Thoughts on the Market

Robotaxis are accelerating along the road to commercial viability. Auto and Shared Mobility Analysts Andrew Percoco and Tim Hsiao discuss what this rapid development means for global investors.
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Andrew Percoco: Welcome to Thoughts on the Market. I’m Andrew Percoco, Head of North America Auto and Shared Mobility Research.
Tim Hsiao: And I'm Tim Hsiao, Greater China Auto and Shared Mobility Analyst.
Andrew Percoco: Today, why robotaxis may be approaching a commercial inflection point. It's Thursday, August 13th at 8am in New York.
Tim Hsiao: And 8 pm in Hong Kong.
Andrew Percoco: So Tim, for years, robotaxis were really confined to limited pilot rollouts across the globe. You've done a lot of work over the last few weeks. We put out a big collaborative report on the robotaxi market and how it could be a $1 trillion TAM by 2040.
What makes this moment different than some of the other robotaxi hype cycles that we've seen in the past?
Tim Hsiao: We observe four things have been converging. Firstly, end-to-end AI is improving much faster. Secondly, hardware and the training costs are falling. And thirdly, more well-capitalized players can fund deployment. And last but not least, regulation is becoming clearer.
The leading operators are no longer just demonstrating the technology. They are running fully driverless services around the clock and generating commercial rides. So in our view, the questions has been shifting from can it work to who can expand operating areas, raise utilization and lower costs at a much faster pace.
So that's a very different setup versus the 2018 and 2021 hype cycles.
Andrew, U.S. autonomous miles could rise from 116 million in [20]25 to 16 billion by 2032. But still make up only about 0.5 percent of all miles driven. How can robotaxis become a meaningful business while remaining such a small part of the market?
Andrew Percoco: I would say, you know, obviously the U.S. mobility and transportation market is a massive market. So even with the rapid growth that we expect in robotaxis, it's going to take a long time to make a material impact in the overall market share of mobility.
But if you think about the profit pools in this business, 16 billion miles at $2 a mile can, you know, pretty quickly become a very significant TAM and market opportunity.
And I think, you know, fundamentally, if you think about a robotaxi business, I would argue you're better utilizing an asset... Or if you think about the, you know, car park, the amount of vehicles that are, you know, in the fleet today or in the U.S. today, they're sitting idle 90 percent of the time, right?
So you're talking about taking a smaller amount of volume and driving a higher utilization on that fleet and driving much improved economics. So yes, it's going to take time to displace the, you know, hundreds of millions of cars that you have on the road in the U.S. and displace the penetration of miles driven.
But ultimately, you know, we think that the profit pool and the opportunity in robotaxis are much more attractive for the entire value chain, as it relates to robotaxis. And I'd say there's a few things that we're watching along the way to make sure that, to your point, you know, this is not another hype cycle. And that there's real commercial backbone to this business.
I'd say the first is seeing the rollouts continue to improve, and the density of the rollouts improve across the select cities that we've seen in the U.S. right now. Robotaxis are only available in a handful of cities in the U.S., so we want to see that continue to expand into more cities. But also the density of the fleet increase in the cities where they're currently present.
And at the same time the safety side is still something that gets a lot of questions in making sure that it is truly safer than a human driver, across technology platforms, right? There's various players in this market with different approaches to technology. So, I think seeing that the safety curve is starting to or continues to improve is going to be very important for the viability of this market going forward.
Obviously U.S. is very different from China. What have you seen in China? China has shown some impressive growth and utilization in some of the operators that are on the road in China. So just curious as to your perspective in terms of what you're seeing on the ground there.
Tim Hsiao: I think China shows that there's much in operations and skill challenges as technology challenges. The fleet in China is above 5,000 vehicles across I think more than 7500 square kilometers in key cities. And some operators average more than 20 orders per vehicle per day.
So, total cost of ownership has fallen roughly 30 to 40 percent, while remote assistance ratios are moving from like one operator for like 20 to 40, even like 50 to 60 vehicles. And we think it will achieve like one for a 100. So that has produced real break-even happens, especially in some major cities like Guangzhou, Shenzhen, Wuhan – the tier one, tier two cities.
