Every generation believes it’s witnessing the next big thing. Today, it’s artificial intelligence. But history warns us: behind every revolutionary technology lies a speculative frenzy and a brutal correction. It started with the steam engine, then the railroads and steel factories, the telegraph, oil, the automobile, and the radio. Later came atomic energy and computers. Recent major technological advances came through computing and the internet, setting the stage for today's AI revolution.

Every major technological boom has followed a similar pattern: an overwhelming proliferation of new companies, excessive market speculation, and extraordinary levels of public hype.

AI is no exception. Just like the radio, computers, and the internet, there was consensus that the technology would transform the world, yet no one could agree on the extent of the transformation.

In the capital markets, valuations have reached fever-pitch levels despite economic headwinds. Recent tariff policies that theoretically should’ve dampened technology investments have had little effect on AI enthusiasm, highlighting the extraordinary investor confidence in this sector.

Major AI companies such as OpenAI and Anthropic have received eye-watering valuations. OpenAI (creators of ChatGPT) reached a $300 billion valuation, and Anthropic (creators of Claude AI) reached a $60 billion valuation in their respective funding rounds. Other companies such as Nvidia and Qualcomm have reached trading multiples between 50 to 150 times earnings per year. These valuations indicate that at the current earnings, it would take 50 to 150 years to break even on your investment, given the current cash flows.

These valuations are only achieved in the capital markets if investors believe in the future earning potential of a company. But with trillion-dollar market caps, the future seems a bit lofty and overvalued.

So it raises the question: Is the AI market in a bubble? The classic definition of a financial bubble is a rapid increase in asset prices disconnected from underlying fundamentals, driven primarily by speculative enthusiasm rather than realistic analysis of future cash flows. Like many previous technologies, people become eager to invest in anything related to the new technology in order to capitalize on its innovations, often abandoning traditional valuation metrics in the process. 

If we look back to the radio, many radio companies dominated the capital markets, but they yielded no major profits for the companies, which led to massive losses for shareholders. Radio Corporation of America (RCA) exemplifies this pattern. Its stock price soared from $1.50 to $114 per share between 1921 and 1929, only to collapse to $2.50 by 1932 despite the radio becoming a household necessity. They could not yield significant profits to justify its valuation.

In the computer market, investors backed major computer manufacturers, many of whom washed out due to major bankruptcies. Many once-dominant computer manufacturers like Compaq (later acquired by HP) and AST (now defunct) failed to reach the lofty valuations investors once predicted. Even IBM had to dramatically reinvent itself to remain relevant. 

Looking at the internet, there was a major internet bubble in the late 90s where internet companies reached the same fever pitch valuations radio and computer companies had before them. Internet companies were backed to valuations that were unsustainable with little to no earnings potential. It all came crashing down in 2000 when the dotcom crash happened.

Today, we see the same trend in AI with the previously mentioned OpenAI, Anthropic, Nvidia, Qualcomm, and so many more companies. Every new technology comes with high amounts of speculation and hype, leading to insane valuations based on future hopes of earnings.

In March 2000, the NASDAQ (a tech-heavy financial index) peaked at 5,048.62 points before losing 76.8% of its value by October 2002. Companies like Pets.com, which went from IPO to liquidation in just 268 days, exemplify the irrational speculation of that era.

Every single technological boom comes with a massive crash at the end, but we never know when the crash will be. After every crash, there are still a few intrinsically good companies with strong balance sheets, competitive moats, and leadership that are worth backing, such as Amazon and Google, and those companies will come to dominate their respective markets in a Pareto distribution of market share.

In addition to these tech companies, many companies that are in unrelated fields implement these technologies to increase their competitiveness. Walmart, for example, uses computers and data systems to manage their supply chain and inventory to keep costs low for the end-consumer. By utilizing tech advances, Walmart found itself in an advantageous position compared to stores like Sears, eventually outcompeting them and achieving great success.

While the AI boom will likely follow historical patterns with an eventual correction, savvy investors and businesses should look beyond the hype to identify companies with sustainable business models, practical applications, and genuine moats. Unlike previous technological revolutions, AI's potential to augment human capabilities across virtually every industry may produce more widespread and fundamental changes to our economy than any previous technological advance.

​​Some analysts argue that the AI boom is more sustainable than previous technology bubbles. They point to established revenue streams at companies like Nvidia, Microsoft, and Google, alongside genuine productivity gains already being realized. However, history suggests that even transformative technologies with real utility become subject to investment cycles where expectations temporarily outpace reality. The distinction may not be whether there's a correction, but rather its severity and timing.

The question isn't whether the AI bubble will burst, but rather which companies will emerge from the inevitable correction as the Amazons and Googles of the AI era.

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Index for terms:

NASDAQ: Tech-heavy online stock market and can be tracked as an index for how well the tech sector and tech companies are doing overall

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Y-Combinator: The World’s premier startup accelerator, founded by notable Silicon Valley legends such as Paul Graham. They’re highly influential in the tech world, and one of their major mentors is Sam Altman, the current CEO of OpenAI

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Cashflows: The Amount of cash flowing in and out of a business

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Valuation: How much a company is worth based off the market of investors 

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Trading Multiples: How much a current company is trading at based on its multiple of earnings. E.g. if Tiger Inc. makes $50 per year in profit and we value it at $500, it would be trading at a 10x multiple 

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IPO: Initial Public Offering. When a company goes public and gets listed on a stock market, where anyone can trade shares/ownership within a company 

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Pareto Distribution: An economic and social theory by Vilfredo Pareto that 80% of something always ends up being done or owned by 20%. In essence, a large majority of anything in life is always tied back to a smaller minority. For example, 80% of the work completed is done by 20% of the people or 80% of the wealth is owned by 20% of the people. 

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Capital Markets: The market for money to invest in things.

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Liquidation: Breaking a company down and selling off everything to pay off it’s creditors and investors.