How Digital Assets Are Rewiring Financial Markets

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

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

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

Seth Carpenter: And today, our fourth quarterly economic roundtable discussion is going to try to take a wide-angle view on the global economy – and it has held up despite higher interest rates, higher energy prices, geopolitical uncertainty, you name it.

It's Thursday, October 22^nd at 10am in New York.

Jens Eisenschmidt: And 4pm in Frankfurt.

Chetan Ahya: And 10 pm in Hong Kong.

Seth Carpenter: All right then. Let me start with that big question  Why has global growth held up better than maybe would have been expected given everything that we've seen ?

Mike, maybe I'll start from the U.S. perspective with you. What do you think has mattered most? What is driving – if I dare use an overused word – the resilience of the economy?

Michael Gapen:  Most of us believe AI-related spending is interest rate insensitive and geopolitically insensitive. And certainly, I think the data has borne that out. And in the direct translation of AI hypercaler Capex spending to growth, we find that AI is accounting for 4/10 to 6/10 contribution to growth in any given quarter. You could nudge that a little higher if you think it’s creating productivity, which we do.

And that spending is underpinning asset market appreciation – or certainly has for the past several years. And that is underpinning resilient spending by upper income households.

So, I think in the U.S. the clear answer is AI-related spending, but also its linkage to asset markets and upper-income households.

Seth Carpenter: Jens, let me come to you for the European view. I mean the AI story has been a little bit different in Europe. I think consumer behavior sometimes can differ in Europe than in the United States.

What would you say is the story behind the resilience of economic growth there in Europe?

Jens Eisenschmidt:  It’s similar in the sense that there is a clear element of also of AI-related external demand.   That even in Europe now the phones are ringing, given that we are more typically seen as  on the more higher cost end of the spectrum.

So, I think there was clearly in the second quarter data, export-led growth elements related to AI or delivery into that. There was also an element of geopolitical tensions helping some of those producers – say, chemical industry in Germany comes to mind – that would deliver products that would previously be delivered out of the Strait [of Hormuz].

So, that is another element. And then, yeah, the consumer held up [00:04:00] better than had expected. Or that you could have expected given the rise in energy prices. So all in all, that got us a relatively solid second quarter print. And we expect this to be more or less repeated also in the third.

Seth Carpenter:  Chetan, the export story is pretty important. You've been writing about a big CapEx cycle and big industrial cycle in Asia. So, when you think about the Asia story and why the economic growth held up in spite of the global shocks, how would you characterize that?

Chetan Ahya: Yeah. So, Asia is benefiting from a strong pickup in CapEx, which initially was led by the tech sector, but is now broadening out to energy, defense, and broader industrial investments. Exports are strong, and showing some signs of broadening out from tech to non-tech goods too.

This has meant that the region has faced positive terms of trade situation despite higher oil prices. Higher export prices have boosted corporate profits and in turn government tax revenues, offsetting the fiscal pressures from higher fuel subsidies.

And when you're thinking about higher interest rates that you are seeing globally and also in Asia, what is different in this cycle is that the macro stability indicators are in a good place. Current account surpluses in the region have widened quite significantly. In fact, it is $1.6 trillion or 4.2 percent of GDP.

Also what we have is the private sector balance sheets outside of China are quite healthy.

So, all in all, both higher oil prices and interest rates have not disturbed the CapEx and growth cycle in the region.

Seth Carpenter:  Is there a lot of dispersion across sectors, across countries for this cycle that you’re talking about? Can you go a little deeper there?

Chetan Ahya: Yeah. So let me start first with the story [00:09:00] on investment versus consumption So initially, the growth story in the region started with a pickup in exports and CapEx. But what we have seen is that this has now broadened out into a dynamic where we see an improvement in the labor market and therefore consumption growth.

So, we have this recovery broadening out from exports to CapEx to consumption.

And within the region, when you're thinking about different economies. Initially, we saw very strong growth in Korea and Taiwan. But now we have seen growth being strong in all parts of the region, especially in economies like India, Japan, and also some of the Southeast Asian economies like Malaysia and Singapore.

