AI Needs a 2.7x Productivity Jump by 2030 to Justify $1.1T Buildout, Wharton Research Says
Post-reality · reddit · 2026-09-24
MIT Technology Review covers research by Wharton finance professor Jessica Wachter and Jonathan Wachter: after accounting for capital costs, depreciation and a 15% return requirement, AI hyperscalers need a 2.7-fold productivity gain by 2030 to justify nearly $1.1 trillion in infrastructure spending through 2027, based on outlays by Alphabet, Microsoft, Amazon, Meta and Oracle.
- Morgan Stanley estimates $2.9 trillion in global data-center spending through 2028, with $1.5 trillion requiring external capital
- Growing reliance on debt and private credit could spread AI infrastructure risk beyond Big Tech
- The paper warns a failed boom could become "the largest misallocation of capital in history"
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