The AI Boom: Does the Story of Dot-Com Bubble Repeat?

If you’ve ever glanced at a stock chart or checked a market quotation, you are likely familiar with the term “bubble.” In finance, a bubble refers to a phenomenon where the prices of commodities, real estate, or assets like stocks experience a rapid and unjustified surge, driven by factors that are neither predictable nor rational. This steep price rise is often followed by a crash as investors rush to offload what they perceive to be overvalued assets.

History offers numerous examples of bubbles: the infamous stock market crash of 1929, the dot-com bubble of 2000, Japan’s Nikkei crisis of 1992, and the 2008 subprime mortgage crisis. When a bubble bursts, the fallout can ripple through entire economies, triggering recessions and affecting everyday lives. So, no surprise that the term “bubble” typically evokes dread.

But are bubbles entirely bad? Alan Greenspan, Federal Reserve Chair during the 2008 crisis, famously remarked, “There were no bubbles in the Soviet Union,” implying that such cycles are inevitable and even essential in a liberal economy. According to economic growth theory, it is not merely the increase in productive factors but technological progress that has significantly improved living standards over the centuries (Solow, 1957). Charles Kindleberger documented cycles of manias, panics, and crashes in financial markets as far back as the 1600s.

Research by the National Bureau of Economic Research (Randall Morck, 2022) highlights an intriguing perspective: while technological advancements create immense positive externalities, such as enabling market entry for new firms or enhancing societal well-being, chronic underinvestment in innovation persists across industries. The frenzied enthusiasm the bubbles generate can flood markets with liquidity. Even after a crash, the injected funds often catalyze technological growth, giving birth to new market movers and benefiting society long-term.

Take the dot-com bubble of the early 2000s. It was a period of irrational exuberance, with investors pouring capital into hundreds of startups without clear business plans or solid foundations. Most of these companies collapsed, resulting in significant losses for investors. Yet, we all know that a select few emerged as giants — Amazon, Google, and others — that have forever changed the way we live, work, and interact.

Fast-forward to today, artificial intelligence (AI) is dominating markets, led by companies like OpenAI and Nvidia. The chart below shows that since the release of GPT-4, the sector has seen record-breaking growth fueled by massive liquidity inflows. While this trend cannot be solely attributed to this technological milestone, the data speaks volumes. The ripple effects are evident across major indices: Nvidia, having dethroned Intel, now ranks among the top three constituents of the Dow Jones index, a testament to the company’s remarkable ascent in the AI era.

Many analysts are drawing parallels between today’s AI-driven market dynamics and the dot-com bubble. Various indicators suggest valuations have reached extreme levels of overpricing, reminiscent of those earlier times. This isn’t to say the AI bubble will burst tomorrow, but it’s a reminder that speculative euphoria rarely ends without a correction. This serves as a cautionary tale. Now might not be the best time to jump into the AI hype train; instead, it is an opportune moment for careful research. 

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