Seth Carpenter: I want to stay on this broadening theme, Michael.

Is all of the CapEx spending, all the investment spending, by business in the United States, is it just an AI story? Are we seeing any broadening of the investment story in the U.S. beyond AI? Or should we just resign ourselves that the rest of the economy is going to stagnant?

Michael Gapen: No, I do think we are seeing evidence of [00:11:00] some broadening out. It is most clear in manufacturing.

So, I do think it points to some broadening out in the AI story beyond the narrow AI story into something that is broader that both Chetan and Jens have referenced about in a multipolar world needing to build out redundancies in supply chain.

Maybe there's some incentive to do some reshoring. So, whether it's a spillover effect from AI or a spillover effect from geopolitics writ large, I do think there's some evidence that we're seeing the broadening out.

I would just caution and say, just remember, manufacturing in the U.S. is relatively small. It's only about 10 percent of output and maybe 10 percent of employment. But nonetheless, it's there. So, it's not just an AI story. I think you can characterize it as a bit broader.

Seth Carpenter:  Let me come to you, Jens, on this. We've seen an investment story play out for a while in Europe. There was a lot of discussion about defense especially in Germany –infrastructure especially in Germany.

Is that still an important part of spending in Europe, the investment side of things? And how important is investment relative to household?

Jens Eisenschmidt: Yeah. No, I mean, I think in, in terms of the shares; and GDP shares in spending, you're talking about 50 percent versus 20 percent. So, consumption is the more important one…

If you talk about relative [00:13:00] expectations, so I think there your question really points at a key component of the forecast.  If anything, you could expect maybe some more dampening from here, given that energy prices have increased further, and at some point the consumer will just capitulate. Or at least, need to show some signs of retracement. While investment has so far, in the aggregate at least, not shown any signs of a big revival.

And if anything, this is what we would expect more investment from here – be it related to, you know, a progressive AI build out.

Or be it because we anyway expect some more positive investment dynamics given where we are in the cycle and given that the ECB has decreased rates last year. And at some point, this typically shows up in investment demand.

So, long story short, the relative importance as a growth driver should increase of investments, vis-a-vis consumption. I think that is that is relatively clear. The question is just the magnitude here.

Seth Carpenter: How much do you worry then that not only is investment going to become bigger share of growth? That consumption could weaken even more because energy prices chip away at purchasing power of households? Is that a relevant factor for Europe?

Jens Eisenschmidt:  I think that has to be the ma- number one growth worry going forward So essentially, you come down in terms of wage increases from very high level that were reflective of past inflation.

So, the European wage setting process always lags inflation, and so basically today's wage agreements are reflective of yesterday's inflation.

But now we are going above 4 percent, very likely on our forecast. Not an awful lot above 4 percent, but still above.

Then it becomes a question of [00:16:00] how long this is going to persist. If you just believe the future curves in energy markets – not long. But then if you look at more details in terms of, for instance, where diesel prices are likely heading, you can become more pessimistic, and ultimately, this is what matters for the consumer. So long story short, big risks here, of course.

Seth Carpenter: All right. So, a consumer that's not exactly pulling its weight leads me back to China. Key economy in the world, one of the biggest economies going. But when it comes to demand, aggregate demand, China has been in this deflationary cycle for a while. The household sector has been pretty soft in terms of its demand.

What are we looking at there in terms of the consumer in China, the demand side of things in China? is that likely to [00:17:00] change anytime soon? And can the global economy look to China as a source of extra demand to keep this expansion going?

Chetan Ahya: Unfortunately, I think the short answer to your question is no. We are still very cautious on China's consumption outlook. And what we have been characterizing the China growth story as it's going through a K-shaped recovery.

On one side, you have the strength in exports and AI CapEx. And on the other hand, we have a very weak consumer.

Now, why is the consumption growth weak in China? So firstly, the property sector has still not [00:18:00] completed the adjustment cycle.

