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Market & Investment

How much are hyperscalers spending on AI in 2026?

By AI Statistics Center Editorial TeamLast updated: Reviewed against primary sources

Short Answer

Wall Street consensus for 2026 hyperscaler AI capital spending is $527 billion, with total global data-centre construction projected at $2.9 trillion through 2028 (Goldman Sachs, Morgan Stanley, 2026).

Key Facts

  • $527B — consensus estimate for 2026 hyperscaler AI capex (Goldman Sachs Research, 2026).
  • $2.9T — in global data center construction projected through 2028 (Morgan Stanley Research, 2026).
  • $500B — in AI-related spending projected for 2026 (UBP Investment Outlook 2026, 2026).
$527B

consensus estimate for 2026 hyperscaler AI capex

Wall Street consensus for 2026 hyperscaler capital spending is now $527 billion, up from $465 billion at the start of Q3 2025 earnings season, continuing a trend of upward revisions.

Who are the biggest AI spenders?

Capital expenditure from Microsoft, Alphabet, Amazon, and Meta is expected to rise by more than 34% again in 2026 to about $500 billion combined. Microsoft and Amazon lead on absolute dollars; Meta leads on percentage growth; Alphabet leads on return-on-ad-spend from AI.

How much of US GDP is AI investment?

Morgan Stanley estimates AI-related investment now accounts for around 25% of US GDP growth. The multiplier effect — construction, power, cooling, logistics, chips — is why the AI buildout is being compared to railroads and electrification rather than to prior software cycles.

Is the data-centre buildout near its peak?

No. More than 80% of the projected $2.9 trillion in data-centre construction through 2028 is still ahead — a multi-year industrial buildout, not a speculative tech cycle. Power availability and grid interconnect, not chip supply, is now the binding constraint.

Supporting Data

Recommended Citation

AI Statistics Center, citing Goldman Sachs Research (2026). https://aistatisticscenter.com/answers/how-much-are-hyperscalers-spending-on-ai

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Last reviewed and updated: by the AI Statistics Center Editorial Team. All statistics are sourced from primary research publications and linked directly to their origin.