Goldman Sachs just put a price tag on the AI buildout, and it reads like a defense budget. The bank’s May 2026 report, titled “Tracking Trillions,” estimates that annual AI-related capital expenditure will climb from $765 billion this year to $1.64 trillion by 2031.
Add it all up and the cumulative tab comes to $7.6 trillion over six years. For perspective, that figure exceeds the GDP of every country on earth except the US and China.
Where the money goes
Goldman’s breakdown splits the spending into three buckets: compute, data centers, and power. Compute infrastructure, meaning the chips and servers that actually run AI workloads, is projected to absorb roughly $5.1 trillion of the total. That’s about two-thirds of every dollar spent.
Data centers, the physical buildings that house all that silicon, are expected to attract $2.1 trillion in investment. Power infrastructure, the grids and generation capacity needed to keep the lights on inside those buildings, rounds out the picture at $358 billion.
