# Goldman Sachs projects AI infrastructure spending to hit $1.6T by 2031 > Source: > Published: 2026-08-20 14:48:44+00:00 Via en.wikipedia.org # Goldman Sachs projects AI infrastructure spending to hit $1.6T by 2031 The bank's latest report forecasts $7.6 trillion in cumulative AI capital expenditure over six years, with compute hardware eating two-thirds of the total 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. The compute number carries an important asterisk. Goldman assumes NVIDIA will capture 75% of that market. If that estimate holds, Jensen Huang’s company would be on the receiving end of roughly $3.8 trillion in revenue over the forecast window. ## The hyperscaler arms race The four largest cloud companies, Meta, Microsoft, Amazon, and Alphabet, are expected to collectively spend around $5.3 trillion in capital expenditure from fiscal years 2025 through 2030. Goldman notes that this figure alone surpasses the GDP of Japan, which has the fourth-largest economy in the world. Global AI-related investment, including private companies and non-US spending, is estimated to exceed $1 trillion for 2026 alone. ## The bottleneck nobody wants to talk about Goldman’s analysts flagged two risks that could complicate this spending trajectory. The first is power. The $358 billion earmarked for power infrastructure might sound like a lot, but it represents less than 5% of the total AI capex forecast. The second risk is more fundamental: whether these investments will generate justified returns in the near term. The AI infrastructure buildout is, at its core, a bet that demand for AI services will scale proportionally with the supply of compute. **Disclosure:** This article was edited by Editorial Team. For more information on how we create and review content, see our [Editorial Policy](https://cryptobriefing.com/editorial-policy/).