So, from consumer standpoint, they have still a weak labor market and wage income growth. On top of that, they have seen this massive decline in asset prices. And, so they are actually, de-leveraging at a very rapid pace. The outstanding debt for consumers is contracting at the rate of 1.5 percent. 1.5 percent is not a big number, but just to see that contraction is quite surprising.

And so therefore, all in [00:19:00] all, China's consumption growth continues to remain weak. We do think that there is a possibility that the policymakers respond to this weak growth and provide some support. But we're not expecting that support to be big fiscal expansion in a way that you get a major surprise on the consumption outlook for China.

Seth Carpenter: But as we started off saying, things are holding up, and so that fact brings up a question in my mind. Where are the risks? Where are the downside risks? And so, Mike, maybe I'll start with you.

What do you think would lead to a downturn in the U.S.? Where's the biggest vulnerability? What do we have to look out for?

Michael Gapen: Well, I think in the, the near [00:20:00] term, I do think higher rates pose a vulnerability. So, I would say if the central bank has to shift to a much more dramatic tightening cycle and interest rates go a lot higher, that would be a near-term vulnerability. But I think if we look further out, if the resiliency of the economy is driven by the AI investment cycle, then I think a potential over-investment cycle is the greater risk.

Seth Carpenter: Alright. Jens, what about in, in Europe?

Jens Eisenschmidt:  Clearly we have a discussion among European, in particular monetary policymakers, as evidenced [00:21:00] by the latest accounts of the ECB about the degree to which long rates have increased. Maybe, too much and, you know, present a significant tightening of financial conditions.

And juggling that in a good way will certainly be a risk and reason to be cautious.

So, I would say, here the three risks. Again, consumption because of energy prices, interest rates, or a too tight monetary policy stance. And of course, the investment cycle overall.

Seth Carpenter: Chetan, you get the last word in Asia

Chetan Ahya: So, I would say, Seth, two risks. One is higher oil prices and the second one is, if you see a contraction in AI investments in the U.S. and therefore in Asia as well.

So, on oil prices, I would say a threshold of $130 to $150 of oil would be a problem for the region. It would make the governments finally do resort to higher oil prices for the consumers.

And if you get a combination of higher oil prices and lower AI investments, that would be quite a big shock to the region's growth outlook.

Seth Carpenter: Super helpful. And I think that's probably a good place for us to stop for today.

We talked about global growth. It's been holding up really well. Sources of that resilience probably differ a bit across regions, but investment is important and becoming probably more important over time. And that investment boom is spreading through trade. Domestic demand in parts for Asia. Europe has got its own story going on. And obviously, the consumer around the world matters a lot.

That current outlook though, of a reasonably strong economy with this shock from energy that's driving up inflation, means that the policy side of things, especially monetary policy, is now becoming kind of complicated.

So, what should a central bank do? When we come back tomorrow, we're going to ask questions about the Fed, the ECB, the Bank of England, the Bank of Japan. How they're thinking about what's going on, the tightening that needs to be done, whether or not this is going to be a fully synchronized hiking cycle.

And I guess most of all, what's going to tell us when the policy hiking has gone far?

Mike, Jens, Chetan, thanks so much for joining today. And to the listener, thank you for listening, and be sure to tune in tomorrow for part two of our conversation.

And 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.

Sabrina Hao: Welcome to Thoughts on the Market. I'm Sabrina Hao, Morgan Stanley's AI and Tech Thematic Equity Strategist.

Adam Wood: And I'm Adam Wood, Head of U.S. Software Research at Morgan Stanley.

Brian Nowak: And I'm Brian Nowak, Head of U.S. Internet Research.

Sabrina Hao: Today, what private companies are telling us about the AI opportunity and what it means for public markets.

It's Tuesday, October 20th, at 10am in New York.

Last week, we were at our Spark Private Company conference in California, bringing together more than a hundred startups across software, robotics, AI infrastructure, and beyond. There was even a company helping to manufacture pharmaceuticals in space.

It was a really interesting week to be at the conference given everything that was happening in the market. But really, we came away feeling even more positive about the AI cycle.

While public market investors are waiting for returns to justify trillions of dollars in AI spending, we're already seeing that pay off in private markets. AI demand is real, companies are delivering tangible returns for customers, and startups are scaling faster than ever.

