Thoughts on the Market

The Politics of Powering AI

October 12, 2026

The Politics of Powering AI

October 12, 2026

Energy costs are a key election issue and AI data centers are adding to the debate. Our Head of Public Policy Research Ariana Salvatore looks at policy discussions in Washington that could determine how the U.S. powers its next technological boom.

Morgan Stanley Thoughts on the Market Podcast

Transcript

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

 

Today, I'll discuss the growing energy demands of AI and what the government can do in response.

 

It's Monday, October 12th at 10am in New York.

 

Markets and policymakers are preparing for a potentially important debate following the November elections. The future of American energy infrastructure. And at the center of that debate is an increasingly urgent question: How can the U.S. build enough power infrastructure to support the AI investment cycle – without passing the costs on to everyday electricity consumers?

 

Late last month, lawmakers in Congress introduced the bipartisan American Affordability and Jobs Act. That legislation represents a significant effort to reform federal permitting. But importantly, it also includes provisions that require data centers to cover the transmission costs associated with their projects.

 

We think that's a notable development, particularly as we think about the legislative agenda after the November elections. Of course, the path forward still remains uncertain given substantial policy differences and a limited legislative calendar after the elections.

 

But why might this matter for markets?

 

Well, first, it's worth considering the scale of the energy challenge. My colleague Stephen Byrd and his team recently updated their projections for the U.S. data center power shortfall. They now see a potential 57-gigawatt gap through 2028, and that's before accounting for new solutions that could accelerate access to power. That's up from their previous estimate of 38-gigawatts.

 

And that's why the permitting proposal is so important. There are two elements that I'd highlight.

 

First is the effort to accelerate infrastructure development. The bill would reform federal environmental reviews and provide greater certainty for projects that have already received approvals. We think that can help reduce delays and uncertainty around new energy projects, although permitting reform alone won't resolve constraints involving equipment, labor, or grid capacity.

 

The second element is the growing focus on who pays for the infrastructure, and here the proposal actually builds on an existing policy initiative. Earlier this year, a number of hyperscalers signed on to the Ratepayer Protection Pledge.

 

That's a voluntary agreement under which companies commit to securing the electricity needed for their data centers and pay for associated power infrastructure upgrades rather than passing the costs on to residential consumers. The pledge was subsequently expanded to include a broader group of utilities, developers, and state participants.

 

Now, what's different about the permitting reform bill is its potential shift from voluntary commitments toward federal requirements. In particular, the proposal would require data centers to cover their associated transmission costs.

 

That's an area where we think policymakers from both parties appear to share concerns about electricity affordability, even though they may disagree over the broader approach to energy policy.

Looking beyond the elections, we think that creates two related policy catalysts for investors to watch.

 

The first is whether Congress can reach an agreement on permitting reform that helps accelerate the construction of energy infrastructure. And second, whether lawmakers move to establish a more formal cost-sharing requirement for data centers.

 

The eventual policy mix, we think, could influence both the timing and the economics of new projects. Faster approvals could make some investments more attractive. But requiring developers to absorb additional transmission costs could also change where projects are built and which power solutions they pursue. A changing policy framework could also reinforce the importance of alternatives.

 

Of course, legislation is far from guaranteed. The elections will shape the political environment in which these negotiations continue, and any final agreement could differ substantially from the current proposal.

 

But stepping back, I think there's a broader takeaway.

 

For much of the AI investment cycle, the focus has been on the pace of technological innovation and capital spending. Increasingly, though, policy decisions around electricity infrastructure, permitting, and affordability could become just as important in determining how quickly that investment translates into operational capacity.

 

The permitting bill is an early indication of how D.C. may approach those challenges after the elections. And for investors, the central question may be less about how much companies are willing to spend on AI and more about how quickly and at what cost they can secure the power needed to support it.

 

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.

 

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  • Ariana Salvatore

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Andrew Sheets: Welcome to Thoughts on the Market. I'm Andrew Sheets, Global Head of Fixed Income Research at Morgan Stanley.

 

Today, thinking about equity resilience in the face of rising bond yields.

 

It's Friday, October 2nd at 2pm in London.

 

The benchmark U.S. 10-year Treasury yield has risen about 100 basis points this year. Global equities, at the same time, are up about 13 percent. And those two facts sit in an uncomfortable tension.

 

After all, higher bond yields give investors better return options elsewhere, and they also make future corporate profits worth less today, which in theory should push stock prices lower.

But there's a wrinkle here.

 

That valuation theory actually has two moving parts. What we're referring to here is what we would call a dividend discount model or a Gordon Growth Model, where the value of a company today is worth the value of its dividends divided by the difference of its required rate of return and its growth rate.

 

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Over the last year, profits for the S&P 500 are up about 30 percent, and the earnings growth for the median company, well, that's still up in the mid-teens. Growth in Europe, Asia, and emerging markets have also been historically strong.

 

Indeed, if you'd told me on January 1st that the S&P 500 would be up about 13 percent, and at the same time, U.S. Treasury yields would be up about 100 basis points, I probably would have told you with reasonable confidence that stocks would look more expensive relative to bonds.

 

But they don't. The valuation of the equity market, the P/E ratio, has fallen significantly as yields have risen. But because earnings have risen so much more, stocks are still higher. And the so-called equity risk premium, the difference between the earnings yield and the bond yield, it's pretty stable year to date.

 

Now there's another way that higher yields could hurt the stock market. They could simply cause people to sell their stocks and buy those higher yielding bonds. But so far, we're not seeing evidence of that. The flows that we track continue to show money flowing into both stocks and bonds.

 

And the two markets are moving in the same direction day to day. They're showing positive correlation, which is not the outcome you'd expect if people were shifting money from one to the other.

 

There's also an interesting way that companies have a say in this debate. Investors every day look at the market and decide if these yields are high enough that they want to buy them. But companies look at the same yield and say, "Is this low enough that we would want to sell?" And so especially for the companies that are funding the AI build-out – these large technology companies with so much AI spending to do. Many of them, even at these higher yields, are still saying these are attractive levels to issue at. And are more attractive than, say, issuing more stock.

 

The other factor that's always important to keep in mind whenever we're debating long-term valuation questions between stocks and bonds, or really any asset class, is that valuation is a slow-moving force. It is often not terribly predictive of the next six or even 12 months. Indeed, if we think about the difference between the earnings yield on the equity market, the inverse of the P/E ratio, and what the bond market yields, that difference. Well, that difference only explains about 10 percent of returns between stocks and bonds over the next month.

 

Now, valuation is more powerful the longer you give it. And so, extend that horizon out over the next three years and that valuation gap between bonds and equities, well, explains about half the three-year outcome.

 

Markets are not equations that are solved once a quarter. They are ongoing arguments about the future. And when growth is strong, investors are simply more willing to give growth and that future potential the benefit of the doubt.

 

We think this goes a long way to helping to explain the equity market's resilience despite Treasury yields moving well above five percent. But it's also raising the bar.

 

Higher yields simply leave less room for earnings disappointment. Those profits need to keep growing quickly.

 

Thank you, as always, for your time. If you find Thoughts on the Market useful, let us know by leaving a review wherever you listen. And also tell a friend or colleague about us today.

 

Morgan Stanley Thoughts on the Market Podcast
Betsy Graseck and Michael Cyprys explore how AI could expand advisor capacity and tokenized assets...

Transcript

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.

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