When it comes to share price, nothing has been quite so good to companies these past couple of years as making waves in A.I. Much of the S&P 500’s gains over that period have been powered by a few companies with the 10 largest market caps — specifically companies who went all in on A.I. (Nvidia, Microsoft via Open AI, Alphabet… you get the picture). Tons of VC funding went to any and all companies touting some version of AI or Large Language Models (LLMs) in an otherwise tight funding environment. So… the question has to be asked… Are we due for a course correction?
We think yes.
Hindsight is 20/20
We’re not going to sit here and say it wouldn’t have been awesome to plow all our money into Nvidia in January of 2023. For those of you not following the A.I. hype train, most companies building LLMs use an army of Graphics Processing Units (GPUs) to power their neural networks. GPUs perform complex computations like machine learning better than the traditional CPUs you’ll find in your computer. So, when the A.I. boom kicked off with Chat-GPT, Nvidia’s stock went through the roof. They’re the biggest GPU manufacturer, so it made sense.
So yes, “betting it all on black” vis-a-vis Nvidia would have been great. But the truth is, we think the overall valuations for A.I. companies are going to cool, and a lot of portfolios are exposed.
Source: JP Morgan Report
If you look at the concentration of the S&P 500, we’re well above historical averages for how much the top 10 stocks are driving the overall index (and by extension, the overall economy). The Mag 7 (Alphabet, Amazon, Apple, Meta, Microsoft, Nvidia, Tesla) generated a 75.7% return in 2023 compared with the overall S&P’s return of 24.2%. And because the S&P 500 is weighted based on market capitalization, the largest companies make up a significant portion of the index. Historically, the top 10 stocks in the index usually make up closer to 20% of the index… they were 34% of the S&P 500 at the end of June. Given that much of that outperformance has been driven by growth (and/or hype) in A.I., portfolios with outsized Mag 7 exposure could be at risk if the Mag 7 turns less magnificent.
The Hype Cycle
Gartner has a great graph to describe hype cycles of new tech:
Much of the coverage of A.I. has been fawning… or apocalyptic. But we think Gartner is directionally accurate. It’s always hard to predict where you are in a graph like this, but this is our best guess:
It seems that much as every startup that touted crypto had VCs throwing money at them 5 years ago, A.I. has followed suit in the last couple of years. There are some pretty amazing use cases, sure, but much of the promise of LLMs has been largely that — promises.
“…[C]onsider for a moment the possibility that perhaps A.I. isn’t going to get that much better anytime soon. After all, the A.I. companies are running out of new data on which to train their models, and they are running out of energy to fuel their power-hungry A.I. machines. Meanwhile, authors and news organizations (including The New York Times) are contesting the legality of having their data ingested into the A.I. models without their consent, which could end up forcing quality data to be withdrawn from the models.
Given these constraints, it seems just as likely to me that generative A.I. could end up like the Roomba, the mediocre vacuum robot that does a passable job when you are home alone but not if you are expecting guests.
…Should we as a society be investing tens of billions of dollars, our precious electricity that could be used toward moving away from fossil fuels, and a generation of the brightest math and science minds on incremental improvements in mediocre email writing?”
While that was written before Apple finally joined the party at WWDC24 with its suite of “Apple Intelligence” (Apple really is the master of branding), the sentiment still holds true in our estimation (and the estimation of Matteo Wong at the Atlantic):
“Generative AI is coming to your smartphone, your laptop, and your tablet, shortcomings be damned. The move could well strengthen the Apple ecosystem—but if the technology exhibits even some of the failures typical of nearly every major [A.I.] rollout over the past two years, it could also be another sort of Trojan horse, bringing down the walled garden from within.”
It’s absolutely possible that Apple (and its partnerships with Open A.I. and Google) knocks it out of the park. In typical Apple fashion, they’re late to the innovation party, but generally do a better job of commercializing a nascent technology into mainstream adoption. But even so, the soaring valuations of A.I. companies have us watching our portfolio exposures a little more carefully at the moment.
All of this to say — we’re not predicting an imminent dotcom bust for A.I. It could be the real deal. But, the relative concentration of S&P 500 gains attributable to companies heavily leveraged in A.I., paired with the possibility of an approaching “Trough of Disillusionment,” means investors and advisors alike should be paying close attention to how much exposure their portfolios have to the Mag 7. If the A.I. boom cools, so too will a decent chunk of the valuations of some of these companies.
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