Thoughts on the Market

Betsy Graseck and Michael Cyprys explore how AI could expand advisor capacity and tokenized assets could grow into a $2.3 trillion market by 2030.
Read more insights from Morgan Stanley.

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Betsy Graseck: Welcome to Thoughts on the Market. I'm Betsy Graseck, Morgan Stanley's Global Head of Banks and Diversified Finance Research.
Michael Cyprys: And I'm Mike Cyprys, Head of U.S. Brokers, Asset Managers, and Exchanges Research at Morgan Stanley.
Betsy Graseck: Today, we're looking at the next phase of growth across asset and wealth management – and how tokenization, AI, and changing investor flows could reshape the industry.
It's Thursday, October 1st at 9am in New York City.
Assets under management, or AUM, are near record highs across the globe, with a lot changing beneath the surface. Now, much of the recent AUM growth has come from markets rather than from net new client flows. And meanwhile, fees do remain under pressure.
At the same time, technologies like AI and tokenization are creating new opportunities for both asset and wealth managers. Our base case has tokenized real world assets growing from roughly [$]40 billion today to about [$]2.3 trillion by 2030.
Mike, let's start with tokenization. What are the use cases that matter most near term?
Michael Cyprys: So, as we think about it, there's a number of use cases that we see. The most compelling ones really are around cash treasuries and collateral. Take for example, earning yield. Some tokenized funds allow you to earn interest by the minute or the second that is invested rather than having to remain invested by that 4pm cutoff that is the case today.
Another benefit is allowing collateral to move around a lot more easily, and this can help support a shift toward 24/7 markets. So, if securities can trade 24/7 – or derivatives – you may also need the cash leg of that transaction to keep pace. Right now, there are certain futures contracts that do trade over a weekend, but those positions do need to be pre-funded on Friday.
So that's going to limit perhaps the full uptake for that of 24/7 until you can get the movement of the collateral to keep pace. And that's where tokenization can come in to help solve a real market need.
There's also trapped collateral that's just sitting around the world, where institutions and corporates just keep pockets of liquidity in different places just in case they need it at a moment's notice. There’s a cost to that while it sits idle. But tokenization can allow for just more just-in-time movement of money, say with tokenized deposits, tokenized money funds, or stable coins.
And another use case is around investors outside the U.S. that may not have as easy access to U.S. markets. But tokenization can help lower barriers, reduce frictions, and allow for greater access to U.S. market exposure. Private markets get a lot of attention, but we think that's maybe a little bit further out.
So, to put some numbers around this, today there's around [$]40 billion of tokenized real-world assets. So, think tokenized stocks, bonds, funds. In our base case, we could see that growing to about [$]2.3 trillion by 2030, with a vast majority tied to these collateral mobility and reserve and treasury management use cases.
Betsy Graseck: Pulling up a notch, we are expecting assets under management to reach about [$]247 trillion by 2030. But revenue growth is expected to lag asset growth. Mike, what really separates the firms that can grow above market trends you expect?
Michael Cyprys: Yeah. So, as you said, most of the growth is going to be driven by market beta, right? So, we have expectation for about 9 percent growth annually in assets under management for about $160 trillion globally today to about $250 trillion by 2030. We expect about three-quarters of that growth rate comes from market beta, which leaves you around 2.5 percent for organic asset growth.
So, growing just AUM with the market is not going to really be enough to differentiate. And so, as we think about, you know, how one can differentiate? First, I think it comes down to where one is positioned across the industry. We do see flows concentrating in passive solutions and selected private markets, and the economics can be pretty different there as well.
Another way to differentiate is through distribution. Wealth, retirement, model portfolios, customized solutions, all of those channels are becoming much more important. And so, you want to be closer to where that asset allocation decision is actually getting made.
And another point of differentiation is around operating leverage, and that's where AI comes in, which I'm sure is a topic we're going to get to in a little bit. That we think can help allow money managers to expand research coverage, can allow salespeople to cover more clients, allow for adding more products and customization without adding necessarily a lot more people and cost at the same rate.
So, look, bottom line, I'd say, we think above market growth from having the right products, the right distribution, getting them in front of the right clients, and the technology to scale that just a lot more efficiently.
