The artificial intelligence market has entered a phase that, in terms of scale, significantly surpasses the infamous dot-com bubble. Data analysis conducted by expert Hedgie shows that the parallels between the two eras are so obvious that ignoring them would be professional negligence. However, the current AI boom is not simply repeating the late 1990s scenario—it surpasses it across a number of critical indicators.
Shocking Numbers
Let's start with infrastructure. During the dot-com era (1999–2001), total spending on building network infrastructure amounted to about $500 billion. In the AI era (2025–2026), this figure has soared to $5.8 trillion—an increase of more than 11 times. The size of initial public offerings (IPOs) also shows a massive gap: the largest dot-com IPO raised about $4 billion, while in the AI sector, this figure reached $86 billion.
A particularly alarming signal is the valuation of unprofitable companies. The most expensive unprofitable company during the dot-com era was worth about $100 billion. Today's equivalent is valued by the market at $965 billion. And this is despite the fact that many of these giants not only fail to generate profits but also produce massive losses.
Signs of Overheating: Déjà Vu on a Grand Scale
Analyst Hedgie points to frightening parallels in market behavior. Unprofitable companies go public at the peak of hype, and SpaceX, for example, went into the red just a month after the largest IPO in market history. The buyer financing scheme is also concerning: Nvidia launched a program to finance its own customers, something Lucent and Nortel did in the late 1990s. This ended in some of the largest bankruptcies in U.S. history.
Why the Current Bubble Is More Dangerous
The main danger, according to the expert, lies in the fact that the AI bubble is "hidden beneath a layer of stocks." Unlike the dot-com bubble, which consisted mainly of stocks, the current bubble includes private credit, project bonds, and insurance company money. All these funds are flowing into data center infrastructure, creating a multi-layered structure that, upon collapse, could trigger a cascading effect.
Examples are already evident. Blue Owl froze investor withdrawals while simultaneously financing 80% of Meta's $250 billion campus in Louisiana. Oracle's rating was downgraded to nearly "junk": half of its order book is tied to OpenAI. Anthropic has $90 billion in capacity lease obligations with zero profit before its IPO.
Analyst's Conclusion: The Technology Is Real, the Price Is Not
AI is a real technology, just like the internet in 1999. But the question is not about the technology itself, but whether companies justify the amounts investors are paying for them. The answer, according to the expert, will soon come from public reports. I would add: history teaches us that bubbles burst not when the technology becomes obsolete, but when expectations no longer match reality. We are currently observing exactly this phase—and the scale of the consequences could be unprecedented.