AI Is the Bubble to Burst Them All
In the nearly three years since AI took center stage in Silicon Valley, the major players, with the exception of Nvidia, whose chips will likely still be in use after the bust, still haven't demonstrated what their long-term AI business model will be. OpenAI, Anthropic, and the AI-embracing tech giants are burning through billions, inference costs haven't fallen (those companies are still losing money on almost every user query), and the long-term viability of their enterprise programs is a big question mark at best. Is the product that will justify hundreds of billions in investment a search engine replacement? A replacement for social media? Workplace automation? How will AI companies price the costs of energy and computing, which are still skyhigh? If copyright lawsuits don't break their way, will they have to license their training data, and will they pass that extra cost on to consumers? IN recent MIT study made waves—and helped fuel this most recent wave of bubble fears—with a finding that 95 percent of companies that adopted generative AI didn't benefit from the technology at all.
“Usually the uncertainty goes down,” says Goldfarb. People learn what works and what doesn't. With AI, that has not been the case. “What has happened in recent months,” he says, “is that we have realized that there is a sharp boundary, and some of the earliest claims about the effectiveness of AI have been mixed or not as great as initially claimed.” Goldfarb thinks the market still underestimates the difficulty of integrating AI into organizations, and he's not alone. “If we underestimate this difficulty as a whole,” says Goldfarb, “then we're more likely to have a bubble.”
AI's closest historical analogue here may not be electric lighting, but radio. When RCA began broadcasting in 1919, it was immediately clear that it had powerful information technology in its hands. But it was less clear how that would translate into business. “Would radio be loss-making marketing for department stores? A public service broadcasting Sunday sermons? An advertising-supported medium for entertainment?” the authors write. “All were possible. All were subjects of technological narratives.” As a result, radio turned into one of the biggest bubbles in history – a peak in 1929, before losing 97 percent of its value in the crash. This was not an incidental sector; RCA was, along with Ford Motor Company, the most highly traded stock on the market. It was, like The New Yorker recently wrote“the Nvidia of its day.”
Pure Play
Why is Toyota valued at $273 billion while Tesla is worth $1.5 trillion to investors-when Toyota shipped more cars than Tesla last yearand brought three times as much revenue? The answer is linked to Tesla's status as a “pure-play” investment in electric (and to a lesser extent, autonomous) vehicles. In the 2010s, Elon Musk used all the exciting uncertainty surrounding EVs to tell a story about a future free of internal combustion engines that was so enticing that investors were willing to bet huge on a volatile startup about proven workhorses. A pure play company is one whose fate is tied to a certain innovation panning out, about which entrepreneurs may tell more exciting and fantastic stories, and you need them for a bubble inflated. They are the vehicle by which narratives turn into material stakes.
So far this year, accordingly Silicon Valley Bank58 percent of all VC investments have gone to AI companies. There aren't a ton of obvious pure-play investments available to retail investors — another criteria for inflating a bubble — but there are some big ones. Nvidia is at the top of the list, having staked its future on building chips for AI companies, and the first $4 trillion company in history in the process. If a sector sees a lot of pure plays, according to Goldfarb and Kirsch's framework, it is more likely to overheat and have a bubble. SoftBank has plans to sink tens of billions of dollars into OpenAI, the purest AI play out there, though it's not yet open to retail investment. (If and when it finally is, analysts speculate OpenAI could become the first trillion-dollar IPO.) Investors have also backed pure-play companies like Perplexity (now valued at $20 billion) and CoreWeave (market capitalization of $61 billion). In the case of AI, these pure-play investments are especially worrisome because the largest companies are increasingly interconnected. Nvidia just announced a $100 billion proposed investment in OpenAI, which in turn relies on Nvidia's chips. OpenAI relies on Microsoft's computing power, the result of a $10 billion partnership, and Microsoft in turn needs OpenAI's AI models.
