AI Infrastructure Spending Hits $2.59 Trillion as Hardware Costs Reshape the Market

Dewayne Robinson (0:00)

Welcome to the Cloud Wars AI Minute. I'm Dewayne Robinson, your host, and we talk about all the key things that your boss expects you to know about what's happening in the AI industry. And let's talk about this new Gartner number that just came out. The Gartner is claiming that it's a $2.59 trillion CapEx expenditures that we're starting to see companies investing in the AI infrastructure space. Well, this is a very big number. And in an earlier video, I covered the fact that now we're starting to see cashflow not being able to keep up. But there's another interesting component of this that we might want to think about. And that is that when we take a look at this across the board, and we start seeing these revised numbers coming out from Gartner, it starts to open up a very interesting conversation. Because if we take a look at Nvidia for a second, who is going to be running a lot of this compute on their hardware, you're going to see that they're at $89 billion in one quarter. Now, that's their revenue in just one quarter alone, and that's up 117% year over year.

This means that they're demanding prices and they're manufacturing this in a market that the demand is far exceeding their ability to actually produce equipment. And you're also seeing 400% DRAM prices going up since the start of 2024

And so when you combine these two different pieces together, what we're seeing is that the revenue is really being made by the hardware manufacturers and the ability to do the compute. So this is where all revenue seems to be going right now. So the actual model makers and the providers and the hosters aren't the real ones making the money. It's actually coming all the way back down to the ability to actually produce and be able to generate compute. Now, with that, it really starts that Gartner has even predicted that in 2026, we're going to see the trough of disillusionment happen in the AI space. Now, what this really means is that we're going to see the hype cycle bring it down a bit to be able to go into what is the actual reality of AI return on investment. And so, we should start seeing this hype cycle come down because the people who are really pushing this, these big vendors like Amazon and Google and Microsoft, are going to be pushing back on the pricing of this hardware. They're going to have to, or they're going to have to deal with either borrowing money to be able to deal with the cash flow problem, to be able to pay for these exorbitant prices for both memory and compute. So that they can continue to be able to make revenue, because either we're going to borrow the money, or we're going to deal with deal margin, or we're going to have margin within our cogs. And so this is going to be a very interesting thing for us to continue to watch throughout 2026

And it should open up some opportunity and hopefully maybe help us reduce the demand that we have on this both compute and memory infrastructure, allowing this to normalize a bit.