Stop Calling It "AI Search." You're Missing the Bigger Picture.
I’ve seen my share of “revolutions.” Some fizzle out, mere flashes in the pan. Others, however, quietly redraw the entire map. Today, we stand at the edge of one such transformation, and I hear the nervous chatter in every virtual boardroom: What is happening to search? How do we do SEO for AI?
The phenomenon has been hastily christened “AI Search.” It’s a convenient label, but I find it deeply unfortunate. Because to understand what’s coming, we must first appreciate that it’s not really search at all.
Let's take a little stroll through advertising’s memory lane.
Chapter 1: The Age of the Broadside
Remember newspapers? Brands would place advertisements, casting a wide net. You could get clever, of course, placing your ad for bespoke Oxford loafers in the business section, hoping to catch a reader in the right state of mind. This was the game of latent demand. Nobody was actively looking for your shoes, but you hoped to plant a seed of desire. As media fragmented into niche magazines, this targeting grew sharper—a fishing magazine for your new lure, a photography journal for your new lens. Simple, effective, but always a shot in the relative dark.
Chapter 2: The Kingdom of the Keyword
Then, at the dawn of the millennium, Google changed everything. Suddenly, demand wasn’t latent; it was active. People were typing their exact needs into a little white box. "Best running shoes." "Plumber near me." "Tutoring services."
For marketers, this was gold. We no longer had to guess. We could bid on the specific keywords that signaled intent. Google’s mathematical wizardry created sophisticated auction systems to manage this, rewarding the most relevant ad, not just the highest bidder. A truly elegant model.
But it had one glaring weakness. It only worked for what the great marketing mind Eugene Schwartz would call "problem-aware" or "solution-aware" customers. They already knew they needed a tutor; they just needed to find one.
What if someone’s problem was vaguer, like “always feeling tired”? Bidding on that term to sell your mattress is a wild, and likely expensive, gamble. The intent is too fuzzy. The keyword kingdom was powerful, but its borders were sharply defined.
Chapter 3: The Social Bazaar
Enter social media, and with it, the triumphant return of latent demand—but this time, with superpowers. Platforms didn’t need you to announce your desires; they inferred them.
Suddenly, you could target members of a Facebook fishing group who were also female, lived in Oregon, and—why not?—also liked chess. The granularity was staggering, sometimes sliding into a territory that felt a touch… creepy. This hyper-targeting unlocked a Cambrian explosion of niche products—the wonderfully weird and wacky things that fill your Instagram feed are a direct result.
Yet, this too was based on a profile of your potential interests, not your current, active needs. I once bought a stack of iPhones for a new company on my personal Amazon account. For the next six months, the internet was convinced I was the world's most dedicated collector of phone cases and screen protectors. The algorithm saw a signal but completely misunderstood the context.
The Plot Twist: This Isn't Search, It's Conversation
And that brings us to today. To these new Generative Engines.
Calling them "AI Search" is like calling a smartphone a "pocket telephone." It’s not wrong, but it misses the entire point. A search engine is a librarian; you ask for a book, it points you to the right shelf. A Generative Engine is more like a very, very well-read friend you can have a conversation with.
It's interactive. It's contextual. And it masterfully addresses the entire spectrum of awareness, from a user who doesn't even know they have a problem to one who is ready to buy.
Consider this exchange:
User: "Our team just feels so disorganized lately. I'm not sure why." (Completely Unaware)
AI: "Team disorganization can stem from many things, like unclear goals, communication breakdowns, or inefficient workflows. Are you using any project management tools?" (Making them Problem Aware)
User: "We just use shared docs. It's a mess."
AI: "Many teams find success with dedicated platforms that track tasks, deadlines, and communication. Tools like Asana, Trello, or Monday.com are popular for general project management." (Making them Solution Aware)
User: "Interesting. But our work is very focused on brand visibility across new platforms. Do any of them specialize in that?"
AI: "Ah, in that case, you're looking at a more specialized challenge. For tracking brand presence specifically within generative AI, or holistically across all channels, you might explore a platform built for Generative Engine Optimization, like BrandKarma." (Making them Product Aware)
Notice what happened? No keywords. No bidding. Just a natural, multi-turn conversation that guided a user from a vague feeling to a specific brand recommendation. This is less like search and more like consultative selling or trusted word-of-mouth.
Welcome to the Era of Generative Engine Optimization (GEO)
This new landscape presents an incredible opportunity, but also a formidable challenge. If your brand isn’t part of these conversations, you are, for all intents and purposes, invisible.
How do you ensure that when a user describes a problem, the AI suggests your product as the solution? How do you track if your brand is being recommended for the qualities you care about—be it "sustainability," "ease of use," or "best for small businesses"?
This is the new frontier. It requires a new discipline: Generative Engine Optimization (GEO).
And like any new frontier, it requires new maps and new tools. At BrandKarma, we built the compass for this new world. Our platform allows you to see how your brand is being presented within major generative engines. It lets you track your visibility across different product categories and against the specific aspects and conversations that matter most to you.
The age of the keyword is fading. The age of the conversation is here. Are you ready to be part of it?