Betsy Graseck: And how important is that AI tool going to be, in your opinion, for separating yourself from the pack? And is it more top-line generative or cost efficiency generative?
Michael Cyprys: I think it's critical. It's both. I think it changes the competitive game because a lot of the economics are very different across the businesses, right? Take passive and index investing, for example, that continues to take share.
It's a low-fee business, so there scale really matters. In solutions and private markets, the revenue opportunity is better, but you need more capabilities and distribution reach. And in private markets, origination is also key, as well as distribution, right?
You can have private credit or an infrastructure product out there in the marketplace. But if you can't get it into a wealth or retirement or insurance channels, then you're leaving a lot of growth on the table.
And then with traditional active, performance still matters, but the wrapper is key. Distribution matters more so than ever, and active ETFs are a great example of that.
Betsy Graseck: And one question on AI is: How far along do you think it is in your coverage embedded already in the workflow and the processes across your group, your asset managers?
Michael Cyprys: So, we're pretty early days here. A lot of firms, already have AI tools today: RFP tools, sales tools, tools within the operational and distribution side.
But saving someone, you know, 10 minutes on a task doesn't necessarily show up in the P&L, right? You need to start removing entire steps from workflows. And then using that time savings to cover more clients, to launch more products, do more research, and ultimately slow the pace of hiring.
And that's where we think the industry needs to move towards, away from these, sort of, point solutions into an enterprise workflow. And that is tools that connect across the entire organization, underpinned by the same data and the same controls. And our work suggests that this could be pretty meaningful over time, perhaps up to as much as 15 points worth of operating margin improvement – for the leaders over time. But we don't assume that all falls to the bottom line.
We expect it to – you know, a lot of that's going to get reinvested, and a portion probably also gets competed away. And when we look at our forecasts for the money managers we cover, I'd say we have modest improvement in operating margins over the next couple of years.
And, to your point, on cost versus revenue, we may actually see it on the revenue side first, as it can help allow for more client touches, broader coverage, and faster product development.
Betsy Graseck: Okay. So, or as you mentioned, early days.
How do you see AI and tokenization impacting either the leverage opportunities, the operating leverage opportunities, or the revenue growth opportunities? Let's start with AI.
Michael Cyprys: We think that the potential here is to really improve the capacity to serve clients. As you think about today, the time that advisors spend actually not talking to clients, right? When you think about time that they're spending on meeting prep or research, notes, follow-ups, onboarding.
And that's a lot of administrative work that is wrapped up, in terms of the advisor’s relationship there. And our work suggests that call it about half of that advisor time could be freed up.
Then advisor capacity could increase upwards of 30 to 40 percent on our numbers, and that can also increase the quality and the experience that the clients receive.
We also see a broader opportunity beyond just the advisor. As you look across the advisor team and the organization, we see an overall cost to serve to come down quite materially.
And I know this is a question you didn't ask it, but that's out there. We don't see AI replacing financial advisors, particularly at the higher end, just given the importance of that trusted relationship. And if anything, the value of that advisor probably goes up, particularly just given there's so much change happening around the world every which way you look. And then you overlay that with the aging demographic trends.
We actually think there could be a bull market for advice as we look ahead. And AI could be that tool to enable the industry to execute on that market opportunity set and also help expand the TAM in terms of the ability of the industry to capture that opportunity set and bring advice to more people than was ever possible before.
Betsy Graseck: And this would be incremental to your growth outlook that you indicated earlier of 7 percent?
Michael Cyprys: This could be incremental…
Betsy Graseck: Okay!
Michael Cyprys: ... to that opportunity potentially over time.
Betsy Graseck: Anything on tokenization that is an opportunity for wealth managers?
Michael Cyprys: Oh, absolutely. And I think that we're really, really early days; just scratching the surface on this in tokenization and wealth.
You know, I think one way to frame tokenization and wealth is it could just make the client balance sheet that much more productive.
And this creates some risk as we talk about in the report for the traditional wealth model with respect to sweep cash and the monetization of that, right? If clients hold less idle cash, that could put some pressure on deposit and sweep economics. But that could also be offset by new lending opportunities at the same time.
