AI Exchanges: Power Problems?

Welcome to Goldman Sachs Exchanges. I'm Alison Nathan, and I'm here with George Lee, co head of the Goldman Sachs Global Institute. Together, we're cohosting a series of episodes exploring the rise of AI and everything it could mean for companies, investors, and economies. George, great to see you again.

Good to be back. I we had a little bit of a hiatus here while I was recovering from knee surgery, but fortunately, not much happened in the world of AI over the past few months. I'm kidding, of course. Has been a cavalcade of extraordinary events. So and be really fun to talk to our guest about what's shaping the movement right now.

Yes. Well, great to have you back, George. And today, we are going to take a closer look at an area that we've touched on before in our conversations, you and I, but really deserve a closer look. And that is the resources that the AI build out could require. We are joined here by Brian Singer, head of GSASD and Goldman Sachs Research.

Thank you for having me, Alison. Thank you, George. Glad to have you here, Brian. Great to be with you all.

And Brian, just to kick off the conversation, we've been talking about the tremendous amount of power that data centers will require for a while now. But the amount of spending on these data centers have just continued to grow and grow and grow. Think that was a key feature of the last few months when we think about the AI space. So first, put some numbers on those developments and what it could mean for power demand.

Sure. I mean, we have seen the hyperscalers' capital budgets and r and d budgets in 2026 and 2027 combined increase by more than $300,000,000,000 And I'm sure we can get into the debate whether there's going to be a second derivative inflection coming for slower growth going forward, but you're growing off of an upwardly revised budget of $300,000,000,000 plus, and that is going to trickle down into power and a whole host of other uses. And so we've been focused on where will that money go and what are the investment opportunities for the enablers?

And some of your work, Brian, I noticed, all of that spend, and there's obviously a lag effect, but you calculate that we remain in deeply supply demand imbalanced state. Right? Maybe you could talk a little bit about where we stand there.

Yeah. That's right. I mean, Alison, you and I go back to the shale revolution. Yeah. And arguably before as well, unfortunately or fortunately. And that was a very similar time period where we saw a massive increase in capital spending followed by a cyclical downturn. And what drove the shift then from the appraisal hopes and dreams phase into the execution phase were three factors. One, the product became oversupplied. Two, your innovators saw their return on capital erode. And third, the innovators ran out of financial flexibility. You're asking about really the first of those here, which is

Yeah. Well, my perspective is that demand growth will continue to surprise us. And contributing to that, and you observed in your research report, is that there's more demand from enterprises for fundamental sources of of token flow. Second, if you just observe the way that these agentic systems work, they are furnaces for tokens. And so you have the, you know, straightforward demand of consumers performing inference on chatbots, but what I see really opening up and what I think we'll see will ultimately swamp the amount of human AI traffic is agentic machine to machine traffic. So I think tha