The current hype around artificial intelligence significantly surpasses the infamous dot-com bubble of the late 1990s in key metrics. As an analyst, I see the parallels between these two eras becoming increasingly obvious, but the scale of the current boom is truly unprecedented.
To begin, let's recall the lessons of the past. The internet was a breakthrough technology that changed the world, yet the vast majority of companies from that era went bankrupt without building sustainable business models. Today's situation with AI largely repeats this scenario, but with far more impressive numbers.
Numbers That Cannot Be Ignored
The key difference lies in the scale of investments. According to my analysis, infrastructure spending during the dot-com era was about $500 billion. In the AI era, this figure has soared to $5.8 trillion — an increase of more than 11 times. The sizes of initial public offerings (IPOs) are also incomparable: the largest IPO during the dot-com era raised about $4 billion, while in the AI sector, this figure reached $86 billion.
Particularly alarming is the valuation of unprofitable companies. The largest unprofitable company of the dot-com era was worth about $100 billion. Today's equivalent is valued at $965 billion — almost ten times more.
Signs of Overheating and Dangerous Signals
The market is already showing classic signs of overheating. Unprofitable companies are going public at the peak of the hype, and the story with SpaceX is a vivid example: its shares went negative just a month after the largest IPO in market history.
Another alarming signal is the buyer financing scheme. Nvidia launched a program to finance its own customers, something Lucent and Nortel did in the late 1990s. For both companies, this ended in some of the largest bankruptcies in U.S. history.
Why Is the Current Bubble More Dangerous?
The main danger, in my opinion, is that the current bubble is "hidden under a layer of stocks." The dot-com bubble mainly consisted of securities. Today's includes private credit, project bonds, and insurance company money. All of this flows into data center infrastructure, creating a multi-layered structure that, upon collapse, could cause far more serious consequences.
A vivid example: Blue Owl froze investor withdrawals while simultaneously financing 80% of Meta's $250 billion campus in Louisiana. Oracle's rating was downgraded almost to "junk" status — half of its order book is tied to OpenAI. Anthropic has $90 billion in capacity lease obligations with zero profit before its IPO.
My conclusion: AI is a real technology, just like the internet in 1999. The question is not about its potential, but whether companies justify the amounts investors are paying for them. We will soon see the answer in public reports, and based on current data, a painful correction awaits us that could affect not only the stock market but also broader financial systems.