In today’s Cloud Wars AI Minute, I break down Gartner’s $2.59 trillion AI infrastructure spending figure and why rising compute and memory costs are shifting where the economics of the AI boom are landing.
Highlights
00:11 — Let’s talk about this new Gartner number that just came out. Gartner is claiming that it’s $2.59 trillion in 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 cash flow not being able to keep up.
01:02 — If we take a look at Nvidia for a second, that is going to be running a lot of this compute on its 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 percent 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.
01:36 — 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. This is where all revenue seems to be going right now.
02:15 — 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.
03:22 — 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 both compute and memory infrastructure, allowing this to normalize a bit.
Dewain Robinson
Principal Copilot Solution Architect
Microsoft
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