So, wealth firms need to be able to support tokenized assets and lending capabilities without losing that client relationship to someone else's platform. And that's why longer term, the wallet or the client interface becomes pretty important – because that's where the investments, cash borrowing, payments, all of that comes together.
Betsy Graseck: And all of this happening right ahead of Nasdaq and NYSE's December 6th, a big event.
Michael Cyprys: That's right. U.S. equity markets are going 23/5 on December 6th.
Betsy Graseck: Meaning that the only hours they will be closed every day are between...
Michael Cyprys: 8 and 9pm.
Betsy Graseck: And that's on a pathway to 24/7 ultimately, you believe?
Michael Cyprys: That's our expectation, as you have other disruptors around the world that are looking to provide retail with access to 24/7 markets.
Betsy Graseck: Exciting times, Mike. As you indicated in the beginning, we have 79 percent growth with AI and tokenization potentially amping that up ahead of a pathway to a 24/7 market.
Michael Cyprys: Indeed.
Betsy Graseck: Thank you so much for joining us here on Thoughts on the Market, Mike.
Michael Cyprys: It's been great speaking with you, Betsy.
Betsy Graseck: 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.

As investors look toward the U.S. midterm elections, the biggest question is what could change. Our Head of U.S. Public Policy Research Ariana Salvatore outlines the signals worth watching.
Read more insights from Morgan Stanley.

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Ariana Salvatore: Welcome to Thoughts on the Market. I'm Ariana Salvatore, Head of U.S. Public Policy Research at Morgan Stanley.
Today, I'll be talking about the upcoming 2026 midterm elections.
It's Wednesday, September 30th, at 10am in New York.
As the elections inch closer, investors are increasingly asking about potential ramifications. We just put out a deep dive covering our expectations, and we arrive at four key takeaways.
The first, midterms are unlikely to change the core executive-led policy agenda. As we've been noting for some time, a lot of the policy uncertainty that markets have dealt with since the beginning of 2025 has actually come from the executive branch rather than Congress.
Tariffs, trade policy, deregulation, immigration, and export controls are all variables that are going to remain within the White House's authority. So even if control of Congress changes, we don't think investors should assume that those parts of the policy agenda simply go away. Where Congress actually matters more is on fiscal policy. But even there, the range of outcomes is relatively narrow.
The main differences revolve around the timing of scheduled SNAP and Medicaid cuts, defense spending, and how future government funding and debt limit negotiations evolve.
So, that's our first takeaway. Midterms can change the mechanics of governing, but probably not the broader direction of the executive agenda. That means policy uncertainty, at least across those vectors I mentioned, is likely to stay high.
Takeaway number two, we'd be careful about treating the midterms as a direct signal for the 2028 presidential election. Historically, what we see is the issues that dominate a midterm don't necessarily translate to the next presidential race.
Looking at the six midterm-to-presidential cycles since 1994, the top-ranked issue changed in five of them. And the issue that ultimately proved decisive in the presidential election was actually already visible at the midterm in only two of the six cases. What elections can tell us, however, is where some of the policy fault lines are beginning to form.
We're watching four debates in particular in that context: the fiscal and Social Security debate, individual tax landscape, restrictions on data center development, and healthcare. In our view, across those variables, the useful signal isn't simply which party wins more seats. It's which versions of these policies are beginning to gain traction with voters and within the parties themselves.
That actually brings us to takeaway number three. AI is one area where the midterms could matter, but mainly through data center policy rather than broad AI regulation.
We think it's important to separate those two issues. So first, on data centers, we do see midterms as a catalyst. And that's because many of the most important policy levers sit at the state and local level: permitting, siting, grid interconnection, large load electricity rates, and tax incentives. So that means that the governorships, utility commissions, and state legislatures can actually have a much more immediate effect on the pace and the location of the build-out than Congress itself.
In that vein, our base case remains a conditional build-out, meaning the expected level of AI CapEx can continue. But likely it's going to increasingly concentrate in locations where developers can address concerns around things like electricity costs, infrastructure, water, and community impacts.
