AI spending expected to top $1 trillion in 2 years. That estimate's way too low if Jensen Huang's right
Nvidia CEO Jensen Huang introduces Vera Rubin, a next-generation AI data center platform, and Rubin Ultra, a next-generation AI GPU architecture, during the keynote address
Nvidia CEO Jensen Huang introduces Vera Rubin, a next-generation AI data center platform, and Rubin Ultra, a next-generation AI GPU architecture, during the keynote address at the company's annual GTC developers conference in San Jose, California, on March 16, 2026. Nvidia CEO Jensen Huang is way ahead of estimates on the amount of spending that's coming for AI – even the most optimistic ones. During Wednesday evening's earnings call, Huang said he thought AI capital expenditures could get up to $4 trillion.
"The capex is at a trillion dollars, and it's growing toward the three to four [trillion-dollar mark]," he said, speaking only of capex for hyperscalers like Alphabet and Amazon, which excludes other segments of the supercomputing market such as neoclouds. Nvidia's chief financial officer Colette Kress was even more specific on the call. "With analysts now forecasting hyperscale capex to exceed $1 trillion in 2027 and agentic AI beginning to proliferate [across] all industries, AI infrastructure spending is on track to reach $3 to $4 trillion annually by the end of this decade," she said.
There's just one thing: That's way ahead of Wall Street's estimate trajectories. One analysis by Laura Martin at Needham shows the consensus estimate of hyperscaler capex hitting $1.03 trillion in 2028 – a third to a quarter of what it will be just two years later, if Huang's prediction is correct. "If Jensen Huang's prediction is correct … then the consensus estimates included in the chart below will be revised upwards, we believe," she wrote on Thursday with her colleague Dan Medina.
"[His] vision for the hyperscalers is different from what the hyperscalers are saying on their earnings calls, and more interesting."
The BriefWire