MIT Technology Review examines what happens when the AI bubble bursts, warning that hyperscalers may need to nearly triple productivity by 2030 just to break even on their trillion-dollar infrastructure bet.
Wharton finance professor Jessica Wachter and a coauthor built the estimate around confirmed hyperscaler outlays, projecting nearly $1.1 trillion in data center spending through 2027 across Alphabet, Microsoft, Amazon, Meta, and Oracle. The wager matters well beyond Silicon Valley.
Inside the AI Bubble’s Productivity Math
Wachter previously served as chief economist at the Securities and Exchange Commission (SEC). She found hyperscaler productivity must grow 2.7 times over to break even by 2030.
That calculation accounts for the cost of capital, a 15% return, and depreciation of the assets. Absent that growth, Wachter and her coauthor reach a stark conclusion.
“The current buildout will be the largest misallocation of capital in history.”
— Jessica Wachter, Wharton finance professor,
Alphabet posted a $5.9 billion free cash flow deficit last quarter, its first since going public in 2004. Investors increasingly view AI spending risks markets as the concentration grows.
Debt Spreads the Risk Beyond Big Tech
Morgan Stanley calculates hyperscalers will finance over half of their planned $2.9 trillion in data center spending through 2028. That money increasingly comes from external capital instead of cash reserves.
In Louisiana, Meta transferred an 80% stake in its Hyperion data center to private-credit firm Blue Owl Capital. The arrangement shows how complex hyperscaler financing has become.
Columbia Business School’s Stijn Van Nieuwerburgh warns that debt like this increasingly flows through pension funds and private credit vehicles. He says few people realize how deeply that exposure has spread into their own retirement and insurance savings.
Crypto strategist Arthur Hayes has floated a related scenario. He argues an AI credit bust could force the Federal Reserve to print money, pushing bitcoin (BTC) toward $1 million.
“A parlay bet by the capital markets and the economy.”
— Gary Gensler, former SEC chair and MIT Sloan School professor,
Gensler expects a retrenchment eventually, though its timing remains uncertain. Whether it arrives gradually or abruptly may determine how much of that trillion-dollar bet becomes a lasting loss.
The post MIT Explains What Happens When the Trillion-Dollar AI Bubble Bursts appeared first on BeInCrypto.
