Where Data Tells the Story
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The world is projected to spend $7.6 trillion building the infrastructure that powers artificial intelligence (AI).
The visual above shows the baseline aggregate AI capital expenditure
It comes from the estimate prepared by Goldman Sachs Global Institute and Goldman Sachs Global Investment Research as of March 3, 2026.
The projection covers six years (2026 through 2031) across three categories: compute (chips and processors), data centers (the physical buildings and cooling systems), and power (energy infrastructure).
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Compute is the dominant category by a significant margin. It gets $494 billion in 2026, rising to $1,127 billion in 2031.
Across the full six-year projection, compute totals approximately $5.1 trillion of the $7.6 trillion aggregate.
Data centers account for approximately $2.1 trillion. Power accounts for approximately $358 billion.
The Goldman Sachs model’s most specific assumption sits inside the compute category.
NVIDIA is assumed to account for 75% of total compute spend in each year of the projection. At 75% of $5.1 trillion, NVIDIA’s implied AI-specific revenue over six years is approximately $3.8 trillion.
The $7.6 trillion global AI infrastructure projection is simultaneously a single-company revenue forecast.
The model uses NVIDIA’s VR200 Rubin chip as the baseline specification ($80,500 per GPU, including node costs, 3,000 watts per package) as the price basis across all years.