Evans argues there's a hard financial ceiling on AI infrastructure spending — companies already devoting over 50% of revenue to capex can't sustain much higher growth, since the money simply doesn't exist at that scale. ✦ AI generated
Benedict Evans · a16z Podcast · 2026-06-08 · original ↗
starts at this moment · 49:26
“Various people including you know uh CEO of Google said that the risk of underinvesting is riskier than overinvesting. Is there any level of capex where that stops being true and are we getting there now?”
Clearly, like those companies could not spend 1.5 trillion next year or if they did, they'd have to borrow it and they certainly couldn't sustain that level of spending um for any length of time. Um, and so there's a certain point at which like that growth has to slow down because like there isn't any more money.
verbatim transcript · starts at 49:26
49:26did, they'd have to borrow it and they certainly couldn't sustain that level of spending um for any length of time. Um, and so there's a certain point at which like that growth has to slow down because like there isn't any more money. Um now clearly you can talk about ROI and your ability to produce returns from that investment. Um and you know clearly the capital markets are willing to fund
49:52that up to a point but like pick a number at random like we can't spend $10 trillion a year on inf AI infrastructure because there isn't $10 trillion a year there to spend on it. So there's a finite there are kind of like laws of physics caps on the amount of money um that's available. I'd hesitate to say something more tangible than that at the moment. I mean, I kind of almost go back
50:16to what I said at the beginning that like we've got a bunch we've got a bunch of multiples. So, um there's far more demand than supply. On the other hand, the efficiency is increasing massively. Um we don't know what the next model will be. We don't know where edge or open source come in yet, when edge and open source come in yet. And meanwhile, [snorts] you're always chasing the next
50:36model. And so this is kind of the line that runs across all of it is is the model is only relevant for 3 to six months, six to nine months, whatever you want to say. And the model costs how many billion dollars. Um, and how much infrastructure do you need to do that? Um, I don't think that mass is really shaken out yet. I mean, obviously you
50:53can, you know, there's a bunch of very clever semiconductor analysts who spend lots of time trying to put [snorts] numbers on this. It is kind of like trying to put numbers on bandwidth, internet bandwidths in the late 90s. like you kind of know what the rows in the spreadsheet are, but you don't really know where the values are. All you can really say is, well, look, it
51:09can't be you. There's there's clearly physical limits on this. Um I think you know another way to answer the question is like if you're Google or Meta or Microsoft um to [snorts] some extent Amazon some extent Apple this is sort of an existential problem and you have a sort of you know a FOMO problem in that um so on the one hand your returns on the investment at the moment are hugely