Broader AI safety regulation is different. Here, we think government configuration actually matters less, and that's because we see comprehensive federal legislation as pretty unlikely in the near term, absent a high salience event or incident. So congressional control is not necessarily the key driver.
And finally, takeaway number four: for markets, we see more micro implications than macro ones. For equities, the composition and cohesion of the congressional majority can matter for individual sectors. Congress that's able to negotiate changes to scheduled SNAP or Medicaid cuts, for example, could have implications for consumer and healthcare companies.
AI related sectors could also respond to changes in expectations and sentiment pertaining to data center restrictions. For rates, the key question is whether the election produces fiscal outcomes that materially change expected deficits.
United Republican control would be the only outcome preserving reconciliation as a potential vehicle. Divided government, conversely, would narrow the scope for new legislation and put more emphasis on funding and debt limit negotiations. And for the dollar, our strategists see the transmission mechanism running primarily through U.S. yields and the growth outlook rather than the election itself.
So, bottom line, we don't think the 2026 midterms are likely to produce a wholesale change in the policy or macro backdrop. But there will be important lessons to pick up along the way.
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.

Our China Industrials Analyst Sheng Zhong explains how AI, robotics and a major investment cycle could transform China’s manufacturing base and its role in global supply chains.
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Sheng Zhong: Welcome to Thoughts on the Market. I’m Sheng Zhong, Morgan Stanley’s China Industrials analyst.
Today – how AI and automation are transforming China’s factories, and what that could mean for global manufacturing.
It’s Tuesday, September 29th, at 3 PM in Hong Kong.
For decades, Made in China has been shorthand for scale, speed, and low-cost manufacturing. Now the story is shifting toward something more ambitious: using technology, productivity, and industrial know-how to shape not just what gets made, but how it gets made.
We call this transition Industry 5.0. Industry 4.0 was about connecting machines and digitizing production. Industry 5.0 goes a step further, using AI to improve how factories schedule production, manage quality, and maintain equipment.
China is starting from a position of enormous scale. It represents roughly 28 percent of global manufacturing value-added and covers all 666 industrial subcategories defined by the United Nations. There are already more than 30,000 basic-level smart factories and more than 100 million connected industrial devices.
That industrial base also gives China a strong platform for robotics. Traditional industrial robots generally perform fixed tasks. Embodied AI could make machines more flexible, allowing them to gain new capabilities through software and updated models. That could effectively turn some physical labor into software-upgradable capital.
And the numbers give you a sense of how quickly this could scale. China could go from selling about 8 million robots a year in 2025 to 29 million in 2030, and 76 million by 2035. That’s roughly a ninefold increase in annual sales in just a decade.
Scaling robotics and AI across such a large manufacturing base will require a lot of capital. We estimate Industry 5.0 could generate about $12 trillion USD of incremental industrial investment in China from 2026 through 2035. Around $5.5 trillion USD would go toward factory upgrades, including robotics, smart equipment, and software, while roughly $6 trillion USD would support new industrial capacity.
But that investment cycle is likely to build gradually. We expect industrial capex growth of about 4 to 5 percent annually in 2026 and 2027, before accelerating toward 6 to 7 percent from 2028 as excess capacity is absorbed, technology bottlenecks ease, and AI adoption broadens across factories.
If that investment translates into higher productivity, the economic impact could be meaningful. By 2035, China’s industrial profit margin could rise to 8 percent from roughly 5 today. Industry 5.0 could lift China’s potential GDP level by around 3.5 percent, helping cushion some of the drag from an aging population. And China’s share of global manufacturing value-added could increase from about 28 percent to 30 percent.
And those changes would not stop at China’s borders. Final assembly can shift to new locations, but the supplier networks, machinery and production know-how behind it are much harder to replicate. We estimate only around 40 percent of China-to-U.S. exports can be readily substituted.
That means China’s role may increasingly extend beyond exporting finished goods to supplying the equipment, components and industrial systems used to make them elsewhere. That is the move from Made in China toward Made by China.
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.

Fewer companies have been driving equity market gains in 2026. Our CIO and Chief U.S. Equity Strategist Mike Wilson looks at what investors should make of the narrowing rally as the year enters its final stretch.
