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Looking at AI Stocks: What to Check

How do you assess shares of artificial intelligence companies? A general guide to business model, valuation, hype cycles, volatility and spreading risk through ETFs.

Daytraders.nl redactie · February 24, 2026 · bijgewerkt October 10, 2026 · 5 min leestijd

In short

  • “AI stock” is not a fixed term. Companies can earn money from AI in many ways, or only talk about it.
  • Look at the business model first: where does the money come from?
  • High expectations are often already in the price. That is called valuation.
  • Themes like AI often go through hype cycles: lots of enthusiasm, then sometimes a sharp fall.
  • Many AI companies are large and linked to one another. That creates concentration risk.
  • This article gives no forecasts and no price targets.

What do we mean by AI stocks?

AI stands for artificial intelligence: software that performs tasks that normally need human thinking, such as writing text, recognising images or analysing data. By “AI stocks”, people mean shares of companies that do something with AI. That can cover a lot:

  • companies that build AI software or services;
  • companies that supply the chips and equipment AI runs on;
  • companies that rent out data centres and cloud capacity;
  • companies that use AI to improve their own work.

These groups earn money in different ways and face different risks. There is no official list of “AI companies”. Funds and the media draw the line themselves.

Step 1: look at the business model

Ask yourself a few simple questions:

  1. How does the company earn money? Does it sell products, subscriptions or services?
  2. How much of its revenue really comes from AI? Sometimes it is a small share. The rest comes from other activities.
  3. Who are the customers? Does the company depend on a few large customers?
  4. Does the company make a profit? Or is it burning cash in the hope of growing later? That shows in the annual accounts. Read more about profit and loss statements and earnings reports.

You can find more on this approach in the tutorial on fundamental analysis.

Step 2: understand valuation

Valuation asks whether the price is reasonable compared with what the company earns. A well-known measure is the price-to-earnings ratio (P/E): the price divided by earnings per share. A high P/E means investors are paying a lot for each euro of profit. They are counting on strong growth.

A hypothetical example: share A costs 20 times annual earnings, share B 80 times. For B, expectations are much higher. If growth turns out lower than investors hoped, the price can fall sharply, even if the company itself is not doing badly. A low P/E does not automatically mean a bargain, and a high one does not automatically mean it is too expensive. The measure is a starting point.

Hype and its cycles

With new technology you often see the same pattern:

  1. A new technology gets lots of attention.
  2. Investors expect a lot and prices rise quickly.
  3. Many new companies and funds appear.
  4. Reality sometimes falls short of expectations. Sentiment turns and prices fall.
  5. What is left afterwards may well have value. That is not true of every company.

This pattern is not a law. It is a way to look critically at your own enthusiasm. Read also about market psychology.

Swings and concentration risk

AI stocks often swing sharply. This is called volatility. You can lose a lot in a short time, even if the company recovers later.

There is also concentration risk: a large part of the value sits with a small number of big companies. Broad stock indices sometimes have this too, because the largest companies weigh heavily in them. So when you look at an ETF, check which companies carry the most weight. Interdependence matters as well: if demand for chips falls, that also affects the companies that use them.

Regulation adds another factor, such as the European AI Act. New rules can change companies’ costs or opportunities. How is hard to say in advance.

Spreading risk through ETFs

If you do not want to pick a single share, an ETF lets you invest in several companies at once. Some ETFs focus on technology or on AI. Diversification reduces the risk of one bad pick, but not the risk of the theme itself. If the whole sector falls, such an ETF falls too. Look at:

  • which companies it holds and how much each one weighs;
  • the ETF’s costs (the ongoing charges, TER);
  • how large and easy to trade the fund is.

Read more about ETFs and about portfolio basics and diversification. See also the page on stocks.

How do you keep it manageable?

  • Decide how much you can lose before you buy. See risk management.
  • Limit the share of any one theme in your portfolio.
  • Read the company’s own sources, such as annual reports, and be critical of stories on social media.
  • Compare broker costs on the broker comparison.

Conclusion

There is no reliable way to know which AI stocks will do well. What you can do is learn how to look: at the business model, the valuation, the chance of a hype, the swings and how your money is spread. That helps you decide for yourself whether, and how much, risk you want to take.

Investing involves risk and you can lose all or part of your money. This article is general education, not investment advice.