A friend of mine runs mobile coffee bars for events. We were talking about her business recently, and she told me something that stopped me mid-conversation: about thirty percent of her new customers now find her through ChatGPT and Google. People asking AI who does what she does — and her name coming up.
In the same week, I asked AI who the best real estate agent is in a friend's province. He's the best I've worked with in a decade. Four queries. He showed up once, at number twenty-five. On two queries, he didn't appear at all.
Something fundamental has changed in how professionals get found. And most people haven't caught up yet.
AI doesn't search. It recommends.
When a potential client or partner asks ChatGPT, Perplexity, or Google's AI Overview about professionals in a given field, the AI doesn't return a list of links. It constructs a curated answer — drawing from entity signals it can verify across the web.
Published articles. Author profiles. Professional databases. Structured data on websites. Consistent biographical information that reinforces the same expertise across multiple platforms.
If those signals exist and align, you appear in the answer. If they don't, you don't exist in the AI's model of your industry.
The data is stark. Half of all searches now trigger AI-generated responses. The majority end without the user clicking a single link. Content with more than fifteen connected entity signals shows nearly five times higher probability of being selected by AI systems.
What the documented professionals do
I've studied this pattern closely over the past year. The professionals who appear in AI recommendations share a few traits — none of which require fame or a large following.
Their name and positioning are consistent everywhere. Same expertise described the same way on LinkedIn, their website, Medium, author profiles, and professional databases. Their website carries structured data — Schema.org markup that explicitly tells AI systems who they are, what they specialise in, and where else to verify them. They've published enough content across enough platforms that AI can cross-reference their expertise.
This isn't about producing content at scale. It's about building a documented professional identity that AI systems can read and trust.
The practical layer
A personal website with JSON-LD structured data and a sameAs array linking your profiles. Two or three platforms where you publish consistently. Author profiles on Amazon or similar if you've written a book. Professional entries on Crunchbase, ORCID, or Wikidata if they're relevant to your career.
Each of these is a data point. When they're consistent and reinforcing, AI systems develop confidence in your identity. When they're scattered or absent, you're simply not part of the conversation.
The window for building this advantage is now — while most professionals still think of visibility as a social media game. By the time AI-driven discovery is the undisputed default, the positions will already be established.
The question worth asking: if someone asked an AI about your area of expertise today, would your name appear in the answer?
Laurent Terrijn is a serial entrepreneur, author of The Foundation: 30 Lessons That Matter, and personal brand strategist with over 15 years of experience building businesses across Europe, Southeast Asia, and the Middle East. He writes about entrepreneurship, systems thinking, and building things that last.
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