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Goldman Sachs chief executive David Solomon cited estimates that US data-centre construction could require more than $10tn by 2032, according to Coinpaper. That would amount to about 3.6% of annual US GDP, giving a sense of the scale behind the AI computing build-out.
Why it mattersSolomon also pointed to rising borrowing needs and financing costs as risks to project returns. Goldman Sachs research separately estimated AI infrastructure investment could reach $8tn over four to five years; Coinpaper cautions that these projections cover overlapping categories and periods, so they should not be added together. For AI, the bottleneck is not only getting enough chips and electricity. Someone must finance the buildings and equipment, and then make the numbers work.
Discuss: Should the AI infrastructure boom rely more on debt, or should investors demand clearer evidence of returns first?
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