So in our view, I think in China, wider operating domains, fleet density and utilization rate, as you just mentioned, reinforce one another. So make it some more like the real commercial case. Instead of just, like trials as we saw a couple years ago.
If more value shifts towards the software, fleet operation, and the data, as well as the customer relations, how does that change the profit pool, across the auto industry, especially in the U.S.?
Andrew Percoco: First off, I think the auto industry in general is becoming, you know, more software focused and aware. You know, it's being led by the robotaxi market where the autonomous driving software and technology is obviously the most important part about getting this technology to market.
That is ultimately trickling down to personally owned cars where you're seeing more autonomous technology being deployed. Auto OEMs are able to charge subscription revenue for this software. So it expands, I'd say, the value proposition of buying a vehicle expands the profit pool for the OEMs.
It changes in some ways the cyclicality, or can change the cyclicality of the industry if you've got more kind of recurring revenues, subscription like business model versus just a hardware focused OEM model, which has been kind of the predominant focus for the OEMs historically.
I'd say the other angle, interesting angle here is, you know, as this business scales, there's gonna be a lot of vehicles on the road. There's gonna be a lot of fleets of vehicles on the road. Those need to be managed by somebody or some company, right? So if you think about, you know, the rental car industry, right? These companies have been in the business of managing fleets and renting out fleets for a very long time. They know how to do that very, very well.
I think there's an interesting opportunity for that part of the value chain, to participate in aiding these robotaxi fleet operators, in scaling and bringing their business to market. Charging, maintenance, reconditioning, all the things that take a lot of time and a pretty large amount of physical infrastructure.
That's an opportunity for the rental car industry to come in and leverage their existing know-how to help. And, you know, I think Tim, an important part of this commercialization process is driving down the cost structure of robotaxis. They are very sensor; heavy sensor heavy. They're very compute heavy. I think China is the clear leader on cost and supply chain. I think in China you're seeing robotaxis, you know, around $35,000 to $40,000, which is considerably lower than what we see in the U.S. today.
So, how do you think that that will accelerate adoption in China, but I'd say more importantly overseas as some of these robotaxis businesses look to expand outside of China.
Tim Hsiao: In our view, it could be a major accelerant because as we noticed that the depreciation is still one of the largest fixed costs for robotaxi. So, as we just mentioned, I think, $35000 to $45000 US dollars, the purpose-built robotaxi can lower the breakeven utilization threshold. And make it easier to finance fleets and open cities that could not support the $150,000 US dollar vehicle.
And not only in China, because globally, I think the Chinese cost deflation can be paired with the local ride-hailing platforms in the overseas market that provide demand and regulatory access. But as we highlighted in our previous, the global reports once again, we don't think the cheap vehicle is sufficiently by their self.
So in our views, on top of the competitive cost structure, registration, data localization, insurance, and local operating costs can still delay the margin curve, particularly in Europe, which we think there are still quite a lot of uncertainties.
So Andrew, as we just, as we just discussed, the lower vehicle costs help, but the operating model still has to work, right? So with operating costs expected to fall and the margin potentially moving above 30 percent or even higher at scale, what are the key assumptions investors should focus on?
Andrew Percoco: There’s a handful of key assumptions you need to sensitize to get to that 30 percent or more margin structure in this business. I'd say the first is going to be utilization, right? You need to be running these assets at a high utilization to essentially amortize those fixed costs over a larger number of miles driven.
Number two, insurance today is probably one of the largest buckets of cost when we think about this business. Insurance is, from our perspective, a big unlock for this industry as the safety, as we mentioned before, the safety data continues to improve. We think that will be a reason to, to expect that the insurance costs associated with autonomous driving technology and robotaxis will continue to decline.
It's about 30 cents per mile on our estimate, so it's very significant in terms of the overall cost structure of robotaxis. Drivers or where there's the most sensitivity around the model. Obviously, there's charging costs, there's maintenance costs. Those are, I think, fairly known at this point. But the utilization and insurance, I think, are the two biggest drivers of really getting that margin profile to improve over time.
