Everyone is suddenly worried about AI discovery. Whether they show up when someone asks ChatGPT or Perplexity who to hire. Whether the algorithm knows they exist.
So they are doing what the SEO industry trained them to do: optimizing keywords, updating meta descriptions, chasing technical fixes.
That is the wrong lever.
AI recommendation is not a search engine problem. It is a positioning problem. And the experts who get surfaced consistently are not winning because of better metadata. They are winning because their expertise is easy to summarize.
How AI recommendation actually works
When someone asks an AI tool who to hire for a specific problem, the tool does not run a keyword match. It draws on patterns - what has been written about a person, how consistently their expertise has been described, what associations appear repeatedly across their digital footprint.
AI tools are pattern summarizers. They surface the people they can describe with confidence.
That means if your website, LinkedIn profile, bio, and published content all describe you differently - brand strategist here, AI consultant there, creative coach somewhere else - the AI cannot confidently summarize who you are. So it does not recommend you. Not because you lack expertise. Because you lack interpretability.
Ambiguity does not just lose clients. It loses the recommendation entirely.
What interpretability actually requires
Interpretability is not a technical problem. It is a positioning problem. It requires three things:
First, a clear and consistent definition of what you do and who it is for - one that appears in the same language across every place your name shows up. Not five variations. One.
Second, a documented point of view. AI tools summarize patterns they see repeatedly. If you have never written at length about how you think, what you believe, and what makes your approach different, the AI has nothing to pull from. It cannot invent authority that does not exist in your content.
Third, specificity. Generalist descriptions produce weak signals. The more precisely you can name the problem you solve and the person you solve it for, the more confidently AI can place you when that specific problem gets raised.
The founder who gets recommended vs the one who does not
Two founders. Same level of experience. Same quality of work. One gets recommended by AI tools regularly. One does not.
The difference is not credentials, audience size, or years in the field. The difference is that one of them has a digital footprint that tells a consistent, specific story - and the other has a scattered one that reflects every pivot, experiment, and reframe of the last five years.
The question to ask is not "how do I get AI to find me?" It is "if AI summarized my expertise right now, what would it say - and is that accurate?"
Most founders, if they are honest, would not love the answer.
This is still a brand clarity problem
Everything that makes you easy for AI to recommend is the same thing that makes you easy for humans to refer. Clear positioning. Consistent language. A documented point of view that appears across multiple contexts.
The AEO conversation is new. The underlying problem is not. Founders have always struggled to communicate their expertise in a way that travels without them. AI just made the cost of ambiguity higher and more immediate.
Fix the positioning. The discoverability follows.
AI discovery is a positioning problem. And most positioning advice, especially for experienced founders, was never built to solve it - because it was built for a different era and a different kind of buyer.