The similarities are placing. Just like the web firms of 20 years in the past, AI corporations as we speak entice huge investments primarily based on transformative potential moderately than present profitability. International company AI funding reached $252.3 billion in 2024, in line with analysis from Stanford College, with the sector rising thirteenfold since 2014. In the meantime, America’s largest tech firms—Amazon, Google, Meta, and Microsoft—have pledged to spend a file $320 billion on capital expenditures this yr alone, a lot of it for AI infrastructure.
Even OpenAI CEO Sam Altman, whose firm is valued at roughly $500 billion regardless of launching ChatGPT simply two years in the past, acknowledges the parallels. “
Are we in a section the place buyers as a complete are overexcited about AI? My opinion is sure,” Altman mentioned in August. “Is AI the most important thing to happen in a very long time? My opinion is also yes.”
However what really brought about the dot-com bubble to burst in March 2000, and what classes does it supply for as we speak’s AI growth? Let’s take a stroll down reminiscence lane—or, when you weren’t born but, some plain ole historical past.
The right storm of 2000
The dot-com crash wasn’t triggered by a single occasion, however moderately a convergence of things that uncovered elementary weaknesses within the late Nineteen Nineties tech economic system. The primary crucial blow got here from the Federal Reserve, which raised rates of interest a number of instances all through 1999 and 2000. The federal funds fee climbed from round 4.7% in early 1999 to six.5% by Could 2000, making speculative investments much less enticing as buyers might earn increased returns from safer bonds.
The second catalyst was a broader financial recession that started in Japan in March 2000, triggering international market fears and accelerating the flight from dangerous property. This one-two punch of upper charges and international uncertainty brought about buyers to reassess the astronomical valuations of web firms.
However the underlying drawback ran a lot deeper: Most dot-com firms had basically flawed enterprise fashions. Commerce One reached a $21 billion valuation regardless of minimal income. TheGlobe.com, based by two Cornell college students with $15,000 in startup capital, noticed its inventory worth leap 606% on its first day of buying and selling to $63.50, regardless of having no income past enterprise funding. Pets.com burned via $300 million in simply 268 days earlier than declaring chapter.
Infrastructure overbuild
Maybe probably the most instructive parallel for as we speak’s AI growth lies within the huge infrastructure overinvestment that preceded the dot-com crash. Telecommunications firms laid greater than 80 million miles of fiber optic cables throughout the U.S., pushed by WorldCom’s wildly inflated declare that web visitors was doubling each 100 days—far past the precise annual doubling fee.
Corporations like International Crossing, Stage 3, and Qwest raced to construct huge networks to seize anticipated demand that by no means materialized. The consequence was catastrophic overcapacity. Even 4 years after the bubble burst, 85% to 95% of the fiber laid within the Nineteen Nineties remained unused, incomes the nickname “dark fiber.”
Corning, the world’s largest optical-fiber producer, noticed its inventory crash from almost $100 in 2000 to about $1 by 2002. Ciena’s income fell from $1.6 billion to $300 million virtually in a single day, with its inventory plunging 98% from its peak.
The parallels to as we speak’s AI infrastructure buildout are unmistakable. Meta CEO Mark Zuckerberg introduced plans this yr for an AI knowledge middle “so large it could cover a significant part of Manhattan”. The Stargate Mission, backed by OpenAI, SoftBank, Oracle, and MGX, goals to develop a $500 billion nationwide community of AI knowledge facilities.
But, essential variations exist. In contrast to many dot-com firms that had no income, main AI gamers are producing substantial revenue. Microsoft’s Azure cloud service, closely targeted on AI, grew 39% year-over-year to an $86 billion run fee. OpenAI tasks $20 billion in annualized income by the top of the yr, in line with The Info, up from round $6 billion in the beginning of the yr.
The large actuality examine
The dot-com crash in the end got here right down to a harsh actuality: Most web firms couldn’t justify their valuations with precise enterprise outcomes. Corporations have been valued primarily based on web site visitors and development metrics moderately than conventional measures like money movement and profitability.
As we speak’s AI firms face an identical check. Whereas AI funding has reached historic ranges, the income hole stays substantial. In response to tech author Ed Zitron, Microsoft, Meta, Tesla, Amazon, and Google can have invested about $560 billion in AI infrastructure during the last two years, however have introduced in simply $35 billion in AI-related income mixed.
A current MIT research discovered that 95% of AI pilot tasks fail to yield significant outcomes, regardless of greater than $40 billion in generative AI funding. This disconnect between funding and returns echoes the basic drawback that in the end doomed the dot-com bubble.
The query going through buyers as we speak isn’t whether or not AI will remodel the economic system—most specialists agree it is going to. The query is whether or not present valuations and infrastructure investments will be justified by near-term returns, or whether or not, just like the fiber-optic cables of the Nineteen Nineties, a lot of as we speak’s AI infrastructure will sit unused whereas the market awaits demand to meet up with provide. As historical past exhibits, even transformative applied sciences can’t escape the gravitational pull of economics—so whereas the web did change the world, it didn’t occur as shortly as a few of its early champions promised, and several other of these individuals who obtained forward of themselves have been humbled within the course of.
For this story, Fortune used generative AI to assist with an preliminary draft. An editor verified the accuracy of the knowledge earlier than publishing.
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