Tim, I guess when you think about the next, call it 10 to 15 years, I think we will put out a trillion dollar market by 2040 from a TAM perspective.
What do you think the biggest markets are that investors should be watching, in terms of getting us to that trillion dollar TAM? Obviously, U.S. and China are kinda leading now, but what are the next markets people should be watching?
Tim Hsiao: In addition to the major market, as you just mentioned, the U.S. and China, in our views, I think we also need to focus on markets like Europe, the Middle East and Southeast Asia. I think their scale is underappreciated, as we highlighted in our previous report. Because if you think about that, Europe, the Middle East, and Southeast Asia in aggregate have roughly four million taxis together ride-hailing vehicles.
So even with 25 percent conversion, they imply that about one million is the L4s vehicles. The Middle East offers supportive regulators, you can tell, simpler operating environments and higher fares. And if you think about the Southeast Asia, the ASEAN, I think the market has dense demand and strong local platforms.
And of course, Euro markets definitely can't be ignored because Euro will move more slowly, because we think the regulations and the data rules would initially add cost. But the truth is, if you think about the European market, I think the taxis or ride-hailing fares are among the highest globally, even compared to the U.S. and rest of the world.
So in our view, the material margin could be more attractive. And this market, on top of the U.S. and China, in our view, can support several regional winners. So, not only limited to a very, you know, the single one or two markets.
Andrew Percoco: Yeah, it’s great Tim. It sounds like, you know, the robotaxi race, if you want to put it that way, will be won by those who can really bring together technology, and a compelling cost structure while also following the proper regulations and making sure the safety is improving at a rate that's acceptable to regulators.
So, Tim, thanks for taking the time to talk today.
And thanks 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.

The potential path to a durable U.S.–Iran agreement has twists and obstacles ahead. Our Head of U.S. Public Policy Research Ariana Salvatore discusses current negotiations and the impact of recent developments for investors.
Disclaimer: Important note regarding economic sanctions. This report references jurisdictions which may be the subject of economic sanctions. Readers are solely responsible for ensuring that their investment activities are carried out in compliance with applicable laws.
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Ariana Salvatore: Welcome to Thoughts on the Market. I'm Ariana Salvatore, Head of US Public Policy Research at Morgan Stanley. Today, the latest on U.S.-Iran tensions, talks, and the path to a deal.
It's Wednesday Aug 12th, at 2 p.m. in New York.
The diplomatic picture in the Middle East has shifted yet again.
Last week, there was growing optimism that the U.S., Iran and Oman could reach an arrangement to improve commercial passage through the Strait of Hormuz. But the two sides have since hardened their positions.  This week, we've seen some bouts of escalation, and headlines have been mixed over the past few days.
At the same time, the energy security picture remains complicated. The U.S. administration says the seven-day average of oil leaving Hormuz has risen to almost 9 million barrels per day. But traffic remains well below normal conditions, and the risks we think are no longer limited to the Strait. We’re beginning to see potential for disruption across multiple regional chokepoints and alternate shipping routes.
That brings us back to the framework negotiated nearly two months ago. The U.S. and Iran signed a Memorandum of Understanding in mid-June. It was intended to create a 60-day window for negotiating a more durable agreement. That framework addressed commercial passage through Hormuz, the U.S. naval blockade, sanctions relief and frozen funds – as well as longer-term negotiations over Iran's nuclear program. But the implementation has proven much harder than agreeing on the framework itself.
So where are negotiations getting stuck?
First, there's the Strait itself. Iran has tied a full reopening of the Strait to a broader package that includes an end to the U.S. blockade, sanctions relief and compensation. Washington, in turn, is trying to preserve economic leverage and appears unwilling to provide those concessions upfront.
Second, sanctions sequencing: The U.S. wants relief tied to clear signs of progress, while Iran is seeking confidence that any relief is durable and not easily reversed.
