The Global Rate Debate

Seth Carpenter: Welcome to Thoughts on the Market. I'm Seth Carpenter, Morgan Stanley's Global Chief Economist and Head of Macro Research.

Michael Gapen: And I'm Michael Gapen, Chief U.S. Economist.

Chetan Ahya: And I'm Chetan Ahya, Chief Asia Economist.

Jens Eisenschmidt: And I'm Jens Eisenschmidt, Chief Europe Economist.

Seth Carpenter: And today is going to be our third quarter economic roundtable taking a wide-angle view on the global economy and all the key forces shaping our outlook and the economy.

Seth Carpenter: It's Monday, July 20th at 10am in New York

Jens Eisenschmidt: And 4pm in Frankfurt.

Chetan Ahya: And 10pm in Hong Kong

Seth Carpenter: Since our last roundtable in April, the global economy has continued to face all sorts of shocks, a mix of resilience and friction. Inflation pressures have not disappeared. Energy and geopolitical risks have come up, they've receded, they've come back, they've receded all over the place

But there is one underlying source of momentum that we have to talk about. A nd that is the AI-driven CapEx cycle.

Michael, let me turn to you because the U.S. is a real focal point of all of this. Tell me a little bit about where Morgan Stanley Research is thinking about hyperscaler CapEx. How big it is? And then for you, when you think about the U.S. economy, just how big of a driver is it for what we're looking for in the U.S.?

Michael Gapen:  

Yeah, we continue to revise higher our estimates for hyperscaler and AI-related CapEx in the U.S. economy. We were thinking a little over a trillion for 2027. Now we're more like 1.2 - 1.3 trillion, maybe as high as 1.4 trillion in 2028. So, the level of hyperscaler spending continues to keep rising.

The growth rate and its effect on the economy is likely to slow. But as you noted, it's still a major driver of momentum in the U.S. You would look at that headline number and think, "Wow, that's, you know, 3.5 percent or so of GDP. Must be a massive source of momentum for GDP growth."

But roughly about 60 percent of that hyperscaler CapEx spending goes to items like computers and peripherals, equipment spending categories that have a very, very high import content.

We still get a significant number that AI CapEx is probably contributing around 40 basis points to growth this year. Be a similar-sized amount perhaps next year.

So, for an economy that's growing somewhere a little bit above 2 percent right now, maybe closer to 2.5 percent next year, that's a non-trivial amount.

We just have to remember it's fueling growth around the world, just not here in the U.S.

Seth Carpenter: Yeah, that's a really great point because I have seen some estimates where people say, "Well, if it wasn't for AI CapEx, the U.S. economy wouldn't have grown at all." And that's clearly wrong, as you point out. ,

But U.S. imports are necessarily exports from somewhere else. And, Chetan, if I can pull you into the story then, U.S. firms are buying a lot of AI-related equipment from Asia. What does that mean in your part of the world? And in particular, I'm thinking about Korea, Taiwan, and maybe some other economies in Asia.

What's the critical story there?

Chetan Ahya: So, for Asia, this has definitely been a big boon. If you look at Asia's exports, they have been booming, and particularly for the ones which are exporting semiconductors to the U.S. They are seeing semiconductor exports growing by 90 percent. And when we go back in time and compare Asia's semiconductor exports, it's very tightly linked to the U.S. IT CapEx. And it's not surprising when Mike Gapen mentions about the imports going up. It's on the other side, helping Asia's exports quite meaningfully.

So, so far, we've seen this benefiting Korea, number one, Taiwan, and also Japan. All these three are big beneficiaries of U.S. AI CapEx. And of course, also not just U.S., but the other countries which are doing any little amount of CapEx on AI front, that's also helping these three economies in the region.

Seth Carpenter:

You've been doing a lot of work, Chetan, recently about how much the story can actually broaden out, that the AI CapEx cycle has really contributed to Asian growth, but it doesn't tell the whole story that there's a broader industrial cycle.

Can you give us a little bit of a flavor of that story?

Chetan Ahya: That's right, Seth. So, we are actually highlighting that there is a CapEx and industrial super cycle that is underway in Asia, and there are four components to this story. AI and semiconductors CapEx., which we just briefly discussed.

Number two is energy. Number three is defense. And number four is industrial supply chain onshoring related CapEx. I know that everybody still thinks that AI is the most important part of this story, but when I give you the numbers and the breakup of that... So, for Asia, AI and semiconductor companies CapEx is about $380 billion in 2026, but energy CapEx is going to be $900 billion.

So, this is a far broader story than just AI for Asia.

Seth Carpenter: Mike, let me come back to you and to the U.S. then. So, isn't the growth story also broader than that as well domestically?

So, what's going on in terms of consumer spending in the U.S., and is there a broader CapEx story in the U.S. as well?

Michael Gapen: I would say, is it broader than that? I think maybe you could argue also it's narrower than that. Here's what I mean by that. As I noted AI CapEx contributing about 40 basis points to growth, it's certainly underpinning equity valuations in the U.S. and underpinning strong wealth creation.

