, citing a press release from five years ago that no longer reflects the current positioning, or reducing a carefully nuanced value proposition to a single blunt sentence. And there’s no appeals process. There’s no “flag this answer as inaccurate” button that feeds directly back into the model’s behavior.
This is the crisis that GEO is trying to address — imperfectly, urgently, with tools and methodologies that are still being invented as we speak. The practice, broadly, is about structuring your content and managing your digital presence so that AI systems cite you accurately, mention you frequently, and position you favorably when relevant questions are asked. It’s less about keywords and more about what Gartner’s analyst Alan Antin described as making sure these “generative AI solutions” — now functioning as “substitute answer engines” — are getting your story right.
What the acronym war is really about
I want to briefly address the terminology chaos, because if you’ve spent any time in marketing circles recently, you’ve probably seen people fighting passionately over whether to call this AEO, GEO, LLMO, AIO, or something else entirely. Andreessen Horowitz threw their weight behind GEO in a May 2025 thesis. Others argue AEO is clearer, more ownable, and less confused with geography and geology. As of early 2026, Wikipedia notes that no consensus definition distinguishing these terms had been established even in academic literature, and practitioners use them interchangeably.
My honest take: the acronym doesn’t matter nearly as much as the underlying understanding. What matters is grasping that we have moved from a world where visibility meant ranking to a world where visibility means being cited, trusted, and accurately represented inside AI-generated answers. Call it whatever you want. Just don’t let the terminology debate be a reason to postpone the strategic reckoning.
What has actually changed for brands — and what hasn’t
Here’s something I tell clients that tends to both reassure and unsettle them at the same time: the fundamentals of brand building have not changed. What has changed is the surface area on which those fundamentals now need to operate.
Credibility still matters. In fact, it matters more than ever, because AI systems draw heavily on what the industry calls E-E-A-T signals — Expertise, Experience, Authoritativeness, and Trustworthiness. Brands that have built genuine authority over time, that have earned coverage from reputable sources, that have produced original research and clear perspectives — those brands are better positioned in the AI era than brands that gamed SEO with thin content and paid link schemes. The chickens are coming home to roost for brands that built their visibility on shortcuts.
Consistency matters more than ever too. One of the most important factors in how AI systems represent a brand is what researchers call entity consistency — whether your name, your positioning, your core claims, and your narrative are coherent and identical across every platform where you have a presence. LinkedIn. Your website. Press coverage. Industry databases. Partner pages. Podcast transcripts. Every single one of these is a potential source that an AI will draw from when constructing its understanding of who you are. If those sources say different things — if your LinkedIn bio says one thing, your website another, and your CEO’s interview from two years ago something else entirely — the AI will produce an inconsistent or confused picture of your brand, and you will have no way to fix it in real time.
What has changed is the traffic model. For the first time in the history of digital marketing, you can have enormous influence on a customer’s decision-making process while receiving zero clicks to your website. Major publishers like Reuters and The Guardian are being frequently cited by AI platforms while receiving less than 1% of their referral traffic from those same platforms, according to Similarweb’s 2026 GenAI Brand Visibility Index. Being cited and being visited are now two completely different things. And most analytics dashboards were not built to measure the former.
“Your brand can now shape a customer’s decision without ever touching their browser. That sounds like power. It is also a form of invisibility — and learning to navigate it is the defining challenge of modern brand strategy.”
What I’m doing differently
I’ve restructured how I approach brand strategy engagements significantly in the past year. Not because the old disciplines don’t matter — SEO still matters, content still matters, media relations still matter — but because the sequence and the framing have to change.
The first thing I now do with any new client is what I call an AI visibility audit. Before we touch messaging or content strategy, I run their brand name and their core category queries through every major AI platform — ChatGPT, Perplexity, Google AI Mode, Gemini — and I document what comes back. Who is the AI saying my client is? What claims is it making? What sources is it drawing from? What competitors is it mentioning in the same breath? This audit is often more revealing than any focus group, because it shows you how the most widely consulted information system in human history currently understands your brand. The results are frequently surprising. Sometimes appalling. Always instructive.
The second thing I’ve changed is how I think about content. The old SEO model was essentially about volume and keyword coverage. The new model is about what I’d describe as answer authority — producing content that is so clear, so well-structured, so factually grounded and credibly sourced that an AI system, when faced with a relevant question, reaches for your content as its reference point. That means fewer pieces with more substance. It means writing with the same discipline a journalist brings to a story — active voice, concrete evidence, clear sourcing, no weasel words. It means understanding that clarity is now a competitive advantage in a way it never quite was in the era of keyword stuffing.
And the third change is perhaps the most uncomfortable one for some of my clients: I’ve started pushing hard for what I call narrative governance — the practice of auditing and actively managing the story about your brand that lives outside your owned channels. This used to be primarily the domain of PR and reputation management. Now it’s a core brand strategy function, because the AI systems drawing from the open web don’t distinguish between your press releases and a Reddit thread from 2021 that happens to rank well. Everything is a source. Everything contributes to the entity portrait that AI systems construct. You cannot afford to be passive about it.
The honest uncertainty
I want to close with something that the best analysts and strategists I know are all quietly saying to each other, even if it doesn’t always make it into the published think pieces: we don’t fully know how this plays out yet.
GEO as a formal discipline essentially didn’t exist before 2024. The tools being built to measure AI visibility are still young. The citation patterns across major AI platforms change 40% to 60% month-over-month — meaning whatever source an AI cites today may not be the same one it cites next quarter, for reasons that aren’t always transparent. Anyone who tells you they have definitively cracked the code on AI visibility is, as EMARKETER’s principal analyst Nate Elliott put it, “either wildly overconfident or trying very hard to sell you something, or possibly both.”
What I do know — what I can say with confidence from watching this shift play out in real client contexts — is that the brands that will navigate this transition best are the ones that don’t treat it as a technical problem. The ones that understand it as a brand problem. A trust problem. A story problem. The same things that made brands resilient before the algorithm era — genuine authority, a coherent identity, a consistent voice, a clear point of view on the world — are the same things that will make them visible in the AI era.
The technology is new. The underlying question is ancient: when someone asks who you are, does the answer sound like you?
That’s the work. It has always been the work. It just happens now that the one being asked is a machine — and the stakes of getting it wrong have never been higher.
From SEO to AEO and GEO — Nestor Andre