And third, there’s the nuclear question: enrichment levels, Iran’s existing stockpile, and a longer-term verification framework. These are still to be negotiated. That’s likely to take longer than the 60-day time period.
So, what’s the right framing here for investors?
We think it’s not necessarily a deal or no deal binary. It’s more so a series of partial agreements, implementation tests, setbacks, and renewed negotiations. After the June deal was signed, we flagged several live paths to re-escalation: execution risk around sanctions and Strait control, a potential divergence between the U.S. and Israeli objectives, domestic political pressure in Washington, and the basic challenge of resolving core nuclear questions within such a short time frame. We think those risks are now becoming more visible, but we think both sides have strong incentives to avoid a return to a full conflict, like the type of engagement we saw back in March of this year.
Moving forward, the signposts we laid out in June—maritime normalization, access for the International Atomic Energy Agency, sanctions implementation, military restraint, and rhetoric—all remain the right trackers to watch. But expect the bargaining process itself to be noisy, unstable, and non-linear. Rather than a clean transition from conflict to ceasefire to final deal, the more likely path will have fits and starts.
So what should investors do with that information?
On oil, our commodity strategists remain constructive on prices, given the ongoing supply uncertainty and the emergence of new chokepoints across the region. Altogether, they see those constraints keeping the market relatively tight compared to the levels we briefly saw in June when the MOU was signed.
If there’s another sharp rise in oil prices, our U.S. equity strategists think that could be a key risk to the near term outlook. Our U.S. economists agree, but also think the Fed would need a bigger shock than markets previously expected to resume hiking. As a result, we expect the Fed to stay on hold this year.
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 CIO and Chief U.S. Equity Strategist Mike Wilson discusses a new market cycle, in which investors are demanding more than just growth from companies.
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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 look at an important shift in what the market wants to see from companies going forward.
It's Tuesday, August 11th at 11:30 am in New York.
So, let’s get after it.
This week I am going back to our broadening thesis – but with a slightly different twist.
Earlier in the year, broadening was about beta. It was about the market moving beyond a narrow set of mega-cap winners and rewarding economically sensitive areas as the rolling recovery took hold.
In the last few episodes I’ve talked about how that phase is now over. And we’re moving from an early-cycle broadening into a mid-cycle quality rotation. In short, the market is no longer demanding just growth – but growth with durable earnings, strong margins, and free cash flow.
To be clear, the broadening in earnings is still very much alive. Russell 3000 median stock earnings growth is running at 15 percent, the strongest since 2021; while median sales growth is at 8 percent, the best since 2023. At the same time, 87 percent of S&P 500 companies are beating earnings expectations this quarter, and earnings revisions breadth has rebounded to 23 percent, with 76 percent of industry groups showing positive revisions breadth.
However, headline earnings are no longer enough for stock outperformance. The market is saying, ‘Show me the money’— and that’s exactly what should happen in a mid-cycle transition. When companies raise both earnings and free cash flow estimates, they are rewarded. When they only raise earnings and not free cash flow, the market is much less forgiving. Investors are no longer paying indiscriminately for growth. They want cash conversion.
This is also why I think AI adoption remains such an important theme. The market is increasingly rewarding companies that can demonstrate real efficiency gains from AI, not just talk about the open-ended opportunity in abstract terms.
That is a very different phase for the AI cycle. The first phase was about building the infrastructure. The next phase is about who uses it well. Companies that can translate AI adoption into better margins, better productivity, and better free cash flow should continue to be rewarded. In other words, AI is becoming less about the promise and more about the evidence.
That framework tells us where to be positioned. I continue to favor quality and AI adopters. Within Financials, I prefer large-cap Financial Services, particularly Insurance and Capital Markets exposed businesses, where earnings revisions are inflecting and our regime analysis remains supportive. Within cyclicals, I like Discretionary Goods, where the wallet-share shift from services to goods, improved pricing, and better earnings revisions all point to catch-up potential.
