Valérian de Thézan de Gaussan
AI is getting better very fast. It can write code, summarize documents, create plans, explain difficult ideas, and produce work in seconds that used to take hours. Because of that, many people think expertise will matter less. I think the opposite is happening.
The reason is simple: AI is not consistently good. It can give you an excellent answer one minute and a bad answer the next. The bad answer may not even look bad. It can sound confident, clear, and professional while still being wrong. An expert can usually tell the difference. A beginner often cannot.
AI is uneven
One of the strangest things about AI is that it can be brilliant and careless at the same time. You can ask it a difficult question and get an impressive answer, then ask something simple and get an obvious mistake. Sometimes it understands exactly what you want. Sometimes it misses an important detail, invents something, or gives you a solution that looks reasonable but would fail in the real world.
That makes AI different from traditional software. With normal software, we usually expect the same input to produce a predictable result. With AI, the quality can vary much more. That means the human using it still needs judgment. Someone has to decide whether the output is actually correct.
Experts know what good looks like
The biggest advantage an expert has is not that they know every answer. It is that they know what a good answer should look like. A good programmer can look at AI-generated code and quickly notice that something is unsafe, too complicated, slow, or simply wrong. A good lawyer can notice when an argument is weak. A good designer can see when something looks clean but does not solve the user’s problem.
The same is true in almost every profession. A good marketer knows when a message sounds nice but will not convince anyone. A good analyst knows when the numbers look impressive but the reasoning behind them is weak. AI can generate the work, but the expert judges the work. That difference is extremely important.
When AI is right, experts move faster
When AI gets things right, an expert can use it as leverage. They can give it a task, check the result, make a few changes, and move on. Something that used to take three hours may now take thirty minutes. The expert is not being replaced. The expert is simply able to work much faster.
This is where AI becomes especially powerful. A strong developer with AI can write more code. A strong analyst can explore more ideas. A strong writer can test more versions. A strong founder can examine more options before making a decision. The skill was already there. AI gives that skill more reach.
When AI is wrong, experts recover quickly
The real difference appears when AI makes a mistake. An expert usually sees the problem and knows what to do next. They may change the prompt, reject the answer, use only part of it, or solve the difficult part themselves. Because they understand the subject, they can stay in control even when the AI fails.
A non-expert has a harder problem. If the answer sounds believable, they may simply accept it. Then they build the next step on top of the mistake, and then another step after that. A small error at the beginning can become a large problem later. This is especially dangerous because AI is very good at sounding confident. A wrong answer written badly is easy to reject. A wrong answer written beautifully is much harder to spot.
AI gives beginners power, but not always judgment
This does not mean beginners should avoid AI. In fact, AI can be an excellent learning tool. It can explain ideas, answer questions, generate examples, and help people attempt work that would previously have been out of reach. It gives people a way to learn faster and experiment more.
But being able to produce something is not the same as being able to judge it. A beginner can now create a website in a day, but that does not mean the website is secure, maintainable, accessible, or well designed. Someone can generate a business plan in ten minutes, but that does not mean the assumptions are good. Someone can build an impressive financial model, but that does not mean the numbers make sense.
AI lowers the cost of producing work. It does not automatically give people the experience required to know whether that work is good.
The better AI gets, the more important judgment becomes
At first, this may sound strange. If AI keeps improving, should expertise not become less important? For some tasks, yes. There are many situations where the result only needs to be good enough. A simple internal email, a summary of some notes, a list of ideas, or a rough first draft may not require much expertise. In those cases, AI can often do the job perfectly well.
But the situation changes when mistakes are expensive. If you are building important software, making a major business decision, giving professional advice, designing infrastructure, managing money, or doing anything where quality really matters, judgment becomes critical. The more powerful the tool becomes, the more damage you can do if you use it badly.
AI does not remove skill. It multiplies it.
The useful way to think about AI is not “AI versus experts.” It is “experts with AI versus everyone else.” AI gives almost everyone access to powerful tools, but people do not get equal results from those tools.
The person who understands the subject can ask better questions, recognize better answers, catch mistakes earlier, and push the AI further. The person without that knowledge may still produce impressive-looking work, but impressive-looking and correct are not the same thing.
The future probably belongs neither to people who ignore AI nor to people who blindly trust it. It belongs to people who know their field and know how to use AI inside it.
AI can produce the answer. Expertise tells you whether the answer can be trusted.