So about [$]180 trillion in household net worth in the U.S. About [$]55 trillion of that has been created in just the last five years alone, underpinned in part by AI-related spending and optimism about future profitability. That's really supported spending by upper income households. So, I think it's both investment-led and consumer-led, but they're inextricably linked.

So, the positive for the U.S. is that it's providing a lot of resilience.

The negative component of that is it feels like momentum in the U.S. is narrowly driven.

Jens Eisenschmidt: Let me maybe jump in here from Europe to provide some perspective from the other side. So, I think it's a fair summary to say that AI investment is not yet, or maybe will never get there, dominating the business cycle.

What we do have instead is an unusually consumption-driven expansion. That has to do not so much with an extraordinary strength of consumption, but more of an absence of other factors. Now, prospectively looking forward, we think the fiscal expansion might help lifting us a little bit. And then it is really the debate how much AI investment can arrive in Europe.

For now, I would say it's probably a factor of 20 that separates European investment plans from the plans we know that exist for the U.S.

Seth Carpenter:

Let me stick with you then in Europe because you brought up fiscal as one of the factors going on here and where it's going… You and your team recently wrote a blue paper talking about what the outlook is for fiscal policy in Europe, and in particular, we had this era of cheap debt. Interest rates in Europe were low, at times negative. It was super easy to borrow. Not as much happened then.

There's been a shift towards more fiscal expansion at the same time that interest rates have gone up, causing the cost of debt to go up. Feels like there's a lot of push and pull going on. Can you unpack for us a little bit what was in that paper you wrote, what's going on with fiscal policy in Europe, especially in Germany? And what it might mean over time for Euro-area countries?

Jens Eisenschmidt: Yeah, so I think fiscal policy in Europe really is looking at a regime shift. So, there is this very famous, probably in the U.S. even more so than here, notion that the Europeans have built a very comfortable welfare state. And that's true if you just look at the accounting from a GDP perspective. It's close to 50 percent that, you know, budgets are actually extended on welfare spending.

And now you have three structural headwinds for any type of fiscal spend. So, one is aging related costs, you mentioned it already. Defense spending has to increase significantly, and the interest rate costs will also rise significantly. All of that means there will be very hard choices to be made.

The one thing that actually could help here is growth. Growth is the one thing that's, for now at least, missing, at least in comparison to the U.S. It's probably half what we expect, what the U.S. colleagues think is in stake for the U.S., and a quarter or even less than that of what is there in Asia.

So, growth is really the key, the solution, the answer to everything in Europe. More growth than just 1 percent, which is potential, would help solving that fiscal challenge. For now, it looks really, really like an uphill battle. Returning to Germany, it's the one country that has a very good fiscal starting position.

They are pushing a lot but they're to some extent pushing a string. So, even with the German huge fiscal package, given that private sector investments so far are absent, doesn't get us a ton of growth.

Seth Carpenter: Chetan, maybe I'll come back to you before we close part one of this roundtable. The AI CapEx cycle started with AI, broadened out further. How long do you expect this cycle to last? How durable can it be? And how might it compare to previous CapEx cycles?

Chetan Ahya: Yeah, Seth. So, we think this will be a multi-year CapEx cycle. And when we are thinking about the duration of the cycle, there are two things that I would keep in mind.

Number one is that most of the drivers that we just discussed – the CapEx on AI, energy, defense, and industrial supply chain onshoring related investments – these are all structural drivers. So, we think these are going to continue for some more time. At this point of time, we have the visibility for this cycle to be lasting for three-four more years.

And then the second point of framework that I would keep in mind is that the corporate balance sheets are in a pretty good shape. So, when you are thinking about the leverage in the private sector, you can look at both households and the corporate sector balance sheet. But since the cycle is CapEx driven, we are looking at the corporate balance sheets, and they are in a pretty good shape.

Across the region, corporate debt to GDP is below where it was in 2019.

Seth Carpenter: . Mike, let me, let me wrap up quickly with you. We talked about AI, AI CapEx. For now, that's a very strong demand story.

When are we going to see a supply side of things coming from AI? Are you already seeing a big contribution to GDP and growth from productivity coming from AI?

Michael Gapen: We are, but not outside of the high-tech sectors, and we're seeing limited, what I'll call labor market restructuring of tasks and occupations beyond high AI-exposed occupations.

So right now, everything is still very isolated I think maybe as we get into 2029 and beyond, so as Chetan says, we probably have a three to four-year super cycle here around a build-out phase. Then we might see some of that broader-based diffusion to other non-tech sectors in the economy.

Seth Carpenter: All right, Jens, for you, let's wrap up here. So, what is the state of play for the build-out in the CapEx cycle for AI in Europe?

Jens Eisenschmidt: Yeah, it's very early stages. As I said before, we really; we connected to all the industry experts or analysts covering the sector and the total plans are a factor of 20 below what we see in the U.S. by just the seven hyperscalers. So, I would say very fragmented, very small, in general. Not only AI.