In Tech, I continue to prefer hyperscalers over semis. Semis can still participate tactically, especially after recent momentum unwinds, but the hyperscalers offer a better multi-month risk-reward. They have resilient core businesses, attractive relative valuation, and underappreciated optionality around AI-related ROI and adoption. Just as important, they are not only enablers of AI, but they are early adopters. They have the flexibility to spend less if the market becomes more demanding about capex discipline.
In terms of remaining market risks for this year, I’m still watching interest rates and oil very closely. A gradual rise in nominal yields alongside strong economic and earnings data is not necessarily bearish. In fact, historically, that has been one of the better environments for equities because it brings back my ‘run it hot’ theme. Stronger nominal growth supports revenues and earnings. The problem is not the level of rates. It is the pace of change. If back-end yields rise too quickly, the cost of capital becomes a headwind for stock valuations.
Bottom line, the broadening is still happening, but the market is raising the bar. Early-cycle beta is giving way to mid-cycle quality. Earnings are broadening, but free cash flow is also necessary to be fully rewarded. AI is still an important market driver, but the market wants measurable benefits and the leadership is becoming more selective within sectors rather than across them.
This shift may make the market feel less euphoric in the short term, but also healthier and more sustainable in my view. This is not a market that is simply chasing momentum any more.
It is starting to separate the companies that can simply talk about growth from the companies that can convert it into durable free cash flow and longer-term value.
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!

Our U.S. Consumer Finance Analyst Jay Bacow and our Co-Head of Securitized Product Research Jay Bacow explain why AI can transform the way Americans shop for, manage and refinance their mortgages.
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Jeff Adelson: Welcome to Thoughts on the Market. I'm Jeff Adelson, Morgan Stanley's U.S. Consumer Finance Analyst.
Jay Bacow: And I'm Jay Bacow, Co-Head of Securitized Products Research, also working at Morgan Stanley.
Jeff Adelson: Today, how AI could change the way Americans shop for, manage, and refinance their mortgages.
It's Monday, August 10th at 10am in New York.
The U.S. mortgage market is worth more than $14 trillion, and its performance ultimately depends on the choices millions of homeowners make. Today, refinancing still means shopping around, comparing offers, and working through a lot of paperwork. AI could make that process much easier, especially when rates begin to fall.
Jay, you led this work on our AI mortgage blue paper. What's the main way AI could change the mortgage market, and why does the borrower matter so much?
Jay Bacow: So we think the biggest change would be borrower adoption of using AI agents to manage their personal finance. An agent on your phone could just monitor mortgage rates, compare lenders, reduce the paperwork, and make homeowners more likely to refinance when the economics work.
Let's think about what that could be. Historically, only about 30 percent of borrowers that had the ability to lower their mortgage rate by a 100 basis points did so in a given year. When a borrower went to get a mortgage quote, less than half of them asked more than one lender for a quote.
That agent could go reach out to 30 lenders, ask for a variety of different mortgages, could upload all the documents, could do this all effectively instantaneously, present the homeowner with the best option. Allow the homeowner to effectively click a button and refinance. I think this could be pretty transformative for the mortgage market.
Jeff Adelson: Now, as we think about this transformation, Jay, mortgage investors still rely heavily on past refinancing behavior trends. If AI makes borrowers more likely to refi[nance] when rates fall, how could that change the way these investors value mortgage-backed securities?
Jay Bacow: Well, we all know that past performance is not indicative of future performance, and those models are likely to understate future prepayments. If you get a faster response, it's going to make mortgages more negatively convex.
That's going to make the durations shorten. It's likely to widen mortgage spreads by about 10 basis points in our base case. And now, if that base case were to happen and we get, let's call it 100 basis point rally in the future, we think that that could cause something like a 40 percent pickup in refinance volumes versus our current expectations of what refinance volumes would look like in that 100 basis point rally.
Jeff, you cover a lot of the largest mortgage lenders. What does this mean for their business model?
Jeff Adelson: So, it's pretty straightforward. More borrowers refinancing means more loans for the industry to originate. Today, we're still sitting below what I would describe as normalized levels of originations.
We're sitting at about $2 trillion of mortgage originations per year. As we think about normalized, we think that's somewhere in the order [of] around $2.5 trillion. So just that $600 billion alone could get us straight there.
