Inside The Trillions Being Spent On The AI Data Center Buildout

Despite fears of rogue AI agents and increasing political pushback by local communities and politicians, the U.S. is plowing ahead on a data center construction frenzy that’s unprecedented in its scale.

Depending on who you ask, estimates of the total cost of the buildout range from $2.8 trillion by 2030 to $10.3 trillion by 2032 in the U.S. alone. Those figures could even be conservative, with giants OpenAI and Anthropic revealing more about their spending plans as they prepare to go public in the coming months: A leaked copy of Anthropic’s prospectus revealed the firm expects to spend $518 billion on AI infrastructure over the next decade.

Yet we’re still in the early innings of what could become a new industrial revolution. According to economists at Goldman Sachs, U.S. investment on AI will rise from 1.8% of GDP this year to 2.8% in 2028. That’s roughly the same share of the economy as the federal defense budget.

The railroad boom represented about 2.4% of America’s GDP between 1880 and 1890. If AI spending reaches the 2.8% of GDP predicted by Goldman Sachs, it will outstrip the railroad boom in its economic footprint by next year—and that could be a conservative estimate. A recent study from Columbia University economist Stijn van Nieuwerburgh puts that even higher, at 3.6% of GDP by 2032.

The advent of railroads in the 1800s ushered in the Gilded Age, elevating the era’s industrial barons to unimaginable levels of wealth. When Forbes published its first-ever ranking of the country’s richest people in 1918, five of the 30 richest made their money in railroads. Another seven, including John D. Rockefeller and Andrew Carnegie, provided the oil and steel to build the rails and keep the trains moving.