The biggest risk to artificial intelligence investing may not be whether the technology works, but rather if it can be implemented much more cheaply than current massive investments suggest, according to Wharton finance professor Jeremy Siegel.
In an interview with CNBC, Siegel compared the situation to the dot-com boom and bust, noting that what ultimately caused the crash was the discovery that much more data could be transmitted through existing fiber optic cables than initially thought.
“Is there a possible way to get AI without spending the hundreds of billions of dollars on these centers?” he questioned.
Despite this caution, Siegel remains broadly optimistic about AI’s transformative potential. “AI is a revolution unlike anything we’ve seen in our lifetime,” he said, adding that it “could bring about economies of scale that far exceed what we saw from the development of the Internet.”
When discussing market valuations, Siegel noted that while the broader market trades at around 20x earnings, AI-focused companies command significantly higher multiples.
“Does that deserve a 30 or a 35 P/E while the rest of the market is 19 or 20? I would say yes,” Siegel said, suggesting the premium is justified by AI’s revolutionary potential.
Siegel acknowledged the risks of such optimism, conceding that claiming “it’s different this time” often leads to later regret.
However, he maintained his bullish stance, concluding that “we all agree that we are seeing things with AI that we have not seen in our lifetime,” suggesting that despite valid concerns about investment costs, AI represents a genuinely unprecedented economic transformation that warrants investor enthusiasm.
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