AI systems are changing how people find experts, matching specific problems to specific expertise instead of generic keyword searches, and visibility now decides who gets found.
The question changed.
A few years ago, someone might ask: "Who's the best marketing consultant in Dubai?" Today they ask: "I'm building a SaaS product for small businesses in the Gulf. Who can help me with go to market strategy for this specific market?"
That shift changes more than the wording. It changes how people find help.
People no longer search by job title or role. They describe their specific situation and ask AI systems to find someone who understands that exact context.
This is remaking how experts get discovered, how platforms become valuable, and who wins in the creator economy. Most people have not noticed it yet.
The Shift From Generic to Specific
The old way of finding experts was categorical. You needed help with marketing, so you searched for "marketing consultants in Dubai." You got a list of people in that category and picked one based on price, portfolio, or referral.
The new way is contextual. You describe your situation: a founder of an ed-tech company that just launched in the UAE, with product market fit in Saudi Arabia, struggling to structure pricing across markets. Then you ask who you should talk to about it.
When you ask an AI system that question, it does not search for "pricing consultants." It reasons through who has built in this space, who understands Gulf markets, who has dealt with educational product pricing, and who understands the regulatory nuances. It is trying to match your specific problem with someone who has specific expertise.
Most "pricing consultants" will not show up for that search. The person who built an ed-tech company in the region, who navigated these exact market dynamics and understands Saudi and UAE regulatory differences, will.
What This Means for How People Become Discoverable
The old playbook was simple: get good at something, build a portfolio or credentials, and get found when someone searches your category.
The new playbook is different: get good at something specific in a specific context, do work that generates visible evidence such as writing, speaking, or building, and get recommended when someone describes a situation you have solved before.
The difference matters: you now aim to be top of mind for specific problems, not simply findable within a broad category. That requires being visible in a different way.
The Context-Specific Opportunity
If you are an expert, this is good news. Instead of competing with thousands of people in your category, you become visible to the specific subset of people who have your exact problem.
That means you can charge more because your expertise is not commoditized. You get better clients because they found you for exactly what they need. You can be more selective because people self-filter before they reach out. And your expertise matters more because it is specific, not generic.
The real question is whether you are discoverable when someone describes your exact situation to an AI. Building a strong expert profile is the first step toward that kind of visibility.
How AI Systems Are Actually Making Discovery Decisions
When you ask ChatGPT or Claude for a recommendation, the system works through a few questions: what specific problem is being described, what type of expertise would actually solve it, who has demonstrated that expertise, what evidence of that expertise is available, and who would be credible for this specific situation. Then it makes a recommendation.
It reasons through what it knows about the world rather than pulling answers from a database.
The people who show up in recommendations are the ones who have publicly demonstrated expertise in that specific domain, who have written or spoken about solving those specific problems, who have built or advised on something in that context, who have a visible track record, and who are mentioned or cited in relation to that expertise.
They do not need to be famous. They need visibility in the right way.
The Platform Angle
This is also changing how platforms become valuable. The old discovery platforms, listings of consultants and freelancer marketplaces, worked by category: browse marketing consultants, scroll through people with similar credentials, and hope to find the right fit.
The new platforms need to work differently: describe your situation, and the platform finds the expert who has solved it before.
That requires deep expertise tagging beyond simple categories, evidence of expertise such as case studies, writing, and speaking, contextual matching between specific problems and specific expertise, and AI powered recommendation that reasons about fit rather than matching keywords.
Platforms that can credibly answer the question of who someone should talk to for a specific situation become very valuable, because they do what people increasingly ask AI systems to do, with structured data and human credibility layered in.
The Implication for Experts
If you are an expert, this is worth thinking about now. Someone in your domain is going to ask an AI system for help, not if but when. The question is whether you are discoverable.
A few things matter most. Visibility of your expertise: have you written about your specific domain, spoken about it, shared case studies, or built something visible? Specificity: are you visible as an expert in a specific problem or domain, or only broadly in your category? Context: does your expertise have a clear context, such as scaling SaaS in the Middle East rather than generic SaaS consulting? Evidence: can someone verify your expertise by finding your work, your speaking, your insights, or your case studies? Discoverability: when someone asks an AI about your specific domain, can the AI find evidence of your expertise?
The Content Implication
This also explains why content is becoming more important, not less. If you are discoverable through AI recommendations, the path usually looks like this: someone asks an AI for expertise in your domain, the AI mentions you or finds your content, that person reads your content or learns about you, and if you have been helpful and credible, they reach out.
Your content does the work of proving you understand their problem. Generic content does not demonstrate that. A post titled "10 Tips for Success" shows nothing specific. A post that explains how you solved a particular problem in a particular context, and what surprised you along the way, demonstrates real expertise, the same idea behind Advice Was Never Free. Content That Converts goes deeper into what that kind of content looks like in practice.
The Shift Is Already Happening
This is not speculative. People are already doing it.
Searching Google for experts feels less useful because the results are often pay to play: everyone who bid on the keywords, not everyone who actually built something in that space.
Asking ChatGPT who to talk to about go to market strategy for a B2B SaaS product in the UAE gets a thoughtful answer based on what the AI knows about available expertise. People are starting to prefer that.
Once Google's AI Overviews and ChatGPT recommendations become the default way people find experts, the entire discovery landscape shifts, and it is happening faster than most experts realize.
What Comes Next
A few consequences are likely. Generic expertise becomes harder to monetize, while specific expertise becomes more valuable. Platforms that can credibly match specific problems to specific expertise become important intermediaries. Public work becomes a kind of resume: what you have written, spoken about, and built is how people evaluate whether to work with you. Being well known in specific communities makes you more discoverable to AI systems through mentions, citations, and connections. And fake credibility becomes harder to maintain once AI systems are reasoning through what is actually true about your background.
The Real Opportunity
For experts, this is a real opportunity. It means you cannot hide behind general credentials or a polished website alone. It also means you compete on actual expertise rather than marketing budget, your clients find you because you solve their specific problem, you can charge what your expertise is worth, and you get better clients because they are self selected for fit.
The question is whether you are visible in this new discovery paradigm. If you have been building in public, sharing your expertise, and talking about the real problems you have solved, you probably are. If you have been working quietly with no public visibility, you are about to become much harder to find.
Pricing your time appropriately matters too once that visibility starts converting into demand. See The Expert's Guide to Pricing Your Time for how to think about it.
The shift is real. Start by making sure your expertise is listed where AI systems and the people relying on them can find it.
Frequently Asked Questions
How does AI decide who to recommend as an expert? AI systems reason through the specific problem being described, then look for people who have publicly demonstrated relevant expertise through writing, speaking, case studies, or a visible track record in that exact context, rather than matching broad job title keywords.
Do I need to be well known to show up in AI recommendations? No. You need visibility in the right context. A person with deep, specific expertise in a narrow domain can be more discoverable to AI than a generalist with a larger following, because the AI is matching specific problems to specific expertise.
What can I do to become more discoverable to AI systems? Publish specific, evidence based content about problems you have actually solved, keep your expert profile current, and make sure your work is visible in the places AI systems draw from, such as your own writing and public case studies.
Will traditional search still matter if AI recommendations grow? Yes, for now. Traditional search and AI recommendations are running in parallel, and the same visibility habits, public writing, clear case studies, and a well built profile, tend to help with both.