AI capital expenditure forecast to exceed the cost of building railways in both the U.S. and the U.K.

AI capital expenditure forecast to exceed the cost of building railways in both the U.S. and the U.K. — with the internet added on top PwC expects global data center capital expenditure to reach $31.6 trillion between 2026 and 2050 PwC forecasts spending on artificial intelligence to reach almost $32 trillion in 24 years as technology companies race to increase the build-out of AI. The Big Four firm’s outlook on global data centers from 2026 to 2050 is for capital expenditure to surge to $31.6 trillion in that period, with a potential upside of $50 trillion if the rate of AI adoption speeds up. The data is based on information from advisory firm Oxford Economics, which modeled data center capex in 36 countries and territories and five regions. According to the report, unlike the development of railways or the internet, the infrastructure of AI stands out because its building cycle resets every four to six years. The expected spending figures on AI are larger than the combined figures for the expansion of railways in the U.S. and the U.K. and the cost of building the internet, even when adjusted for inflation, per PwC. The report noted that what also distinguishes this spending cycle from other similar ones is that its due to increase over time, with the firm expecting capex to grow from $800 billion this year to $1.1 trillion in 2030 and $1.8 trillion in 2050. Don’t Short Yourself Free Weekly Newsletter Don’t Short Yourself offers weekly money tips to help you earn it, stack it and grow it. “That’s because the bulk of the spend doesn’t go towards the buildings,” the report said. “Rather, it funds what fills them: servers, storage systems, networking equipment, central processing units (CPUs), and, crucially, the graphics processing units (GPUs) that provide compute power for AI —which age out in a handful of years and will need to be replaced.” PwC’s $31.6 trillion prediction sits within a range of $22 trillion and $50 trillion, where the actual outcome will be based on the acceleration and rate of AI adoption. But across scenarios, the firm sees capex rising considerably by 2050. Goldman Sachs has boosted its forecasts for hyperscaler-spending on AI from $1.2 trillion to $1.7 trillion for 2027 and from $1.5 trillion to $2.1 trillion for 2029. “That’s a significant increase over a multi-year period in hyperscaler expected spending,” Brian Singer, analyst at Goldman’s research arm, said in a recent episode of the investment bank’s Exchanges podcast. It also raised its targets for data center power demand, with 2030’s expected figure of 83 gigawatts lifted to 108 gigawatts. Singer said that the jumps in demand for AI and spending on the the buildout of the tech were “hard to ignore.” The AI trade has powered U.S. equities this year, with the S&P 500 rising 12% and a leading index of semiconductor stocks up 59%.