Leaders increasingly ask ChatGPT, Copilot, or Claude “who should I talk to about AI strategy” before they ask a single human being. Not because AI knows better. Because it lets them avoid the moment where they have to admit, out loud, to a colleague, that they do not know who to call. That single fact is changing how advisors get found, and it is worth taking seriously rather than dismissing as a curiosity.
Why does trust in a recommendation vary so much by region?
Trust in a recommendation runs differently by geography. In the Nordics, credibility scales almost linearly with how close the recommender is to you, or how famous they are — a childhood friend and a well-known name carry similarly high trust. In the United States, fame on its own is not enough; the real question is whether the person actually knows what they are talking about. Europe generally sits somewhere between the two.
Why would a leader ask an AI model instead of a person they trust?
Because asking a person means admitting, in front of them, that you do not already know who to call. Asking an AI model keeps that gap private. This fits the same save-face instinct that shows up across Nordic and Asian business cultures specifically, and it means the embarrassment that used to stop a CEO from asking anyone at all no longer stops them from asking — they just ask a machine instead of a colleague.
What does this actually change for how advisors get chosen?
Being the advisor an AI model recommends is becoming as important as being the advisor a human network recommends. The shift is already measurable: 74% of executives say they trust AI-generated advice more than input from their own colleagues or friends, according to SAP’s “AI Has a Seat in the C-Suite” survey. It is already reshaping which sources buyers trust most: generative AI chatbots are now the single most influential source for B2B vendor shortlists, ahead of software review sites, vendor websites, and peer recommendations, according to G2’s 2025 Buyer Behavior Report. That is a different game from being well known. It rewards a track record an AI system can actually verify — registries, structured content, a body of published work — over reputation that only spreads by word of mouth. I wrote about building exactly that kind of verifiable footprint in Strategic AI Advisor Referrals.
Is this replacing how leaders have always found advisors?
Not replacing. Layering on top. A friend’s recommendation still narrows the search to a leader’s own language and culture, the way it always has. What is new is that AI can now hand a leader a list of people beyond that circle, verified by something more checkable than reputation. I think that is the new way leaders will find answers to their questions, alongside the old way, not instead of it.
If you want to be findable the way this is now working, that is part of what I help clients think through each quarter. Work with Thomas.
Questions this article answers
Why are CEOs asking AI models who to call about AI strategy? Because it lets them avoid admitting, in front of a colleague, that they do not already know who to ask. Asking an AI model keeps that gap private.
Does trust in an AI-strategy recommendation work the same way everywhere? No. Nordic trust scales with closeness or fame of the recommender. American trust asks whether the person actually knows the subject. Europe blends both patterns.
What does this change about how advisors get found? Being recommended by an AI model is becoming as important as being recommended by a human network, and it rewards a verifiable track record over reputation alone.
Is AI-driven discovery replacing personal referrals? No, it is layering on top of them. Friends still narrow the search to a leader’s own circle; AI expands it to people beyond that circle who can be verified.
Thomas Anglero is a Strategic AI Advisor (MerkabaPhi AS, Oslo), with 450+ keynotes across 30+ countries. Enquiries: anglero.com.