While chip manufacturers are reaping record revenues and profits from the AI boom , other companies are spending billions of dollars developing and operating the technology without demonstrating their ability to generate returns commensurate with their investments.
This surge is reminiscent of the dot-com bubble, when optimistic expectations drove technology stocks to record highs, before their collapse at the beginning of the millennium caused trillions of dollars in wealth to evaporate. Will the dot-com crisis repeat itself after more than a quarter of a century, or will the artificial intelligence boom be different from its predecessor? And what awaits the markets if profits fall short of investors' expectations?
When booms turn into economic bubbles
From speculation on tulip bulbs in Holland during the 1730s to the collapse of internet stocks at the beginning of the millennium, historical experiences provide examples of asset prices rising and then falling sharply, although the extent of the losses and their economic impact varied.
The article cautions against exaggerating the effects of the event, as the trade was limited to a small circle of wealthy merchants, and the evidence does not show clear bankruptcies or widespread effects on the Dutch economy.
A bubble does not necessarily have to be based on a useless innovation; it may start from a promising technology, and then exceed expectations regarding the ability of companies to generate profits.
Goldman Sachs' review of the dot-com bubble illustrates how internet companies attracted funding before proving the viability of their business models.
To illustrate this mechanism, imagine a startup developing a promising technology without making a profit. Its stock price rises because investors expect it to succeed in the future, and then the rise attracts buyers who bet on selling the stock at a higher price.
As the rise continues, the fear of missing out may drive more investors to buy, until prices become more linked to earnings expectations than to the company’s ability to generate income.
However, high prices are not enough to determine the existence of a bubble. Evaluating the value of a new technology requires predicting its market size, costs, and profits, which are difficult to determine early on.
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