Adam, let's start with growth. We heard from startups scaling at extraordinary speeds. One was approaching [$] 4 billion in annual recurring revenue in two years, another reaching a billion in under a year.

What really stood out to you about the pace of AI adoption, and why aren't we necessarily seeing that same growth at established software companies?

Adam Wood: So yeah, absolutely, the pace was remarkable. And clearly one of the standouts from the conference when we used to discuss how quickly a company could get to a $1 billion so-called unicorn valuation. And now we're discussing how quickly they can get to a unicorn revenue run rate of a billion dollars, which for me is quite incredible.

But I think I wouldn't make the debate simply about private versus public companies. I'd make the distinction between two different types of software.

I think we have to make a distinction between largely coding and inference tools. There were a number of coding and inference software companies at the conference, and application software. And I think there's a big difference in terms of time and complexity to bring these products to market.

I think the coding and inference, which tends to be the building blocks, as I would call them, underneath the application layer, they can be constructed much more quickly. And I think because we can adopt when we're still building bespoke, which I think is a lot of the phase we're in today, we're still building bespoke software rather than buying off the shelf. They can be adopted earlier as well.

So, we've got faster time to build and faster time to adopt by companies. So, I think it's natural you can see very fast growth in those types of businesses very quickly.

I think in the application landscape, it's a little bit different because those applications have to deliver complete business solutions for customers. In finance and customer service, that means integrating data, understanding workflows, and putting controls in place.

There's much more to build and much more to implement, and generally, the adoption of those tools takes place a little bit later.  After we've gone from the bespoke phase where companies are building themselves, we go to a phase where companies see that there are off-the-shelf packages that are available, that companies have built out.

So, I think it's both a complexity of build debate and also, a time in terms of where we are in the software adoption cycle.

The second thing I'd say is, you know, in public software companies that have a big incumbent existing business, sometimes there can be that big incumbent business that's not growing very quickly. And a very fast-growing AI business in there as well. And that very fast AI growth business can be hidden a little bit by that large public software company that exists.

So, I don't think it's as straightforward as just saying, you know, private's growing very quickly, public not. I think there's a couple of layers of complexity in there in terms of what type of software you're dealing with. And then how big the existing kind of business is in a software company and what is kind of existing software growing a little bit less quickly. And then the AI bit that could potentially be growing very fast.

Sabrina Hao: Absolutely. It makes a ton of sense. Maybe on this theme of full stack solutions, you know, Brian, we heard about the shift from AI assistants to agents that can actually execute work. You've done a lot of work on this, both across consumer and enterprise.

What did you learn about how quickly agents are advancing? And how does it shape the outlook for the internet names that you cover?

Brian Nowak: This is a very exciting time for agentic adoption on both the consumer side and the enterprise side. You know, we've sized potential addressable markets of $30 to $40 trillion of spend on both the consumer side and the enterprise side that we think can be addressed by agentic tools. On the consumer side, people are shopping, they are planning their travel, they're planning their holiday shopping. On the enterprise side, we're seeing both vertical specific agents start to emerge. So, agents within the legal area or agents within the healthcare area. And then we're also seeing broad-based agents from some of the larger private companies also start to bud through.

So, there is a smattering of agents that are popping through. On the consumer side, Muse is your early leader, and we do expect more to come in 2027. And then I think on the enterprise side, they're both vertical specific as well as broader based agents expected to grow.

Sabrina Hao: Agents really raise an important question around disruption. Maybe for Adam, you've written about the moat and the journey in software. It's not just about if a company has a competitive advantage, but how it navigates that transition to an AI-driven world.

Did Spark change your thinking about which software incumbents are best positioned to defend their businesses or capture new growth?

Adam Wood: So, I think Spark really confirmed a lot of our views on that moat and journey framework that we've put forward. The moat protecting the existing business that you have and the journey turning AI into new growth opportunities. And in some ways, the deeper the moat for businesses, the longer that journey can be.

