The global artificial intelligence race is fuelling one of the largest investment cycles in technology history. From data centres and advanced chips to cloud infrastructure and computing power, companies are spending billions of dollars to secure a leadership position in AI. But according to renowned valuation expert Aswath Damodaran, today's AI boom differs significantly from the dot-com era — and that could make any future correction far more painful.
Speaking on the Excess Returns podcast, the NYU Stern School of Business professor, often called the "Dean of Valuation", said history suggests every major technology boom eventually faces a correction. The crucial question is whether the consequences of an AI downturn will resemble the dot-com crash of the early 2000s or something more severe.
Damodaran argues that the internet boom was largely driven by software businesses and equity capital. Companies launched websites, online services and digital platforms with relatively limited investment in physical infrastructure. When the bubble burst, technology stocks collapsed and investors suffered steep losses, but the damage remained largely confined to shareholders.
"The dot-com boom and bust had no huge capital expenditure in that cycle," Damodaran said. "When the bust came, shareholders lost 60%, 70%, 80% or 90% of their money. The loss was restricted to the shareholders."
The AI boom, however, is built on a very different foundation. Training and deploying advanced AI models requires enormous investments in graphics processors, data centres, energy infrastructure and cloud computing networks. Damodaran described it as the biggest infrastructure buildout he has seen in business history, comparing it to the rise of the automobile industry a century ago.
What worries him most is how this spending is being financed. According to Damodaran, a significant portion of AI-related infrastructure investment is being funded through debt rather than equity. Much of this borrowing is coming from private credit markets rather than traditional banks. If AI revenues fail to justify the scale of today's investments, companies could face financial distress and defaults.
"The problem with the AI capex boom is that not only is it immense, but a big chunk of it is funded with debt," he said.
That distinction matters because debt problems rarely stay confined to investors. Defaults can affect lenders, private credit funds and broader financial markets, creating ripple effects across the economy.
Damodaran stopped short of predicting a repeat of the 2008 global financial crisis, but warned that excessive lending during periods of optimism often leads to wider economic pain when expectations fall short.
His warning is not that artificial intelligence will fail. Instead, it is a reminder that transformative technologies can still experience periods of excessive optimism. While AI may eventually reshape industries and generate enormous value, investors must distinguish between genuine long-term opportunity and speculative enthusiasm.
Essential Business Intelligence, Sharp Market Insights, Practical Personal Finance Advice, Daily Fuel, Gold and Silver Prices and Latest Stories — On NDTV Profit.