AI bubble could be more painful than dot-com crash, warns valuation expert Aswath Damodaran

The rapid rise of artificial intelligence has sparked comparisons with the dot-com boom of the late 1990s.

However, according to renowned valuation expert and NYU Stern School of Business professor Aswath Damodaran, the current AI investment cycle may carry risks that extend far beyond those seen during the internet bubble more than two decades ago.

The Indian-American academic, often referred to as the "Dean of Valuation," argued that the structure of today's AI investment wave is fundamentally different from that of the dot-com era, making any future correction potentially more damaging.

Speaking on the Excess Returns YouTube channel, Damodaran said that while it is impossible to predict whether the AI boom will end in a major correction, history suggests that periods of intense market enthusiasm are often followed by a downturn.

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Massive infrastructure spending sets AI apart

According to Damodaran, one of the biggest differences between the two technology booms is the scale of capital investment involved.

During the dot-com era, many companies were built around websites, software and internet services, requiring relatively limited spending on physical infrastructure.

Much of the investment came through equity markets, where investors purchased shares in fast-growing technology firms.

The AI boom, however, is being driven by enormous spending on data centres, semiconductor infrastructure, computing power and energy-intensive systems needed to train and operate advanced AI models.

"This has been the biggest infrastructure run-up I think I've ever seen in business," Damodaran said, comparing the scale of investment to the early growth of the automobile industry more than a century ago.

He warned that such large capital expenditures could magnify the impact of any future market correction.

Debt funding raises additional risks

Damodaran's larger concern is not just the size of AI investments but how they are being financed.

He noted that the dot-com boom was largely funded through equity. When technology stocks collapsed, investors suffered significant losses, but the damage was mostly confined to shareholders.

The AI expansion, by contrast, is increasingly being financed through debt, including funding from private capital markets rather than traditional banks.

According to Damodaran, this creates a risk that a slowdown in the sector could lead to financial distress, loan defaults and broader economic consequences.

"If there's a correction and companies start having problems, that problem is going to show up as distress and default," he said, warning that such effects could spread beyond investors and impact the wider economy.

Lessons from past market crises

While Damodaran stopped short of predicting a crisis similar to the 2008 global financial meltdown, he pointed to that period as an example of what can happen when lenders take excessive risks and capital is allocated too aggressively.

He stressed that his concern is not necessarily the decline of stock prices, but the possibility that companies burdened with large debts may struggle to meet their obligations if growth expectations fail to materialise.

"The potential societal cost of having to deal with debt coming due that you're unable to pay is much more painful than your share price dropping 90 per cent," he said.