In short
Whether elevated AI-related capital expenditures (CapEx) signal overbuilding and potential credit-market stress for investors.
Guests
No guests mentioned; the host is Andrew Sheets, Head of Corporate Credit Research at Morgan Stanley.
Key claims
AI CapEx is expected to be one of the largest investment cycles of the generation; most spending is still ramping up; AI is viewed as the most important next-decade technology by highly profitable companies, increasing willingness to invest despite uncertainty; unlike prior cycles (internet late 1990s, shale mid-2010s), today’s spend is backed by strong balance sheets and debt capacity; prior credit problems often came from overcapacity built ahead of demand, which the episode says is not yet evident.
Notable examples
Railroads, electrification, the internet (late 1990s), shale oil (mid-2010s), and data centers.
Written by AI. May contain mistakes. Listen to the episode to check what was said.
Chapters
Tap a time to open that second in VOThe AI Investment Cycle Explained
0:20 to 2:32
A deep dive into the current AI capital expenditure cycle and its implications.
“AI-related investment will be one of the largest investment cycles of this generation.”
Analyzing Past Investment Cycles
2:32 to 3:16
Comparison of the current AI investment cycle with past cycles and their outcomes.
“But when tying these dynamics together, it's important to remember why large investment cycles have a checkered history.”
Transcript
Automatic transcript. May contain errors.0:00Andrew Sheets:Welcome to Thoughts on the Market. I'm Andrew Sheets, Head of Corporate Credit Research at Morgan Stanley. Today, the debate about whether elevated capital expenditure in AI technology is showing classic warning signs of overbuilding and worries for credit. It's Thursday, October 23rd at 2 p.m. in London. Two things are true. AI-related investment will be one of the largest investment cycles of this generation. And there is a long history of major investment cycles causing major headaches to the credit market. From the railroads, to electrification, to the internet, to shale oil, there are a number of instances where heavy investment created credit weakness, even when the underlying technology was highly successful.
0:53Andrew Sheets:So let's dig into this, and why we think this AI-KAPEX cycle actually has much further to run. First, Morgan Stanley has done a lot of good, collaborative, in-depth work on where the AI-related spend is coming from and what's still in the pipeline. And importantly, most of the spending that we expect is still well ahead of us. It's only really ramping up, starting now. Next, we think that AI is seen as the most important technology of the next decade by some of the biggest, most profitable companies on the planet. We think this increases their willingness to invest and stick with those investments, even if there's a lot of uncertainty around what the return on all of this expenditure will ultimately be.
1:36Andrew Sheets:Third, unlike some other major recent capital expenditure cycles, be they the internet of the late 1990s or shale oil of the mid-2010s, both of which were challenging for credit, much of the spending that we're seeing today on AI is backed by companies with extremely strong balance sheets and significant additional debt capacity. That just wasn't the case with some of those other prior investment cycles and should help this one run for longer. And finally, if we think about really what went wrong with some of these prior capital expenditure cycles, it's often really about overcapacity. A new technology, be it the railroads or electricity or the internet, comes along and it is transformational.
2:18Andrew Sheets:And because it's transformational, you build a lot of it. And then sometimes you build too much. You build ahead of the underlying demand. And that can lower returns on that investment and cause losses. We can understand why large levels of AI capital investment and the history of large investment cycles in the past causes understandable concern. But when tying these dynamics together, it's important to remember why large investment cycles have a checkered history. It's usually not about the technology not working, per se, but rather a promising technology being built ahead of demand for it and resulting in excess capacity, driving down returns on that investment, and the builders lacking the financial resources to bridge that gap.
3:04Andrew Sheets:So far, that's not what we see. Data centers are still seeing strong underlying demand and are often backed by companies with exceptionally good resources. We need to watch if either of these change. But for now, we think the AI CapEx cycle has much further to go. Thank you, as always, for your time. If you find Thoughts of the Market useful, Let us know by leaving a review wherever you listen, and also 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.
3:39It does not consider your financial circumstances and objectives and may not be suitable for you.
From the publisher
Our Head of Corporate Credit Research Andrew Sheets wades into the debate around whether the boom in artificial intelligence investment is a warning sign for credit markets.
Read more insights from Morgan Stanley.
----- Transcript -----
Andrew Sheets: Welcome to Thoughts on the Market. I'm Andrew Sheets, Head of Corporate Credit Research at Morgan Stanley.
Today – the debate about whether elevated capital expenditure and AI technology is showing classic warning signs of overbuilding and worries for credit.
It's Thursday, October 23rd at 2pm in London.
Two things are true. AI related investment will be one of the largest investment cycles of this generation. And there is a long history of major investment cycles causing major headaches to the credit market. From the railroads to electrification, to the internet to shale oil, there are a number of instances where heavy investment created credit weakness, even when the underlying technology was highly successful.
So, let's dig into this and why we think this AI CapEx cycle actually has much further to run.
First, Morgan Stanley has done a lot of good collaborative in-depth work on where the AI related spend is coming from and what's still in the pipeline. And importantly, most of the spending that we expect is still well ahead of us. It's only really ramping up starting now.
Next, we think that AI is seen as the most important technology of the next decade by some of the biggest, most profitable companies on the planet. We think this increases their willingness to invest and stick with those investments, even if there's a lot of uncertainty around what the return on all of this expenditure will ultimately be.
Third, unlike some other major recent capital expenditure cycles – be they the internet of the late 1990s or shale oil of the mid 2010s, both of which were challenging for credit – much of the spending that we're seeing today on AI is backed by companies with extremely strong balance sheets and significant additional debt capacity. That just wasn't the case with some of those other prior investment cycles and should help this one run for longer.
And finally, if we think about really what went wrong with some of these prior capital expenditure cycles, it's often really about overcapacity. A new technology – be it the railroads or electricity or the internet – comes along and it is transformational.
And because it's transformational, you build a lot of it. And then sometimes you build too much; you build ahead of the underlying demand. And that can lower returns on that investment and cause losses.
We can understand why large levels of AI capital investment and the history of large investment cycles in the past causes understandable concern. But when tying these dynamics together, it's important to remember why large investment cycles have a checkered history. It's usually not about the technology not working per se, but rather a promising technology being built ahead of demand for it and resulting in excess capacity driving down returns in that investment, and the builders lacking the financial resources to bridge that gap.
So far, that's not what we see. Data centers are still seeing strong underlying demand and are often backed by companies with exceptionally good resources. We need to watch if either of these change.
But for now, we think the AI CapEx cycle has much further to go.
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 also tell a friend or colleague about us today