We tend to think about this more in our bull case, where we could see something in the order of $3 trillion of originations or more, still below what we saw during the peak COVID years of about $4 trillion or more. But still pretty meaningful and material for the industry.
Now, for the scaled lenders, that can create meaningful operating leverage. Mortgage companies have historically had to hire aggressively when volumes rise, and then they've had to reduce headcount when the cycle turns. AI could allow them to process more loans with the same employee base, making their cost structures more flexible and reducing the need to rebuild capacity during every single refi[nance] wave.
But the earnings benefit we don't think will necessarily match the dollar benefit from volumes. If AI makes it easier for borrowers to compare offers and allows every lender to process more loans, then competition could intensify and pressure gain on sale margins. So the opportunity is a larger market and better productivity.
The key question for individual lenders is: how much of that volume can they capture without giving too much back through pricing?
Now, as we think about automation, Jay, it could bring in more loans, but could also intensify competition and reduce the profit lenders can earn when they originate and sell a mortgage. So, how should investors in your space weigh those two effects?
Jay Bacow: So, the mortgage investors are short the option to the mortgage homeowner of when they can refinance.
And if the mortgage homeowner is going to be more efficient about refinancing, the mortgage investor is going to need to get paid more for that. They're going to demand wider spreads, and they're particularly going to demand wider spreads where that option that they're shorting is worth more. That's generally how it's going to play out, but there's also other aspects as well.
That duration shortening, because the borrower's more likely to refinance, means that the investors that own that duration will need to buy some more duration against that. You're also going to see more demand for duration as rates rally. So it's going to be a bid for the low strike receivers, as our options experts will pay close attention to.
And then if we get a further rally, you also get a more of an impact across the consumer writ large. You can imagine a world where mortgage rates are substantially lower than they are right now. An agent could sit there and say, "Why don't you consolidate your debt between your credit card, your auto loan payments, maybe your student loan payments and your mortgage?" Allowing consumers to save more and then maybe spend that in the economy.
Jeff Adelson: If we maybe take it a step beyond refinancing, how could AI affect home sales, homeownership, and access to home equity?
Jay Bacow: So let's just go back to thinking about this agent that's on your phone that's looking at all the opportunities.
Traditionally, right now, most people are only calling up one lender, they're getting one quote. If your agent is looking at lots of different lenders and lots of different options, you're probably going to get more ability to take out a mortgage. So you're going to get an expansion of the homeownership rate.
That's going to create more demand for housing. As rates rally, you're going to get home sale activity picks up more than it used to, and people are also going to be more able to take advantage of the equity they have in their house. So, you're going to get more usage of second liens and HELOCs and cash-out refinance activity.
Once again, we think this is mostly going to happen three to five years down the road, but we're not really sure exactly how this is going to play out.
So Jeff, what would be some of the signs that people could look at to see if it's playing out in the three to five-year timeline that we're expecting – or slower, maybe even faster?
Jeff Adelson: Sure. So yeah, I mean, I think it's going to be similar to what we've already observed as consumers ourselves and what we're seeing with all the LLMs and AI tools we're adopting today. You should see some rapid advances in the ease of use and the adoption of these technologies from a forward-facing, client-facing perspective. What we all see in the websites, what we all see in the apps.
It should become easier for us to engage with the mortgage process, compare rates to actually step into the process. Whereas today, you still need to maybe speak with a bank officer, a loan officer, or a mortgage broker to get deeper into the process and actually better understand what your rate means today.
So that would be the first step. The second step would be closing speeds. The average originator today still takes about 40 to 45 days to close a mortgage. The biggest and largest originators that have invested the most in technology and AI today are closing at about, call it, 12 to 20 days. So, half the industry level. So, that should come down over time and make it much easier to actually apply and finish a mortgage.
And then quite frankly, the most obvious answer would just be at the given level of rates that are outstanding today, we should see a step up in the level of refi[nance] volumes. That would be the most obvious one. But that'll be the outcome of everything else we've talked about rather than the actual cause.