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Mike Wilson: Welcome to Thoughts on the Market. I'm Mike Wilson, Morgan Stanley’s CIO and Chief U.S. Equity Strategist.
Today on the podcast I’ll be discussing the Market’s Bad Breadth.
It's Monday, September 28th at 11:30 am in New York.
So, let’s get after it.
The market is up this year. That's the good news. But over the last six weeks, I've been watching something that’s giving me pause. This rally has been carried by a shrinking group of stocks.
More than half of the Russell 3000 is at least 20 percent below its June highs and the S&P 500 forward multiple has fallen to 19 times, close to a new low for the year. Meanwhile, earnings growth is still running in the mid-teens for the median stock and revisions breadth is approaching cycle highs for the S&P 500.
That is not complacency. It is a market that has already done a lot of work to price higher energy costs, a tighter Fed, AI disruption, questions around returns on capital, and geopolitical risk.
Last week on the podcast, I noted that this is classic mid-cycle behavior. Earnings are absorbing lower valuations, and quality is taking the baton from the early-cycle winners. Groups that have led powerfully from the rolling-recession trough have been among the weakest areas recently: Autos, Semis, and short-cycle Industrials.
That is what tends to happen when the cycle matures and the Fed turns less friendly. The market stops paying for high beta. And starts rewarding free cash flow, stable margins, operating efficiency, and earnings that are still being revised higher. That is why I continue to favor large-cap quality, particularly asset-light, services-oriented, and fee-based businesses.
Having said that, there is still one problem to resolve. Breadth improved through most of the summer even as crude and yields moved higher. The deterioration came after Jackson Hole. That’s when markets began discounting a more hawkish Fed reaction function. The percentage of S&P 500 stocks above their 200-day moving average fell from roughly 75 percent to below 50 percent, while the index held up much better.
That divergence cannot persist forever. Either breadth catches up to price, or the index comes down to meet breadth. If bond volatility does not settle down soon, it could spill over into equity vol and we would see the S&P 500 price come down about 5 or 10 percent.
Frankly, I would welcome it. A final index-level correction is often how a multi-month correction beneath the surface ends.
There has been a lot of focus on the Fed’s recent pivot to rate hikes. However, the two-year yield is already above the level implied by the Fed’s projections. To me this suggests the bond market has been leaning too hawkish in the near term.
The bigger uncertainty is how the new Fed Chairman approaches liquidity and the balance sheet. He is more of a monetarist than his predecessors, and markets are still trying to understand what that means in practice.
My expectation is that the Fed ultimately provides liquidity if financial conditions tighten too far. But markets may test that resolve first. Bond volatility, funding stress, and whether equity volatility follows are the key signals. If those pressures ease, breadth can catch up and drive the market higher. If they do not, the index probably has more correcting to do.
There is also a new, constructive story developing for investors: AI adoption is moving from promise to practice. Companies with higher AI adoption are seeing stronger margins and earnings trends, but consensus still assumes many of those benefits fade in the out-years.
We think that’s too conservative. Productivity gains tend to compound, not immediately disappear. Earnings momentum is broadening from enablers to adopters, while adopter valuations have reset to more attractive levels. That supports a barbell approach – own select enablers where earnings durability justifies the premium, but increasingly own adopters where improving fundamentals are not yet fully reflected in expectations.
Bottom line, the market is not ignoring risk. It has priced the risks through lower valuations, weaker breadth, and major leadership rotations. What remains unresolved is the gap between a resilient index and a much weaker average stock.
The answer is that we probably see breadth improve and the index level come in before a surge to new all time highs. That’s why, I still want to overweight large-cap quality, but use October weakness to add to riskier stocks.
The market may need one more uncomfortable adjustment. But that may be exactly what sets up a stronger finish to the year. I will be here to guide you.
Thanks for tuning in; I hope you found it informative and useful. Let us know what you think by leaving us a review. And if you find Thoughts on the Market worthwhile, tell a friend or colleague to try it out!

Morgan Stanley Research analysts Michelle Weaver, Ravi Shanker and Dave Arcaro discuss two industrial inflection points: how long it will be before autonomous trucking becomes a reality and why power infrastructure is racing to keep up with AI-driven demand.
