What to Watch When Credit Spreads Narrow

Adam Jonas: Welcome to Thoughts on the Market. I'm Adam Jonas. I lead Morgan Stanley's Research Department's efforts on embodied AI and humanoid robots.

Tim Hsiao: And I'm c, Greater China Auto Analyst.

Adam Jonas: Today – how the global auto industry is evolving from horsepower to brainpower with the help of AI.

It's Thursday, August 21st at 9am in New York.

Tim Hsiao: And 9pm in Hong Kong.

Adam Jonas: From Detroit to Stuttgart to Shanghai, automakers are making big investments in AI. In fact, AI is the engine behind what we think will be a $200 billion self-driving vehicle market by 2030. Tim, you believe that nearly 30 percent of vehicles sold globally by 2030 will be equipped with Level 2+ smart driving features that can control steering, acceleration, braking, and even some hands-off driving. We expect China to account for 60 percent of these vehicles by 2030.

What's driving this rapid adoption in China and how does it compare to the rest of the world?

Tim Hsiao: China has the largest EV market globally, and the country’s EV sales are not only making up over 50 percent of the new car sales locally in China but also accounting for over 50 percent of our global EV sales. As a result, the market is experiencing intense competition. And the car makers are keen to differentiate with the technological innovation, to which smart driving serve as the most effective means. This together with the AI breakthrough, enables China to aggressively roll out Level 2+ urban navigation on autopilot. In the meantime, Chinese government support and cost competitive supply chains also help.

So, we are looking for China's the adoption of Level 2+ smart driving on passenger vehicle to reach 25 percent by end of this year, and the 60 percent by 2030 versus 6 percent and the 17 percent for the rest of the world during the same period.

Adam Jonas: How is China balancing an aggressive rollout with safety and compliance, especially as it moves towards even greater vehicle automation going forward?

Tim Hsiao: Right.  That's a great and a relevant question because over the years, China has made significant strides in developing a comprehensive regulatory framework for autonomous vehicles. For example, China was already implementing its strategies for innovation and the development of autonomous vehicles in 2022 and had proved several auto OEM to roll out Level 3 pilot programs in 2023.

Although China has been implementing stricter requirements since early this year, for example, banning the terms like autonomous driving in advertisement and requiring stricter testing, we still believe more detailed industry standard and regulatory measures will facilitate development and adoption of Level 2+ Smart driving. And this is important to prevent, you know, the bad money from driving out goods.

Adam Jonas: , One way people might encounter this technology is through robotaxis. Robo taxis are gaining traction in China's major cities, as you've been reporting. What's the outlook for Level 4 adoption and how would this reshape urban mobility?

Tim Hsiao: The size of Level 4+ robotaxi fleet stays small at the moment in China, with less than 1 percent penetration rate. But we've started seeing accelerating roll out of robotaxi operation in major cities since early this year. So, by 2030, we are looking for  Level 4+ robotaxis to account for 8 percent of China's total taxi and ride sharing fleet size by 2030. So, this adoption is facilitated by robust regulatory frameworks, including designated test zones and the clear safety guidance. We believe the proliferation of a Level 4 robotaxi will eventually reshape the urban mobility by meaningfully reducing transportation costs, alleviating traffic congestion through optimized routing and potentially reducing accidents.

So, Adam, that's the outlook for China. But looking at the global trends beyond China, what are the biggest global revenue opportunities in your view? Is that going to be hardware, software, or something else?

Adam Jonas:  We are entering a new scientific era where the AI world, the software world is coming into far greater mental contact, and physical contact, with the hardware world and the physical world of manufacturing. And it's being driven by corporate rivalry amongst not just the terra cap, you know, super large cap companies, but also between public and private companies and competition. And then it's being also fueled by geopolitical rivalry and social issues as well, on a global scale. So, we're actually creating an entirely new species. This robotic species that yes, is expressed in many ways on our roads in China and globally, but it's just the beginning.

In terms of whether it's hardware, software, or something else – it’s all the above. What we've done with a across 40 sectors at Morgan Stanley is to divide the robot, whether it flies, drives, walks, crawls, whatever – we divide it into the brain and the body. And the brain can be divided into sensors and memory and compute and foundational models and simulation. The body can be broken up into actuators, the kind of motor neuron capability, the connective tissue, the batteries. And then there's integrators, that kind of do it all – the hardware, the software, the integration, the training, the data, the compute, the energy, the infrastructure. And so, what's so exciting about this opportunity for our clients is there's no one way to do it. There's no one region to do it.

. So, stick with us folks. There's a lot of – not just revenue opportunities – but alpha generating opportunities as well.

Tim Hsiao: We are seeing OEMs pivot from cars to humanoids and the electric vertical takeoff in the landing vehicles or EVOTL. Our listeners may have seen videos of these vehicles, which are like helicopters and are designed for urban air mobility. How realistic is this transition and what's the timeline for commercialization in your view?