Jay Bacow: That makes sense. So faster refinancing, it's likely to make the mortgage market more responsive when rates fall and effects that are going to reach well beyond the borrower.
Jeff Adelson: That could mean higher volumes for lenders, quicker prepayments for investors, and wider swings across housing and rates markets.
Jay Bacow: Jeff, thanks for taking the time to talk.
Jeff Adelson: Great speaking with you, Jay.
Jay Bacow: And thank you all 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.

Our Head of U.S. Public Policy Research Ariana Salvatore explains how U.S.-China tensions, export controls and domestic regulation are reshaping where AI is built, who controls it and what investors should watch.
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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, a look at how government is increasingly determining the future of AI in the U.S. – from where it's built to which technologies US companies and consumers can use.
It's Friday, August 7th at 10am in New York.
AI is rapidly reshaping the economy and society, so this is a pivotal moment for government to consider the rules governing that development. The first area to watch is technology restrictions, particularly in the context of U.S.-China competition.
Now, for much of the past decade, the government's approach has been to restrict a relatively narrow group of technologies with clear national security implications while maintaining broader commercial ties. But as export controls spread across more sectors of the economy and AI moves from software into physical infrastructure, the definition of what qualifies as national security has become broader.
The Department of Commerce could, for example, expand the entity list. That would require US cloud providers, software companies, and model marketplaces to remove or stop supporting models tied to designated Chinese developers.
Congress could then make those restrictions more durable through things like the annual defense bill or other policy vehicles. We're keeping an eye on several legislative proposals, like the AI Overwatch Act, which would tighten controls and give congressional oversight around exports of the most advanced AI chips; and the MATCH Act, which would extend restrictions further upstream to semiconductor manufacturing equipment and seek closer alignment with allied producers.
These measures wouldn't directly ban Americans from using a Chinese model, but they could constrain China's ability to train future frontier systems.
But it's not just the US that could impose a set of restrictions. China has a parallel set of tools focused more on integration and market access. Regulators could block four models or APIs. They could require locally controlled deployment. They could impose Chinese data and content standards or use cybersecurity and entity list authorities to promote domestic substitutes.
The likely result is an increasingly distinct pair of AI ecosystems. That's our two worlds thesis in practice. Over time, we think that means a bifurcated global AI market into separate technology ecosystems.
That looks like the U.S. relying on export controls, allied supply chains, and largely closed frontier model platforms, while China emphasizes domestic hardware, open-weight models, subsidized compute, and localization. Over time, that bifurcation could produce different chips, models, standards, data rules, and distribution channels, while third countries navigate between the competing stacks.
The second area to watch is domestic regulation. Today, the landscape is pretty fragmented. States are moving first on certain specific issues, including automated decision-making and child safety. Now, at the same time, Congress is confronting competing objectives from industry, consumer groups, and national security officials.
So far, we think the evidence suggests that the administration's preference is for a light-touch approach, a largely voluntary national framework rather than a broad new licensing regime. But it's also moving toward more direct oversight of the most advanced models. That includes the possibility to play a more active role prior to model release to ensure that certain protections like cybersecurity and intellectual property are met.
Publicly outlined priorities from industry seem to broadly overlap with that approach: a consistent federal framework, clearer liability standards, access to data, compute, and power, and copyright rules that don't materially limit model training.
But of course, the industry isn't monolithic. There are some important nuances between frontier developers and other players.
So, what does all this mean for investors? The government's reaction function will be critical to the way AI is developed and diffused throughout our society in two key ways.
First, we see regulation altering not only the pace, but also the geography of AI infrastructure.
At the same time, we think these constraints could strengthen the investment case for bottleneck solutions like on-site power generation, fuel cells, storage, and more.
Second, greater technology bifurcation supports investment in parallel supply chains.
The key takeaway here is that the government is no longer simply regulating the industry from the sidelines. It's helping to determine how fast AI develops through domestic rules, where it develops through infrastructure, permitting, and sovereign AI policy, and which technologies are accessible through export controls and market access restrictions.
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.