Al Root

DeepSeek, despite all its unknowns, caused investors to question everything they thought they knew about artificial intelligence.

The emergence of the apparently low-cost Chinese-built AI app is also leaving its mark on stock market valuations. That might be a bigger problem for investors.

The AI app was created for a few million dollars, billions less than U.S. models like OpenAI. And it was all done without the top-of-the-line chips that require so much energy. At least that is what reports suggest; these details haven't been confirmed. Plenty of questions remain about how the start-up could have pulled a feat like this off.

But the very notion that AI could be produced more cheaply has upended the AI trade.

Take Nvidia. Could it charge as much for chips if their best technology wasn't what powered DeepSeek? That question alone caused shares of the AI leader to plunge 17% on Monday, wiping out some $600 billion in market value.

And what about AI data center operators Microsoft, Amazon.com, and Alphabet? Are they spending too much on AI? Will they be able to charge hefty fees to access their chatbots if DeepSeek is so cheap?

Are projections for a surge in electricity demand related to more AI usage vastly wrong? That sunk shares of power producers like Constellation Energy, Vistra, and Talen Energy.

"I was flying back [from a trip on Monday] and was getting flooded with calls," says William Blair analyst Jed Dorsheimer. He covers energy and sustainability for the broker. "The questions are all super granular."

One question Dorsheimer got: "What's the percentage of inference" on electricity demand growth projections? Before Monday, investors probably never heard the word inference.

To build an AI application, an AI model must be trained. After it is trained, the model then can make "inferences" and answer questions or do the task it was designed to perform. The entire process requires power. DeepSeek claims to have cut the costs of training an AI model significantly.

Dorsheimer points to the so-called Jevons effect, which suggests that when things get cheaper, usage increases. So cheaper AI could mean more AI applications. That, very likely, means more electricity demanded for AI data centers, AI-trained robots, and AI-trained self-driving EVs.

That should be good for makers of electrical components and shares of generation equipment maker GE Vernova. Dorsheimer rates shares of the company Buy.

Still, through midday trading Friday, GE Vernova stock was down almost 10% for the week after a 22% plunge on Monday.

Investors aren't focused on potential benefits. They're focused on increased uncertainty. That has hit GE Vernova's valuation. Coming into 2025, the stock was trading for about 50 times estimated 2026 earnings. Now it trades for closer to 36 times.

"A week ago, my questions on GE Vernova were all big picture," Dorsheimer says. "What was shaken was a level of confidence around demand. You didn't have to worry about it [before]."

DeepSeek shook investors' faith. Valuations, to some extent, are built on faith.

"Psychologically, the human psyche craves certainty," Dorsheimer says. "The more you can provide an illusion of certainty, the higher your [valuation] multiple is going to be."

The AI trade has a new dynamic. Simplicity is gone. Now investors must understand the impact of lower costs on chip makers, data center operators, electrical component makers, and electricity demand.

Until that all is figured out, don't expect valuation multiples to return to where they were before the paradigm shift.

Write to Al Root at allen.root@dowjones.com

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January 31, 2025 14:51 ET (19:51 GMT)

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