Adam Jonas:  Anything that can be electrified will be electrified. Anything that can be automated will be automated. And the advancement of the state of the art in robotaxis and Level 2, Level 3, Level 4+ autonomy is directly transferrable to aviation.   There's obviously different regulatory and safety aspects of aviation, the air traffic control and the FAA and the equivalent regulatory bodies in Europe and in and in China that we will have to navigate, pun intended. But we will get there. We will get there ultimately because taking these technologies of automation and electronic and software defined technology into the low altitude economy will be a superior experience and a vastly cheaper experience. Point to point, on a per person, per passenger, per ton, per mile basis.

So  the Wright brothers can finally get excited that their invention

from 1903, quite a long time ago  could finally, really change how humans live and move around the surface of the earth, even beyond,  few tens of thousands of commercial and private aircraft that exist today.

Tim Hsiao:  The other key questions or key focus for investors is about the business model. So, until now, the auto industry has centered on the car ownership model. But with this new technology, we've been hearing a new model, as you just mentioned, the sheer mobility and the autonomous driving fleet. Experts say it could be major disruptor in this sector. So, what's your take on how this will evolve in developed and emerging markets?

Adam Jonas: Well, we think when you take autonomous and shared and electric mobility all the way – that transportation starts to resemble a utility like electricity or water or telecom; where the incremental mile traveled is maybe not quite free, but very, very, very low cost. Maybe only the marginal cost of the mile traveled may only just be the energy required to deliver that mile, whether it's a renewable or non-renewable energy source.

And the relationship with a car will change a lot. Individual vehicle ownership may go the way of horse ownership. There will be some, but it'll be seen as a nostalgic privilege, if you will, to own our own car. Others would say, I don't want to own my own car. This is crazy. Why would anyone want to do that?

So, it's going to really transform the business model. It will, I think, change the structure of the industry in terms of the number of participants and what they do. Not everybody will win. Some of the existing players can win. But they might have to make some uncomfortable trade-offs for survival.  And for others, the car – let’s say terrestrial vehicle modality may just be a small part of a broader robotics and then physical embodiment of AI that they're propagating; where auto will just be a really, really just one tendril of many, many dozens of different tendrils. So again, it's beginning now. This process will take decades to play out. But investors with even, you know, two-to-three or three-to-five-year view can take steps today to adjust their portfolios and position themselves.

Tim Hsiao:  The other key focus of the investor over the market would definitely be the geopolitical dynamics. So, Morgan Stanley expects to see a lot of what you call coopetition between global OEMs and the Chinese suppliers. What do you mean by coopetition and how do you see this dynamic playing out, especially in terms of the tech deflation?

Adam Jonas: In order to reduce the United States dependency on China, we need to work with China. So, there's the irony here. Look, in my former life of being an auto analyst, every auto CEO I speak to does not believe that tariffs will limit Chinese involvement in the global auto industry, including onshore in the United States.

Many are actively seeking to work with the Chinese through various structures  give them an on-ramp to move onshore to produce their, in many cases, superior products, but in U.S. factories on U.S. shores with American workers. That might lead to some, again, trade-offs.

But our view within Morgan Stanley and working with you is we do think that there are on-ramps for Chinese hardware, Chinese knowhow, and Chinese electrical vehicle architecture, but while still being sensitive to the dual-purpose AI sensitivities around  software and the AI networks that for national security reasons, nations want to have more control over.

So  that's a long-winded way of saying we want the Chinese body, but we may need to find a way to have the U.S. brain in that body. And I actually am hopeful and seeing some signs already that that's going to happen and play out over the next six to 12 months.

Tim Hsiao: I would say it's clear that the road ahead isn't just smarter, it’s faster, more connected, and increasingly autonomous.

Adam Jonas: That's correct, Tim. I could not agree more.  Thanks for joining me on the show today.

Tim Hsiao: Thanks, Adam. Always a pleasure.

Adam Jonas: And to our listeners, thanks for listening. Until next time, stay human and keep driving forward. If you enjoy Thoughts on the Market,  please leave us a review wherever you listen and share the podcast with a friend or colleague today.

Vishy Tirupattur: Welcome to Thoughts on the Market. I am Vishy Tirupattur, Morgan Stanley’s Chief Fixed Income Strategist.

Vishwas Patkar: I'm Vishwas Patkar, Head of U.S. Credit Strategy.

Carolyn Campbell: And I'm Carolyn Campbell, Head of Consumer and Commercial ABS Research.

Vishy Tirupattur: Today we'll talk about the feedback – and pushback – we've received on the data center financing note we wrote a few weeks ago.

It's Tuesday, August 19th at 10am In New York.

In the week since we published a report on bridging the data center financing gap, we were met with a wide range of investors to discuss the key takeaways from our report.