An incumbent embedded in complex mission-critical workflows is hard to replace because of the data integrations and customer trust it has by definition. But those same requirements can make introducing AI into its platform more demanding. You can't compromise the reliability of that work.

So that's why we've separated the durability of the business from the speed of its AI transition.

For some of the coding inference businesses we heard from – again, these incredibly fast run rate, fast growth businesses, the monetization has obviously moved very, very quickly. And I think there the investor debate's going to be a little bit the opposite way around. How durable and how big a competitive advantage have these companies built on that very fast-growing revenue base?

And that's not to say these businesses can't have moats. They can. You know, performance, model customization, and integration can create real differentiation. But I think there is a big difference to be made between rapid growth and defensibility.

And, you know, to give a couple of examples here in terms of the moat that some of these AI native vertical and business software companies are leveraging. You know, there's a legal AI company that's hiring former lawyers to become forward deployed lawyers.

We had forward deployed engineers, now we've got forward deployed lawyers. But the reason there is they bring that understanding of legal workflows to the product and its implementation.

So, the value isn't just access to the model. It's making the model and the technology work in the customer's business and understanding in depth those business workflows.

Sabrina Hao: And we've talked about this theme of AI adopters, and really what we need to get this trade to work are those quantifiable benefits from AI. So open weights are a key part of that.

Maybe to pull on another thread, and you, kind of, alluded to this, the models themselves are increasingly becoming table stakes rather than moats. And the value is shifting to everything around the model – whether that's your data, your workflows, the tools that make AI useful.

So where did you see this most clearly at Spark? And does it change your view on where durable value will accrue in software?

Adam Wood: So again, I mean, I think I'd come back to the growing importance of open weight models. I mean, it was a recurring theme at the conference. Almost every company spoke to us and spoke to, you know, the implementation. And again, it reinforces that view of a multi-model world.

You’ve got the inference companies talking about bringing down the costs of using the models. Again, that diffusion concept we talk about. At the application layer, a legal software company said it benchmarks 18 models across 200 criteria to decide which model should run the task. So, you know, you're getting incredible gains in efficiency.

I think there are two implications for public software vendors. I think, you know, first of all, there's an opportunity here for software companies to help their customers with orchestration. So, there's going to be a layer around how do we get the right task to the right model at the right price. And I think a lot of the public software companies, you know, at the hyperscaler level, they can help at a broader enterprise adoption level.

And then down at the application layer, whether we're talking about CRM, ERP, HR, there's an opportunity for software companies to help with orchestration at that layer as well.

I think the second thing, which is probably a little bit less talked about, is maybe there is a gross margin opportunity here. I think in software, all we've discussed so far is the pressure that's going to come on gross margins from having to include the cost of running tokens in a software business model and offer that to customers as part of the package.

If we can bring down inference costs dramatically, and you can hold on to some of the pricing as a software company – maybe there could be a little talked about bull case in the medium term. That maybe software margins are not going to be as pressured as people think. And we can maybe see gross margins hold in a lot better than people think.

Sabrina Hao: Brian, I want to end with something that may seem counterintuitive. In a world where software's becoming easier to build, some of the strongest competitive advantages may actually be in the physical world.

The conference had many companies, whether that was logistics, manufacturing, real-world operations. You know, why is that intersection of the digital and physical world so defensible? And how does it influence your view of who ultimately wins in an agentic world?

Brian Nowak: I think it's important for people to remember that AI is not just software. AI is going to get physical through new types of robots that impact the entire globe. We're seeing it in multiple industries already. We're seeing it on the defense side with drones and other types of mechanisms that are going to change the way that we build out our overall defense tools. We're seeing it on the industrial side, in warehouses, on delivery. We're seeing it on the agriculture side, the way that we're going to the future of farming.

And so over the long term, while I think we will have humanoids and we will have robots in our homes, I think it's important for people to keep in mind there are going to be a lot of physical and robotic implementations of AI over the next two, three, five years that are going to really change the way we do a lot of business.

Sabrina Hao: Absolutely. Lots of exciting things happening. Adam, Brian, thanks for joining me. And thank you for listening. 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.