The way people find professionals has shifted in a way most people haven't fully noticed yet.

For years, search engines shaped discovery. You searched a name. Google returned results. You scrolled, clicked, formed an impression. It was passive discovery at scale, and visibility depended on having enough signal for search to surface you.

AI has changed this fundamentally. Now, when someone asks an AI assistant "who should I talk to about supply chain optimisation in Northern Europe," or "which experts understand this specific problem in my industry," the AI doesn't just find information. It ranks, summarises, interprets, and recommends people.

That's different. That's recommendation, not search. And it works entirely differently.

From search to recommendation

The shift from search to recommendation is more consequential than it sounds. When someone searches, they're active. They're looking. They've already decided they need help. With search, you can get lucky. Someone Googles and you're there.

Recommendation is quieter but more powerful. Someone asks an AI who they should talk to about something, and the system recommends you by name. You're not even in their deliberate search. You're in the system's mental model of "who knows what around here." That's where professionals are increasingly being discovered.

An AI forms its recommendation based entirely on available signal. Your published articles. Mentions of your expertise. Your digital footprint. The coherence and depth of your online presence. If the signal is thin or non-existent, the AI either makes a generic recommendation or skips you entirely.

What AI looks for in professionals

AI recommendation systems are pattern-matching engines. They're looking for coherence. Consistency. Depth. Someone who writes repeatedly about supply chain. Someone whose thinking shows evidence of genuine expertise, not just passing commentary. Someone whose digital presence tells a coherent story about what they know and what they care about.

This favours a particular approach to visibility: showing up consistently, building a body of work, allowing your thinking to deepen over time. It works against sporadic activity, unclear positioning, and thin digital presence.

The professionals who get recommended by AI aren't necessarily the most brilliant people in their field. They're the ones whose digital signal is clear and compelling enough that algorithms understand what they do.

You either exist to AI systems or you don't

Here's the uncomfortable part of all this: if AI doesn't know you, you don't exist to the people using it.

A founder is looking for a consultant. They ask an AI who the experts are. If your name and expertise aren't well-represented in the system's training data and ongoing observations, you're not going to be recommended. It doesn't matter if you're exceptionally talented. It doesn't matter if you've been working in this space for decades. If the signal isn't there, you're invisible to the system, and therefore invisible to the people using it.

This creates a strange new stratification. On one side, people with clear, visible, coherent presence who get recommended by algorithms. On the other, people with deep expertise but minimal digital signal who don't. The competence gap between the two groups might be tiny. The discovery gap is enormous.

What this means in practice

This isn't about gaming AI. It's about recognising that discovery is increasingly mediated by systems you don't control. And those systems have preferences. They prefer coherence over noise. Consistency over sporadic activity. Clear expertise over vague generalists.

If you want to be discoverable, you need to build signal. Write about what you know. Show your thinking repeatedly. Build enough of a digital footprint that when an AI is asked about someone like you, it can build a meaningful recommendation.

The professionals who understand this and act on it will be consistently recommended. The ones who stay invisible will struggle to be found, no matter how good they are.

The shift to AI-mediated discovery has already happened. You're either visible to these systems or you're not.

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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