AI Bubble vs Dotcom Bubble: 5 Chilling Parallels

Jim Rickards spends significant time in the AI Black Paper presentation drawing direct parallels between today’s AI boom and the dotcom bubble of the late 1990s. The comparison is not superficial. He identifies at least five specific parallels that deserve serious attention.

Rickards draws extensive parallels between today’s AI boom and the dotcom bubble of the late 1990s. During the internet boom, companies spent nearly half a trillion dollars on infrastructure, installing 80 million miles of fiber optic cable across America. Eventually, 85% of those cables went unused. Internet companies spent billions on infrastructure funded by debt they could not repay because they were not making money.

The parallels to today are striking. Tech companies are pouring unfathomable amounts into data centers. Speculative funds say AI will add $200 trillion to the global economy, which is nearly double the size of the entire global economy. The media is once again proclaiming a new paradigm. But underneath the hype, Rickards argues, AI companies are going broke and need new investors just to stay afloat.

Parallel 2: Circular Financing. Rickards draws a direct parallel between today’s AI companies and Lucent Technologies during the dotcom bubble. Lucent aggressively lent billions to cash-strapped customers to buy its equipment, booked the full sale as revenue upfront, and created what Rickards calls a feedback loop that cooked their books. The more money Lucent borrowed, the more it could loan out, the more it got back in revenue, and the more it could borrow. This is known as circular financing.

Today, Rickards argues, Nvidia is investing money in startups that then buy Nvidia’s chips. OpenAI invests in Oracle’s data center buildouts, which then use the money to invest back in OpenAI. Grace Blakeley, a research fellow, called Nvidia the central bank of AI and the lender of last resort. Michael Burry, the investor who predicted the 2008 subprime crash, has called Nvidia the Cisco of the AI boom and said this bubble is too big to save. Lucent ultimately fell from $75 to $0.76. Nortel fell from over $8,000 to around $50. Cisco collapsed from $50 to $8.

Parallel 3: Extrapolation Bias. Rickards introduces the concept of extrapolation bias to explain why most investors will miss the coming crash. People believe that because something has happened in the recent past, it is likely or even inevitable that it will continue happening in the future. This psychological trap makes even the highest IQ people deny a pending disaster, no matter how obvious the danger may be.

Rickards references his experience negotiating the LTCM bailout, where Nobel Prize winners with 150+ IQs managed a fund built on models that assumed the future would look like the past. Those models nearly blew up the entire U.S. economy. Myron Scholes, who developed the Black-Scholes Pricing Model that won a Nobel Prize, was among them. The lesson: intelligence does not immunize against extrapolation bias.

Parallel 4: Smart Money Exiting. Some of the most successful investors in the world are already exiting AI stocks. Stanley Druckenmiller, who predicted the 2008 financial crisis, has sold all his Nvidia and Palantir shares. Peter Thiel, a techno-optimist and venture capitalist, sold his entire Nvidia stake. Michael Burry made a $1.1 billion bet against AI. Paul Tudor Jones has said this is so much more potentially explosive than 1999. Jeremy Grantham, who once managed over $118 billion in assets, stated: This is obviously a bubble. The probabilities it doesn’t bust are slim to none. Former SEC Chairman Gary Gensler said AI will be the center of the future financial crisis. Even Sam Altman has admitted: A lot of people are going to lose a phenomenal amount of money.

Parallel 5: The Media Proclaiming a New Paradigm. During the dotcom bubble, Time Magazine was still saying stocks would go “to the moon” near the exact peak of the bubble. Today, Rickards notes, Time Magazine is once again saying AI is a new paradigm redefining capitalism itself. Speculative funds say AI will add $200 trillion to the global economy, which is nearly double the size of the entire global economy, in less than five years.

The key difference, Rickards argues, is scale. The AI bubble is 17 times larger than the dotcom bubble. The amounts being pumped into AI infrastructure dwarf what was spent laying fiber optic cables in the 1990s.

The counterargument is that AI companies are generating real revenue, unlike many dotcom companies. Microsoft, Google, and Amazon are profitable businesses using AI to improve their products. Rickards acknowledges this but argues that the valuations have far outpaced the revenue, and the circular financing patterns are a warning sign.

The AI Black Paper presentation promotes Strategic Intelligence, Rickards’ monthly newsletter from Paradigm Press. The price is $49 for 6 months, originally $299, an 83% discount that works out to about $8 per month. The guarantee is 3 months: subscribers can request a full refund for any reason within that window and keep all reports.

The package includes six months of Strategic Intelligence plus six special reports: AI Fallout (the biggest AI losers to remove from your portfolio immediately), The AI Black Paper Blueprint (his personal million-dollar roadmap), AI Meltdown Insurance (how to profit from the coming crash), Trump’s AI Arsenal (how investing in AI superweapons could turn $1,000 into $162,000), The Perfect Physical Gold Portfolio, and How to Make Your Home Your Personal Fortress.

Where to Learn More

For the complete analysis, read our AI Black Paper review covering Jim Rickards’ full thesis on the AI Minsky Moment.

Read our deep dive on circular financing in AI for the full Lucent comparison.

See our analysis of subprime AI debt for how data center bonds echo 2008.

Ready to explore Jim Rickards’ full research? Learn more about Strategic Intelligence here.

This is not financial advice. Always do your own research before investing.