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Big Technology Podcast · 3 min · Oct 9, 2026

AI-related U.S. capex could approach $2 trillion next year

Dylan Patel estimates U.S. capex tied to AI's full supply chain could approach $2 trillion next year, or 5–6% of GDP. He says U.S. data centers also serve overseas inference demand.

Dylan Patel

Founder & CEO, SemiAnalysis

Founded SemiAnalysis in 2020, a research firm tracking the chip supply chain and AI infrastructure buildout.

  • Alex Kantrowitz, Host · Founder, Big Technology

    Former BuzzFeed News senior tech reporter and author of Always Day One.

About this segment

Dylan Patel estimates U.S. capex tied to AI's full supply chain could approach $2 trillion next year, or 5–6% of GDP. He says U.S. data centers also serve overseas inference demand.

From “Can AI Keep Growing Exponentially? Let’s Ask SemiAnalysis — With Dylan Patel and Jordan Nanos”, Oct 9, 2026. Watch the full episode

Answers “What will AI look like in the next few years?” See all 35 answers

“if you look at, like, next year, CapEx across the U.S. will be on the order of $2 trillion”
Dylan Patelat 1:53 · Big Technology Podcast1:53

Takeaways

  1. His estimate includes more than data centers and chips.
  2. He puts the investment at roughly 5–6% of U.S. GDP.
  3. U.S. capacity also serves inference demand from other countries.

In this episode

Full episode
  1. 9:12AI revenue may justify infrastructure spending sooner than expected5:17
  2. 20:45Neocloud contracts differ from hyperscalers’ self-build plans3:39
  3. 39:34A neocloud security gap exposed other customers’ workloads3:41
  4. 29:20Anthropic pairs high inference margins with low acquisition costs3:39
  5. 14:36AI could shift value to capital without shrinking labor income4:15
  6. 54:52Frontier labs are holding back models before public release4:03
  7. 43:50Oracle's fixed-price deals limit its upside when GPU prices rise4:59

  8. 0:49AI-related U.S. capex could approach $2 trillion next year2:55

Up next · Latent SpaceCompute contracts must price interruptions and hardware differences4:49

Transcript

Transcribed by machine (Whisper) from the episode’s audio, so a word may be off here and there.

  1. 0:54

    we're seeing in this AI infrastructure build out if we can Dylan there's like a chart going around X right now that compares the AI infrastructure build out to previous build outs in the past like railroads like highways and the chart is showing that the percent of GDP for the AI build out today is about 3.6 percent, oh sorry, the median is about 3.6 percent the average year compared to 2.2 percent for the railroads. And basically the commentary is that this is far bigger, right, that would put it basically 50 percent bigger than railroads even in terms of its share of GDP. And the commentary is this is bigger than anything we've ever seen before on a scale that is, you know, effectively unprecedented. I'd love to hear your perspective on just how big this is, whether that's the right way to look at it, and then what it means if we're building out something this big.

  2. 1:47

    Yeah, I mean, the first thing when that chart was going around, I was like, well, people's numbers are too low. It's actually much higher than that already. Really? Okay, so share the real numbers. Yeah, yeah. So, like, I mean, if you look at, like, next year, CapEx across the U.S. will be on the order of $2 trillion, not just data centers and chips, but also all the rest of the supply chain that people are investing in.

  3. 2:11

    So you're close to $2 trillion of CapEx. um and then you stack on top of that uh gp is like close to 30 30 and some change trillion so you're at like you know five or six percent right not not three percent or two percent um so so sort of my thought process is actually like oh wow these numbers are lower than the actual because people are understating the amount and size of capex that's happening in the u.s And I think like part of this is because, you know, with railroads, your capex is in the country that you're deploying it in. With fiber, your capex is in the country you're deploying it in. But for AI infrastructure, your capex in America is actually a lot of it's being used to serve.

  4. 2:57

    outside of America uses, right? So if you look at, for example, Europe, most of Europe's inference for Anthropic is in America. And most of OpenAI's inference in Europe is in America. And similarly, if you look at a lot of Asian countries, and so there is a bit of this, like, this, you know, CapEx in America is actually like much higher as a result because one, you're doing all the training here, and then two, you're actually serving other countries from data centers in America.

  5. 3:26

    And so ultimately, you're sort of at this stage where capacity is much, the economic impact of it is much larger than any other sort of physical infrastructure investment cycle ever before.