A few weeks ago, on a Link•Ability member call, one of our community ran a live experiment. She opened a private browser window – logged out of everything, no history, no personalisation – and gave the same prompt to ChatGPT, Claude, Gemini, and Perplexity: surface whatever you can find out about me.
Four tools. Four noticeably different answers.
ChatGPT built its picture of her from her LinkedIn® newsletters and articles. Claude and Gemini barely touched LinkedIn at all – they reached for guest articles she’d written for an industry association years earlier. Perplexity went broadest, pulling in YouTube and sources from across the open web.
Same person. Same question. Four different professional reputations.
That’s the uncomfortable truth for every senior leader right now: you no longer have one professional reputation. You have several – one for every AI tool that gets asked about you. And you don’t choose which version the board chair, the conference organiser, or the prospective client consults.
Coherence beats credentials
When an AI tool is asked about you, it isn’t weighing your CV. It’s parsing your signal – the words, patterns, and sources that make up your public professional footprint – and composing a version of you from whatever it finds. If your profile says one thing, your published work says another, and your most recent activity says nothing at all, the system doesn’t give you the benefit of the doubt. It gives no second chances to a story that doesn’t add up.
This is the second foundation of the Link•Ability Blueprint – the system I use with every client – and we call it Perception: not whether you can be found, but what the systems that find you conclude. Twenty-five years of hard-won expertise counts for very little if the public record of it is scattered, dated, or misaligned.
What the 2026 research shows
Through early 2026, three independent studies – Meltwater’s GenAI Lens analysis of 9.5 million AI citations across 16 B2B categories, research from Profound on professional queries across six AI platforms, and a Semrush × LinkedIn study spanning 325,000 prompts – converged on the same picture of what AI systems actually cite.
Three findings matter most for senior leaders:
1. Individual voices beat company pages.
Around 75% of the LinkedIn content AI tools cite comes from individual profiles, not company pages. Your organisation’s comms team cannot do this for you.
2. You don’t need a big following.
Just over half of the people AI tools cite have fewer than 10,000 followers – and the group contributing the single largest share of citations sits between 1,000 and 10,000. Not influencers. People with modest, credible, focused audiences.
3. Recency is ruthless.
Nearly half of everything cited is less than three months old, and content older than a year barely registers. A dormant profile isn’t neutral – it ages out of the conversation entirely.
If you’re a senior leader who assumed visibility was a volume game you’d already lost, the data says the opposite. The field is more open than it has been in years. It just rewards different behaviour than it used to.
How to close the gap: three actions
In Episode 5 of The Visibility Advantage Podcast I unpack all of this in depth, but the practical response comes down to three moves you can start immediately:
1. Run the four-model test.
Open a private browser window and ask ChatGPT, Claude, Gemini, and Perplexity the same question: what can you find out about you, in your field, in your city? Note what each gets right, gets wrong, and misses entirely. Almost everyone who runs this finds at least one surprise.
2. Do the alignment audit.
Put your LinkedIn headline, your About section, and your three most recent pieces of public content side by side. Do they describe the same expert? If a stranger – human or machine – read only those, would they categorise you correctly? Misalignment here is why capable leaders don’t surface for the expertise they actually have.
3. Publish for the citation layer using four words: specific, structured, named, fresh.
Take a position on a real question. Give your thinking a visible shape – clear openings, numbered points. Name the actual tools, frameworks, and organisations you mean. And keep the cadence going – one clear, substantive post a fortnight, sustained, does more for your discoverability than a viral moment followed by silence.
Why this is really about trust
It would be easy to read all of this as optimising for machines. It isn’t. Because different AI tools read different corners of your footprint, coherence everywhere is the only strategy that doesn’t depend on guessing which tool gets asked. And a footprint that is consistent, current, and clearly yours is exactly what humans have always needed before they choose someone: a story that adds up. Trust, in other words. The machines have simply made the gaps visible faster.