Why AI Funding Is So Price-Insensitive

Our Global Head of Fixed Income Research Andrew Sheets explains the economic theory behind the unwavering spending on AI infrastructure.

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Andrew Sheets: Welcome to Thoughts on the Market. I'm Andrew Sheets, Global Head of Fixed Income Research at Morgan Stanley.

Today, a uniquely price insensitive development.

It's Monday, May 11th at 2pm in London.

Elasticity is one of the first concepts that they teach in economics, and for good reason.

It's the idea that our sensitivity to the price of something differs from item to item. If the price of pizza goes up, for example, you may decide to go out for burgers. But if the price for something essential, like electricity, or deeply desired, like tickets to see your favorite artist perform; well, if those go up a lot, you're probably going to complain, but also end up paying anyway.

This latter category is what we would call inelastic. The demand for these items holds up even as the price increases, and maybe if the price increases quite a bit. And that is becoming very relevant as we all debate the AI build-out.

It's not an exaggeration that the investment in AI, chips, power, and datacenters is at the center of many market conversations. It's supporting U.S. growth despite a sharp slowdown in job creation. It's supporting stock market earnings, even as uncertainty over the Iran conflict continues to percolate.

Part of this importance is just the sheer size of this build-out. We estimate about $800 billion of investment by large U.S. technology companies this year, almost double their spending last year and triple their spending in 2024. But it's not just the size, it's the idea that this investment may happen almost whatever the cost.

Specifically, we're looking at a desire by multiple large companies to build out large AI infrastructure all at the same time, and that's increased the price of these components. The copper needed to wire together that data center? Well, it's up about 40 percent in the last year. A gas turbine to power it? Up 50 percent. The memory to run it? It's up 150 to 300 percent over the last year alone. And yet, despite these extremely large price increases, the demand to build in AI has been accelerating.

Our forecasts for 2026 spending have been consistently revised higher. And that $800 billion that we think is spent this year is set to be dwarfed by $1.1 trillion of estimated spending in 2027, based on the view of my Morgan Stanley colleagues.

This idea of inelasticity or price insensitivity extends even to the costs of financing the spending. Debt costs for these companies have increased this year, and yet they continue to issue at a record pace.

A quick aside as to why all this spending may be price insensitive or inelastic. AI is seen by these companies as, without exaggeration, maybe the most important technology in a decade. These companies have financial resources and the patience to wait it out, and they see gains to those who can figure out AI technology, even if the winner is not yet clear.

The inelastic nature of the AI theme is a classic good news, bad news story. To the positive, it suggests real commitment to this technology and that spending won't easily be shaken by outside events. That should help buttress overall growth and should also support earnings this year – a core view of Mike Wilson and our U.S. equity strategy team.

But there are also risks. It remains to be seen what returns can be generated from all of this historic investment. Robust demand for items, even as their price goes up, may cause those prices to increase even further. That's inflation happening at a time when core inflation measures are already well above the Federal Reserve's target. And if companies are less sensitive to the cost of their borrowing to fund AI, well, other companies could find their cost dragged wider in sympathy.

We continue to expect record supply and modest widening in the U.S. corporate bond market.

Thank you, as always, for your time. If you find Thoughts on the Market useful, let us know by leaving a review wherever you listen. And tell a friend or colleague about us today.