We projected that meeting the data center demand requires something like $3 trillion of capital expenditure by 2028. And we projected that about half of this funding will come from hyperscaler cash flows, but the rest financed through different channels of the credit markets.

So, Vishwas, some of the skeptics invoke comparisons to prior CapEx cycles, particularly the late 1990s telecom boom that did not quite end well. How would you respond to that skepticism?

Vishwas Patkar: The 1990s telecom CapEx cycle certainly came up in a lot of our meetings. It was the last time we arguably saw CapEx cycle of this magnitude. I think the counter to this is that there are some very important differences versus what we saw then versus what we expect. Most importantly, the CapEx cycle back then was largely financed on corporate balance sheets, and we saw pretty significant uptake in debt issuance and leverage.

Also, through the 1990s, the names, the companies that were spending were mid- to low-credit quality and not cash rich. That's very different from the hyperscalers that are in the center of the AI spending. And these companies are very cash rich, and their credit ratings range all the way from AAA to high A. So very much at the top end of the spectrum.

In addition, we are quite optimistic about AI monetization, both the timeline and the magnitude. Some of this has also already been validated through second quarter earnings. We also think financing will be done through multiple channels going forward and it won't largely flow through to corporate debt. In fact, corporate debt issuance is actually a pretty small number of how we think this [$]3 trillion number will be met. And you know, the private credit piece, that we have talked about a lot in this report; we think it's likely to be skewed towards IG ratings, in many cases backed by contractual cash flows from credit worthy tenants.

So, the risk, in some ways, could come from the sub investment grade non-hyperscaler type tenants. And that's an important theme to be watching. But by and large, this cycle is very different in our view from the late 1990s.

Vishy Tirupattur: So, Carolyn, another pushback, is that the market will be overbuilt and won't be able to refinance in say, five years…

Carolyn Campbell: Yeah, Vishy. This is a really big concern, particularly for securitized credit investors. We're starting to see some of the ABS and CMBS deals look to refinance even this year, and that will pick up as time goes on and these deals hit their five-year maturities.

However, the biggest challenge to building new data centers in the U.S. today is access to power. Our equity research colleagues have identified a 45-gigawatt power bottleneck in the U.S., and we think this should keep the market structurally undersupplied of power and slow down the pace of construction, really limiting that overbuild risk. Thus, we expect that the churn and the vacancy rates will actually remain quite low in the medium term.

And so, while it's a concern that in the long run that these data centers will decline in value; for now we don't see that to be a primary concern.

Vishy Tirupattur: Carolyn, another concern we heard is that the investor demand will not keep pace with the supply, particularly in securitized credit. We also heard about the tenant quality, that tenant quality is a major concern in underwriting these deals.

So how would you respond to those two points?

Carolyn Campbell: Right. I mean, within ABS and CMBS, we don't think supply is really the limiting factor. We think it will come on the demand side for why we think that this market will grow to about [$]150 billion by 2028.

However, our discussions with investors and the data that we've seen suggest that while there are a few big accounts that have been active in the ABS and CMBS space so far, many have yet to allocate meaningfully – preferring perhaps even other esoterics so far. And so, we think that as the supply grows, so too will the number of accounts and the size within which they're participating.

That being said, the market is already starting to price in a higher risk of tenant weakness. We started to see deals with a lower proportion of IG or greater exposure to AI names price meaningfully wider than those deals that are almost entirely IG and are more for collocation and enterprise.

Ultimately there will be winners and losers in this new AI industry. And so, the diversification across region and across tenant type, exposure to residual cloud and enterprise businesses, and the proportion of IG and non-AI tenants in these deals will be very important as we assess the risks of ABS and CMBS deals.

Vishy Tirupattur: Vishwas, any way we cut it, the scale of investment here is pretty large. Would this scale of investment divert capital away from public credit?

Vishwas Patkar: I certainly think that's a possibility, and maybe even a risk over time – but probably skewed towards the back half of our forecast horizon, which goes through 2028. I think with the public credit market, the next few quarters’ supply should be largely manageable, and demand has been and should stay quite strong. But if you look a few quarters out, insurance demand has been very critical to what's supporting credit markets right now. If interest rates go lower, some of these insurance inflows could slow down.

And we've also talked about insurance allocations that are shifting towards private and securitized credit at the expense of corporate credit. So, slowly, you could say supply needs rise. You know, we have about [$]800 billion of financing that needs to be met by private credit while inflow slow down. So, I wouldn't view this as a fundamental risk for public credit, but certainly a reason why credit spreads may not stay as tight as they are, over a period of time.

Vishy Tirupattur: So ultimately, our projections are based on the transformative potential for AI and the role of data center financing to enable that. This is a high conviction view. As we have said elsewhere, we are not too wedded to the specific size estimates in the broad constellation of financing channels.

The point we want to drive home here is that credit markets will play a major role in enabling AI driven technology fusion. As always, they will be winners and losers, but data center financing as a theme for credit investors is here to stay.

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