Why “AI search” is the wrong frame and leading many astray
A lot is riding on two words right now for marketers: AI search. The industry is clinging to an old paradigm and it’s leading many down a mistaken path.
When large language models began answering questions, recommending products, and shaping decisions, the industry reached for the most familiar frame it had — AI search. This is an understandable choice, and a useful starting point. But the term quietly carries two decades of assumptions that no longer hold with big implications for marketers.
The Fallacy
People don’t search in AI. They discover, evaluate and decide — and so does AI.
When someone begins a conversation with ChatGPT, Gemini, or Claude and asks “what’s the best CRM for a 50-person sales team?” or “which of these two vendors should I trust?”, they are not scanning blue links to judge for themselves. They are turning to a new intermediary — one that recommends, weighs the pros and cons, and decides with the reasoning already baked in.
This is not a fringe behavior. It is playing out across every vertical. In B2B, it's already the default. Forrester reports that approximately 90% of B2B buyers now use generative AI somewhere in the purchase journey, OpenAI reports that three in five U.S. adults have turned to AI for health questions in the past three months. And EAB found that 46% of high-school students now use AI in their college search.
So what are the implications of mis-framing AI search vs. AI discovery and decision-making? Many may think they’re subtle, but they are monumental for marketers.
How One Wrong Turn Shapes an Entire Industry
The AI search fallacy isn’t just a vocabulary problem, it quietly sets the focus and direction for an entire industry: what we measure, what we think we can do about it, and even the technology infrastructure that gets built. Because the industry is still calling it search, it measures search-shaped things and builds search-shaped tools — and a generation of new products are still optimizing diligently for search-based behaviors vs AI-driven ones.
Look at what most tools in this space measure: citations and brand mentions. Did you get mentioned? Did your content get cited? These are the currency of a click and traffic era, when the goal was getting a human to notice your link, click it, and drive engagement to your site. They are easy to count but they tell you almost nothing about whether the model will recommend, choose you, or say about you.
That same origin has spawned a new set of acronyms and disciplines — SEO giving way to AEO and GEO. The instinct is right and adds value, but it carries some serious baggage. Think ranking higher, getting cited more, and literally optimizing generative AI.
And for that matter, can you really optimize generative AI? There is useful and valuable work here: making your content AI-accessible, structuring your website well, keeping your brand narrative accurate and consistent across the web, creating FAQs, and the list goes on. But useful as that is, it misses the bigger point: AI isn’t a search engine to be optimized — it’s a new influencer and intermediary that needs to be treated very differently than a search engine.
AI as the Next Big Influencer and Intermediary
AI is now the next big influencer and sits as a new intermediary between your brand and your customer. It doesn’t just pass your message along — it evaluates you, forms a judgment, and delivers a recommendation in conversations with your customers. In effect, every brand now has a set of AI “spokespeople” describing it to customers around the clock, in every market and language. You never hired them, and you can’t fire them.
But brands have always worked through influencers and intermediaries such as the analyst, the broker, the retail buyer, the procurement officer. You never “optimized” a procurement officer; you marketed to them, making sure they understood your strengths and carried an accurate story forward to the person who buys.
The LLM is simply the newest and most powerful influencer and intermediary in that line, and the same logic applies. You don’t optimize influencers and intermediaries, you market to them and through them. Call it what it is: Brand Marketing for AI. That’s the shift — and it requires so much more than GEO.
Measuring What Actually Matters
If you’re going to market to these influencers and intermediaries, the first job is to understand how they currently see you — and that means the metrics have to change. Three questions matter:
The Bottom Line
“AI search” captures part of what’s happening, but not the heart of it. AI search continues to direct us towards tracking mentions and counting citations, when the real shift is that people don’t search in AI; they do discovery and decision-making with AI itself doing the same.
This is where Revere takes a different view. We don’t think the work is optimizing for AI search. It’s marketing to a new influencer and intermediary for AI discovery and decision-making. We measure what actually matters and activate marketing to shape it.
Revere is an AI Brand Intelligence company that helps brands understand and shape how they are represented across the generative AI ecosystem.