I think the one thing I would be looking at for any type of sign of revival, sign of growth is investment. The second would be investment. And you can guess what the third would be… Investments in the core countries. That's really what we need to see, and we haven't seen much in Germany or France on this front.

Seth Carpenter:

That's a great place for us to stop today. We talked about the real side of the economy, AI, CapEx, trade. Tomorrow we're going to come back, and we'll talk about how that growth outlook affects inflation. And once you start talking about growth and inflation, you got to talk about policy, and that's where we'll be tomorrow.

Mike, Jens, and Chetan, thank you for joining today. And for the listeners, thank you for listening. Be sure to tune in tomorrow for Part 2 of our conversation. And I have to say, if you enjoy this show, please leave us a review wherever you listen, and share Thoughts on the Market with a friend or a colleague today.

Welcome to Thoughts on the Market. I’m Ariana Salvatore, Head of U.S. Public Policy Research at Morgan Stanley.

Today: Why sovereign AI is becoming a policy priority around the world.

It’s Wednesday, July 15th, at 10am in New York.

The AI controls debate used to be focused on chips. Cutting edge semiconductors are essential to train large AI models, after all. But over the past year, the debate has moved well beyond that narrow focus. The policy conversation has broadened beyond things like which advanced semis can be sold to China.

The bigger question now is who controls the full AI stack — chips, cloud infrastructure, frontier models, data centers, cybersecurity standards, and the energy systems that support all of it.

That’s what we mean when we talk about sovereign AI. At the simplest level, it's a country’s ability to develop and deploy artificial intelligence using its own infrastructure, data, workforce, and technology ecosystem. But sovereign AI is also about reducing strategic dependence on foreign platforms and foreign-controlled supply chains.

That echoes a trend toward multipolarity that we’ve been writing about since back in 2018. Countries around the world are prioritizing national security over economic efficiencies. We see that theme applying to AI as well.

So, what does this all mean for markets?

First, sovereign AI turns AI infrastructure into a matter of national industrial policy. Data centers, power availability, and grid reliability are just a few examples of components that are becoming strategic assets. That means governments are likely to play a larger role in deciding several aspects of the AI buildout. Where it’s is built? Who finances it? And which countries get access to the most advanced parts of the stack?

Second, sovereign AI reinforces the shift toward derisking and a more fragmented international order. The U.S. is trying to promote the export of an American AI technology stack to allies and partners. At the same time, it’s preserving national security guardrails around the most sensitive capabilities. Meanwhile, we see China trying to indigenize as much of the technology as possible, from chips to cloud to model deployment. Other countries are navigating between the two.

Third, and importantly, sovereign AI is also an energy story.  Who gets to build and benefit from AI increasingly depends on access to low-cost, reliable power. That makes energy availability a competitive advantage — and it also makes energy affordability a political constraint.

That dovetails with one of our thematic predictions heading into this year: the politics of energy. We see rising power costs as a more visible political issue. That’s led to backlash against data center development. There’s more local opposition to new projects, and greater pressure on policymakers and utilities to make sure that existing ratepayers are not subsidizing AI-driven grid investment.

We think that could push AI infrastructure in a few directions. One is toward a conditional build-out. Here, offsets like large-load tariffs and other cost-allocation mechanisms are designed to protect households and small businesses.

Another direction is  policy support for the lowest-cost sources of energy, even where that might create tension with emissions objectives. And the third direction is more off-grid or behind-the-meter power solutions. That would include things like fuel cells, storage, and other time to power strategies — so data center developers can secure electricity without intensifying local affordability concerns.

The pursuit of sovereign AI comes with many questions around inflationary impacts: compute & power are both constrained, regulation remains uncertain, and there could be more limitations on things like tech transfers if the government sees a national security edge. So to the extent that countries want to reduce their dependencies, it may cost more to get there. There are, however, companies that can benefit in this environment.

But there’s also a policy risk. We are left with a more reactive policy environment. Selective access in some areas, tighter controls in others, and ongoing uncertainty around how Washington will treat advanced chips, cloud infrastructure, and frontier model deployment. Now that uncertainty matters because it affects corporate planning, cross-border investment, and the shape of global AI alliances.

So what does this all mean for investors?

More and more, governments view AI capability as a source of economic power and geopolitical leverage. That means the AI race is moving from a question of who builds the best model to who controls the infrastructure, standards, supply chains, and energy systems that allow those models to scale.

In our view, that means sovereign AI is one of the most important themes to watch in the next phase of the AI buildout.

And we’ll be coming back to this topic soon. In the coming weeks, Stephen Byrd and I will talk  about sovereign AI in more depth, particularly around what it means for power demand, data center investment, energy affordability, and the broader infrastructure required to support the next stage of AI adoption.

Thanks for listening. If you enjoy the show, please leave us a review wherever you listen and share Thoughts on the Market with a friend or colleague today.