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The Stock Market’s commitment to AI, or how to separate the wheat from the chaff

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The recent stock market boom in the Artificial Intelligence industry has seen a vast number of companies, both large and small, as well as retail and institutional investors, trying to surf the wave of this new trend and generate economic returns. The fact that the Nasdaq 100 has surged by over 48% in the past year is nothing to sneeze at.

However, in many cases, the use of artificial intelligence is not necessarily the only or the best alternative that companies have for developing their business.

To better understand how to harness this technological development, we need to delve deeper into this industry’s value chain. As in most economic sectors, we can divide this industry into two parts: producers and consumers.

There are two major areas when it comes to the producers. Firstly, there’s the hardware enablers: here the clear example is Nvidia, whose GPUs (graphics processing units) are the fundamental physical element used to build large-scale deep learning algorithms. Then, we have solution and software enablers, such as large language models (Microsoft’s ChatGPT or Google’s Gemini).

However, it’s important to bear in mind that these are the most representative examples, where investors have already positioned themselves, recording significant gains over the past year (Nvidia +235% and Microsoft +64%, compared to +27% on the S&P500). This, in turn, has led to very demanding valuations, with Nvidia’s price-earnings ratio (PER) at 66x and Microsoft’s at 37x, compared to 21x for the S&P.

That’s why it’s worth looking at other areas/values that are just as significant. One example would be the production of GPUs, where Nvidia is merely a designer and needs to leverage other companies to be able to manufacture these devices. It’s a sector where TSMC is the undisputed leader, and whose valuation is significantly more attractive than that of the former, with a PER of around 20x.

In turn, producers are highly reliant on key equipment to manufacture these chips. This segment has well-known examples in Europe, such as ASML and its photolithography equipment, as well as some less familiar ones like its counterpart ASM, whose silicon wafer processing solutions will become increasingly important.

From the consumer’s perspective, it is vitally important to bear in mind how AI solutions will be used in their value proposition. To this end, we can divide companies into two major groups: those with a clear strategy regarding the inclusion of artificial intelligence solutions in their value proposition and those without one.

It’s evident that the focus in this case should be on the latter. However, this is only a necessary condition, not a sufficient one. A second critical factor that we must consider is profitability— not only in absolute terms, but also in relative terms. History has shown us how the implementation of new technological developments can cannibalize more profitable pre-existing businesses, as was the case analog and digital photography.

Artificial intelligence will be transformational, and we can already identify some of the winners of the future. However, there are still less obvious opportunities to benefit from this unstoppable trend.

César Gimeno, fund manager at MAPFRE AM.