Goldman Sachs projects AI capital expenditures to reach $1.2T by 2027

Goldman Sachs has ratcheted up its forecast for how much America’s biggest tech companies will spend building out AI infrastructure, projecting US hyperscaler capital expenditures could climb as high as $1.4 trillion by 2027. That figure blows past the bank’s own prior estimates of roughly $1.1 trillion and dwarfs a broader Wall Street consensus that had been hovering closer to $920 billion. The numbers behind the ramp Goldman’s updated trajectory sketches out a steep climb. The bank previously estimated hyperscaler AI capex at roughly $405 billion in 2025, rising to approximately $750 billion in 2026, before hitting the $1.2 trillion range in 2027. The latest revision pushes that 2027 figure even higher. The companies driving this wave are the usual suspects: Microsoft, Amazon, Alphabet, Meta, and Oracle, with OpenAI also drawing notable investment activity. These firms are collectively transitioning from what Goldman characterizes as an experimental phase of AI deployment into full-scale commercial implementation. Looking further out, the bank estimates cumulative AI infrastructure spending could reach approximately $7.6 trillion from 2026 through 2031. That breaks down into roug...