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Research projects AI hyperscalers need 2.7x productivity gain by 2030 to justify $1.1T infrastructure spending through 2027

New research from Jessica and Jonathan Wachter, cited by MIT Technology Review, indicates AI hyperscalers must increase productivity 2.7 times by 2030 to justify nearly $1.1 trillion in infrastructure spending through 2027, based on spending by Alphabet, Microsoft, Amazon, Meta, and Oracle. The analysis factors in capital costs, depreciation, and a 15% return threshold. Morgan Stanley estimates…

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Key points

  • Wachter research: AI hyperscalers need 2.7x productivity gain by 2030 to justify $1.1T infrastructure spending through 2027.
  • Morgan Stanley: $2.9T global data-center spending 2025–2028, $1.5T from external capital.
  • Brookings: U.S. AI spending to reach $10.3T between 2025 and 2032, averaging 3.6% of GDP per year.
Full story from yellow.com · by Alexey Bondarev · via Reddit AI communitiesOpen source ↗

AI hyperscalers may need to raise productivity 2.7 times by 2030 to justify nearly $1.1 trillion in infrastructure spending through 2027, according to new research.

yellow.com · 24 September 2026

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This text was published by yellow.com and written by Alexey Bondarev. It is reproduced here with attribution so you can read it in full; the rights remain with the publisher. Read it at the source ↗

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