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Why AI Funding Is So Price-Insensitive

4m 36s

Why AI Funding Is So Price-Insensitive

The podcast discusses the concept of price inelasticity in the context of the massive AI infrastructure build-out. Andrew Sheetz explains that demand for AI-related investments remains strong despite sharp price increases for essential components—copper up 40%, gas turbines up 50%, and memory up 150-300% in the past year. Major US tech companies are projected to spend $800 billion on AI in 2025, nearly double 2024, with estimates reaching $1.1 trillion by 2027. This spending is driven by the view that AI is the most important technology in a decade, with companies possessing the financial resources and patience to invest regardless of cost. The inelastic nature of this investment has both positive and negative implications. On the positive side, it signals real commitment to AI, supporting US economic growth and stock market earnings, as noted by Morgan Stanley’s equity strategy team. However, risks include potential inflation from persistent demand driving prices higher, at a time when core inflation already exceeds the Fed’s target. Additionally, if AI companies are insensitive to borrowing costs, other firms may face wider credit spreads. The podcast concludes that this unique price insensitivity makes AI investment a key market driver, but one with significant economic trade-offs.

Transcription

727 Words, 4206 Characters

English
Welcome to Thoughts on the Market. I'm Andrew Sheetz, global head of fixed income research at Morgan Stanley. Today, a uniquely price-insensitive development. It's Monday, May 11th at 2pm in London. Eelasticity 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 "inny-delastic" that 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 data centers is at the center of many market conversations. It's supporting US 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 US 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 will up about 40% in the last year, a gas turbine to power it up 50%. The memory to run it, it's up 150% to 300% over the last year alone. And yet despite these extremely large price increases, the demand to build an AI has been accelerating, our forecast 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 this 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 seek 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. Rebus 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 costs right 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 the market useful, let us know by leaving a review wherever you listen, and tell a friend or colleague about us today. The preceding content is informational only and based on information available when created. It is not an offer or solicitation, nor is it tax or legal advice. It does not consider your financial circumstances and objectives and may not be suitable for you.

Podcast Summary

Key Points:

  1. AI infrastructure investment is highly price-inelastic, meaning demand persists despite significant cost increases.
  2. Major US tech companies are projected to spend $800 billion on AI in 2025, nearly double 2024, with spending expected to reach $1.1 trillion by 202
  3. Key components like copper, gas turbines, and memory have seen price surges of 40% to 300% over the past year, yet AI build-out continues to accelerate.
  4. This inelasticity extends to financing, as companies issue debt at record pace despite rising borrowing costs.
  5. The positive side

Summary:

The podcast discusses the concept of price inelasticity in the context of the massive AI infrastructure build-out. Andrew Sheetz explains that demand for AI-related investments remains strong despite sharp price increases for essential components—copper up 40%, gas turbines up 50%, and memory up 150-300% in the past year. 1 trillion by 2027.

This spending is driven by the view that AI is the most important technology in a decade, with companies possessing the financial resources and patience to invest regardless of cost. The inelastic nature of this investment has both positive and negative implications. On the positive side, it signals real commitment to AI, supporting US economic growth and stock market earnings, as noted by Morgan Stanley’s equity strategy team.

However, risks include potential inflation from persistent demand driving prices higher, at a time when core inflation already exceeds the Fed’s target. Additionally, if AI companies are insensitive to borrowing costs, other firms may face wider credit spreads. The podcast concludes that this unique price insensitivity makes AI investment a key market driver, but one with significant economic trade-offs.

FAQs

Price inelasticity is when demand for an item holds up even as its price increases significantly, such as for essential goods like electricity or highly desired items like concert tickets.

Morgan Stanley estimates about $800 billion of investment by large US technology companies this year, almost double their spending last year and triple their spending in 2024.

Copper for data centers is up about 40%, gas turbines up 50%, and memory up 150% to 300% over the last year alone.

AI is seen as the most important technology in a decade, and companies have financial resources and patience to invest despite rising costs, viewing it as a critical opportunity.

It shows real commitment to the technology, supports overall growth and earnings, and spending won't easily be shaken by outside events.

Risks include potential inflation from rising prices, uncertain returns on historic investment, and wider borrowing costs for other companies.

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