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Michelle Weaver: Welcome to Thoughts on the Market. I'm Michelle Weaver, Morgan Stanley's U.S. Thematic and Equity Strategist.
Ravi Shanker: I'm Ravi Shanker, Morgan Stanley's U.S. trade transportation analyst
Dave Arcaro: And I'm Dave Arcaro, Morgan Stanley's Utilities, Power & Clean Energy analyst.
Michelle Weaver: Today, what we learned at Morgan Stanley's Industrials Conference about the changing economics of autonomous trucking and the increasingly tight power market supporting the AI build-out.
It's Friday, September 25th at 10am in New York.
Now, I know we're all on the road taking meetings post-conference, so the audio might sound a little bit different, but we wanted to bring you the latest from our annual Industrials Conference that recently concluded in Laguna Beach, where two themes really stuck out. The growing physical infrastructure demands behind AI, particularly power, and the shift in autonomous trucking from proving the viability of the technology to commercializing it at scale.
Ravi, after roughly a decade of development, you've said autonomous trucking is entering a critical 12 to 18-month period ahead of serial commercial production.
What's changed, and why is the debate shifting from whether the technology works to whether it can be commercialized at scale?
Ravi Shanker: I think for 10 years the industry has been focused on making the technology work. but with players like Aurora now putting up almost half a million miles of fully driverless revenue-generating operations, on public highways in the U.S., day and night, rain and shine, for different customers. With people like Kodiak, also running, several trucks, in revenue-generating service, for customers like Atlas, I don't think there is much debate on the technology itself.
And so, I think the debate is now moving from does this work to can this work for me? Where the next steps are going to be dotting i's and crossing t's on the path to actually pressing these trucks into commercial service rather than having to prove that it works in the first place.
Michelle Weaver: Your research suggests that autonomous trucking can deliver roughly a 20 percent lower cost per mile, while higher utilization could be an even bigger source of value. What are the key assumptions behind that math? And what still needs to happen operationally for fleets to capture those benefits?
Ravi Shanker: Yeah, so we recently updated our TCO math, on autonomous trucks and published a North American insight, where we revised and revisited our views on autonomous trucking with a lot of proprietary data, in there as well. And part of that new TCO math, again, I think revisited some of the changes in the split of operating costs of trucking over the last several years.
First of all, I'll kind of throw a huge disclaimer out there that your mileage may vary, right? Because, depending on who you are as a trucker, if you're public or private, small or large, dry van or reefer, heavy or asset light, long haul or short haul, your split of costs are going to be slightly different.
But we started out, by looking at the ATRI's national average. And labor accounts for 35 to 40 percent of the P&L of the average trucker. So, when you take the driver out and substitute that with an autonomous driver, if you will. Even after paying the autonomous technology company roughly 85 cents a mile, for the autonomous operation, you will still save a significant amount of money. Versus the 40 percent of the roughly $3 per mile that it costs for labor today.
In addition to that, fuel is another third of your cost structure. And there, an autonomous truck should be anywhere from 13 to 22 percent more fuel efficient. We have taken the low end of the scale to be conservative. And then you layer on insurance savings, maintenance savings on top of that. Even if you add some incremental costs, either for human drayage at both ends or for the truck itself being more expensive – we believe you will save about 20 percent per mile versus a human driver today.
And I'll point out that the unit economic savings are only about a-third of the total savings with the utilization benefit driving another two-third savings on top of that.
Michelle Weaver: But there, there still seems to be a notable disconnect between how much freight carriers and shippers think can be automated and how much of the network may actually be suitable to be automated. What's the industry potentially underestimating?
Ravi Shanker: Yeah. We have seen this in our conversations. Again, part of our report was conducting detailed surveys and in-depth interviews with a lot of our coverage companies. And I will say that there still needs to be a lot of education, of how these trucks work, where they work, what the unit economics are going to be out there.
There's still a lot of misinformation. For instance, there's this big perception that you still need human drivers at both ends of an autonomous truck move because these trucks can only operate on a highway. And here's where our AlphaWise analysis, comes in. I think it's the first of its kind analysis where we use geolocation data to pinpoint 10,000 plus of the largest commercial facilities belonging to the hundred largest commercial shippers in the U.S.
