I vividly remember the market excitement of 1999-2000. The media was filled with fears of the “Y2K bug” and booming “internet” headlines. While many feared computers would fail to handle the date change to 2000, others were thrilled by the internet’s promise of massive productivity boosts. Back then, as a venture capitalist, raising money for anything .com related was remarkably easy. However, things changed dramatically just a few months into the year 2000.
Back then, the S&P 500, especially the Nasdaq, skyrocketed daily. The big names surged, forcing indexers and ETFs to buy more to keep up, creating a positive feedback loop that fueled higher and higher market gains. It was a gold rush for investors.
The Dot-Com Craze of the ’90s
Much like then, we see investors today chasing anything related to “artificial intelligence” (AI). In 1999, companies added “.com” to their names to attract investors. Now, companies are announcing AI strategies left and right. According to the Accenture Technology Vision 2024 Report, the number of companies mentioning AI on earnings calls has skyrocketed since the launch of ChatGPT.
However, unlike the dot-com era, today’s AI companies have actual revenues and profits. But does that mean we’re safe from another market disappointment?
A Forced Feeding Frenzy
In 1999, as the dot-com bubble grew, ETF providers and index managers had to buy more of the largest stocks to keep up with the index. This created a feeding frenzy. Similarly, today, the top 10 stocks in the S&P 500 make up over one-third of the index. A 1% gain in these top 10 stocks impacts the market just as much as a 1% gain in the bottom 90%.
As money flows into passive ETFs, all underlying companies’ shares must be purchased, driving up the biggest stocks’ prices and creating a mirage of market stability. As of June 10th, only 31% of stocks were outperforming the index as a whole. The lack of market breadth becomes evident when comparing the market-cap-weighted index to the equal-weighted index.
The Bubble Risk
Despite this forced feeding frenzy, there’s no immediate threat of a market reversal. Even if we are in a bubble, it can last longer than expected. The real risk comes when reality fails to meet expectations. Sales growth expectations for AI are incredibly high, and while it’s possible they’ll be met, there’s also significant risk.
Trees Don’t Grow to the Sky
Back in 2000, companies like Cisco Systems (the Nvidia of the dot-com era) saw their valuations plunge back to reality. The same could happen with AI. Nvidia has benefited hugely since the launch of ChatGPT, but there are risks. Demand could fall if AI is overhyped, competition could lower prices, suppliers might want a bigger share of revenue, and scale might not matter as much as expected.
Several investing legends advise caution, questioning how investors will be compensated when training an AI model costs hundreds of millions to billions of dollars each time. This AI boom is just another in a long line of investment themes.
Elon Musk on AI Investment: “The promise of AI is vast, but the costs associated with its development are equally enormous. Investors should ask themselves, ‘What is the path to profitability when the initial investment is so high?'”
Peter Thiel on Emerging Technologies: “Every technological boom, including AI, presents a compelling narrative, but prudent investors must scrutinize the financial realities. How will substantial upfront costs translate into sustainable returns?”
Warren Buffett on Market Trends: “While AI is the current trend captivating the market, it’s essential to remember that every investment theme carries inherent risks. Investors must consider the long-term viability and the substantial costs involved in developing these advanced technologies.”
Training large AI models currently costs around $100 million, and this expense is projected to escalate, potentially reaching $1 billion for models in development now and up to $10 billion by 2025-2026 (Epoch AI) (THE DECODER). These staggering costs highlight the need for careful financial analysis and strategic planning in AI investments.
What History Teaches Us
Past booms, like those in SPACs, crypto, and meme stocks, provided opportunities but ended brutally when they reversed. Each phase of innovation led to stellar market returns as investors chased new opportunities. We are in another speculative boom with AI, and once again, people believe “trees can grow to the sky,” a German proverb suggesting natural limits to growth.
While today isn’t exactly like 2000, there are similarities. Will this time be different, or will the AI bubble burst just like the dot-com bubble did? Unfortunately, we won’t know until we can look back through the lens of history.
FAQs
- How does the current AI boom compare to the dot-com bubble? The AI boom shares many similarities with the dot-com bubble, such as rapid growth and investor enthusiasm. However, many AI companies today have real revenues and earnings, unlike many dot-com companies.
- What are the risks of investing in AI stocks? Risks include overhyped demand, increased competition, revenue sharing pressures, and scalability issues.
- How can investors navigate the AI boom? Investors should be cautious, focusing on companies with solid fundamentals and realistic growth prospects.
- What lessons can we learn from the dot-com bubble? Growth has natural limits, and hype can drive prices unsustainably high. It’s essential to keep a balanced perspective and not get swept up in market mania.
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