What must happen for AI’s trillion-dollar gamble to pay off

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A financial analysis shows that hyperscalers must increase productivity by 2.7x by 2030 to justify their $1.1 trillion AI infrastructure spending, requiring sustained revenues of roughly $3.7 trillion by 2032 and broad economic productivity gains. The massive data center investments, increasingly financed through complex debt structures distributed across the financial system, create systemic risks comparable to pre-2008 financial engineering if anticipated productivity gains fail to materialize.


Source: MIT Technology Review

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