And we found out that the average [00:05:00] commercial facility is less than two miles away from the nearest ramp point. And these trucks can comfortably do seven to 10 miles, if not longer, off a highway on main roads to get to their end destinations. So, I think you just need a lot of education in the industry.
And that is part of the dotting of i's and crossing of t's that we think the industry needs to do in the next 12 months before we see the start of serial commercial production next year.
Weaver: Thanks, Ravi. I want to bring Dave into the conversation here, and that question of turning demand into real world capacity brings us naturally to power, where the challenge is also increasingly about physical infrastructure and execution.
Dave, coming out of Laguna, you describe management commentary across power equipment as notably positive. What surprised you most about what you heard on demand bookings and project activity?
Arcaro: Yeah, absolutely. What surprised me most was probably how consistent the commentary was across companies, across large frame turbine providers and the smaller, on-site power equipment players, the new entrants and the more mature companies in the market. Very consistent feedback. All very positive.
And I would say also what surprised me too was the lack of disruption across the board. You know, we all see the headlines about data center moratoriums, political pushback, community challenges that really, it seemed, to increase the risk of data center execution and delays out in the market.
But at least with the power equipment companies, they're just not seeing it. You know, in terms of the feedback that we heard from management teams across the board at Laguna, they review project timelines actively with their customers, and that's all still intact. We haven't seen any changes in bookings or slot reservations for equipment deliveries.
Still seems to be a very stable and very strong backdrop across the board.
Weaver: One of the broader conference themes was the availability of power is becoming a bottleneck for AI infrastructure. How are equipment shortages, longer wait times, and customers planning further ahead affecting pricing? And how far ahead can the industry see?
Arcaro: Yeah, we are seeing equipment companies booking out orders farther and farther. The large frame gas turbines, to give you a couple examples, from companies like GE Vernova, they're now in conversations to contract turbines for 2031 and 2032. Smaller equipment companies like INNIO, who make, smaller scale engines for data centers, they're in conversations with customers and taking reservations into 2029 and 2030.
So, what we heard from the conference as well was that utilities, which is a big customer for this equipment, they're looking out farther and farther now into the 2030s. That's new and that's a surprisingly long time in terms of how far they're looking out. And we're also hearing data centers looking out toward the end of the decade, you know, late 2020s in terms of trying to secure their power equipment in advance.
We would still consider it very much a seller's market. Pricing has been rising, and companies at the conference gave further indications that it's likely to keep rising, what looks like into the 2030s from here. We just haven't seen any signs of softening yet, really regardless of the company or the equipment type that they're selling into the market.
So still farther and farther out that we're seeing visibility into the order flow, and with that is also coming firm and even rising prices into the 2030s.
Weaver: Investors often frame the power debate as electricity from the grid versus smaller power sources built on-site at data centers. Based on what you heard at Laguna, how should investors think about the balance between those two approaches?
Arcaro: Yeah, it's an interesting dynamic. When you talk to utilities and some of the large frame turbine companies, they all say that all this data center demand is going to the grid. Eventually, it's all going to go to the grid. When you talk to the smaller equipment manufacturers and the power as a service providers, they say nobody wants the grid.
They see long-term opportunities to sell, on-site power equipment and contract it with their end customers for 15 to 20 years, and we're seeing evidence of that. So, I think, it'll stay It's an ongoing debate among, investors as well. On our end, we think the on-site power market is going to be an extremely large market as we get toward 2030, given limitations in how much power is likely to be accessible from the grid over time for the data center industry.
But I would say, my takeaway and my observation from the conference that I would highlight is that it's a really favorable market and favorable backdrop for both sides.
Michelle Weaver: From autonomous freight to the power needed to support AI, one message from Laguna was clear. The next phase of technology adoption increasingly depends on what the physical economy can actually build and scale.
Ravi and Dave, thanks for taking the time to talk.
Shanker: Thanks, Michelle.
Arcaro: Thanks for having me.
Weaver: And to our listeners, thanks for listening. If you enjoy Thoughts on the Market, please leave us a review wherever you listen to the show and share the podcast with a friend or colleague today.