Will AI Mimic the Dot-Com Bubble?

The explosion of interest in bots like ChatGPT has powered U.S. stocks to massive gains, leading to continued speculation over whether the AI investing craze may follow the path of the infamous dot-com bubble and crash of the late 1990s and early 2000s.

“Both represent transformative technological innovation that redefine industries and change societal behaviors,” Henry Nothhaft Jr., president of business consultancy EssentialDX who’s been involved in AI-based startups since 2009, told Cointelegraph. “As with the dot-com bubble, with AI, we’re experiencing a hype cycle characterized by rapid innovation, a frothy investment environment, a lot of new entrants and, I think, inflated expectations.”

The poster child of the mania is AI chip supplier Nvidia, which was trading at about $160 per share the day before ChatGPT made its public debut in November 2022 and is now trading at nearly $900 per share, according to Marketplace, becoming the third-largest U.S. company by market value.

Among the differences, the veterans of big tech dominate much of the AI enthusiasm, with the stock market’s recent rally led by the “Magnificent Seven” stocks: Alphabet, Amazon, Apple, Meta Platforms, Microsoft, Nvidia, and Tesla.

“It’s not like 1999 when investors were racing to hot IPOs for companies that had no chance of making money,” Mike Edwards, deputy chief investment officer of Weiss Multi-Strategy Advisers, told the Wall Street Journal. “Today’s winners are disciplined, enormous companies that have moats in place and data sets to exploit.”

Those discounting a full-fledged tech bubble arriving also note that AI is supported by tangible applications and use cases, with many companies incorporating AI into their operations and products.

In a blog entry, Lei Qiu, portfolio manager for disruptive innovation equities at investment management firm AllianceBernstein, noted that many of the mega-caps building out cloud infrastructure that supports AI are generating “substantial” revenues as clients seek productivity gains. She wrote, “Rather than anticipating the next big product — a failed tactic of the dot-com boom — today’s profitable AI stalwarts are spending on cloud infrastructure primarily to improve efficiency.”

Another difference is healthy skepticism surrounding the emerging technology. Governments across the globe, academic institutions, and even companies making AI software are studying its potential risks with a level of scrutiny that wasn’t present in the 1990s. Many investors are also believed to have taken lessons from past tech bubbles, from dot-com to crypto.

Critics question whether the technology will prove useful beyond a narrow set of tech juggernauts and ultimately fall short of projections.

“If you’re just a regular company, it’s not clear how AI is benefiting you yet,” Steve Sosnick, chief strategist at trading firm Interactive Brokers, told ABC News. “Is this helping Pepsi do their work more efficiently? Hard to say.”

“There is growing evidence that the hype machine is slowing down,” said a recent article in The Washington Post. While OpenAI, Microsoft, and Google have unveiled gaudy new products with fanfare, AI so far is “yet to upend the way people work and communicate with one another,” and profits continue to be elusive as AI tech “remains hugely expensive to build and run,” according to the Post.

As in past bubbles, hype may also periodically run ahead of the transformation the technology may ultimately deliver.

“Are we in an AI bubble? Yes,” Julie Wainwright, former CEO of Pets.com who went on to lead the RealReal and now heads an AI nutrition company, told Marketplace. “Will there be a rush to move the technology forward and companies funded that will fall by the wayside? Absolutely. But the technology’s real.”