A popular finance podcaster is pointing to a structural risk inside the AI boom that echoes the forces behind the 2008 financial crisis.
In a new post on X, Bloomberg Markets executive editor Tracy Alloway shares her commentary on today’s AI capital expenditure (CapEx) race and Wall Street legend Jeff Saut’s pre-crisis research on the US housing market.
Alloway says back then, Saut noted that housing had become so large and so central that it began driving economic stress rather than reacting to it.
“But in September 2007, Saut noticed the causal direction was changing: the enormous size of the US property market and its supercharged importance to the wider economy meant that housing itself became the driver of macroeconomic problems.
Instead of reacting to economic stress, the housing sector was starting to cause it.
Cause and effect had flipped.”
Alloway emphasizes that AI is now a powerful force driving the US economy.
“AI is now affecting property values, the labor market (with the net impact still argued), electricity prices, manufacturing, and household wealth. JPMorgan estimates that about 44% of the S&P 500’s value now comes from the 30 biggest AI-focused companies, and the sector has made Americans about $5 trillion richer in 2025. If AI’s market value suddenly falls, so, presumably, does consumer spending.”
Looking closely at the AI buildout, Alloway says hyperscalers still have the money to fund the AI buildout. But she warns that the massive scale of the endeavor means that the tech giants might need to tap financial markets to get more funding.
“The scale is staggering. [A] Center for Public Enterprise report… estimates that Meta, Microsoft, and Amazon are expected to pour more than $350 billion into AI infrastructure this year alone, with even larger outlays expected in the coming years.”
While banks, private credit and other financing avenues welcome the chance to fund the buildout, Alloway says the situation could change if hyperscalers fail to deliver profits. She again references Saut’s 2007 note, which described a collateral crunch as the abrupt collapse of assets underpinning the loans.
“But one day the ability to monetize all this spending and transform CapEx into revenue is actually going to matter. If those profits don’t materialize — if consumers switch to cheaper Chinese alternatives, if the value of GPUs falls — the sector could face a collateral crunch.”
Alloway warns that a collateral crunch could spark a credit crunch as financiers back away from the AI sector – a dynamic that could trigger an economic crisis similar to the one witnessed in 2008.
“The danger is that a collateral crunch becomes a credit crunch and the entire AI-finance-economy flywheel comes to a screeching halt.”
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