August 4, 2026
Head of U.S. Public Policy Strategy Ariana Salvatore and U.S. Thematic Strategist Michelle Weaver, alongside Senior Economist and Strategist in Morgan Stanley’s Private Wealth Management Sarah Wolfe, examine the economics of the AI data center boom, the pushback and the policy implications.
Sarah Wolfe is a member of Morgan Stanley's Wealth Management Division and is not a member of Morgan Stanley’s Research Department. Unless otherwise indicated, her views are her own and may differ from the views of the Morgan Stanley Research Department and from the views of others within Morgan Stanley.
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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 ongoing transition in the economic recovery from early to mid-cycle.
It's Monday, August 3rd at 11:30 am in New York. So, let’s get after it.
Following on from my podcasts the past few weeks, I want to reiterate our key call that the economy and the market are moving from early to mid-cycle. That may sound like strategist jargon, but it has very real implications for leadership, positioning, and how one should think about the next phase of this bull market.
For much of the past year, the market was rewarding early-cycle characteristics and behavior. Lower-quality, higher beta stocks, and the most explosive earnings revision stories led the way. That made sense. We were coming out of a rolling recession, operating leverage was improving rapidly, and earnings revisions were accelerating off of depressed levels. But as the business cycle matures, the market typically becomes more discerning. It starts to ask a harder question: not just who can grow, but who can sustain that growth with stable earnings, strong margins, and free cash flow generation. In other words, quality starts to matter again.
That’s exactly where we are now. The rotation towards quality has begun, and I don’t view that as a bearish development for the broader market even if it’s bad for some of the former leaders. The S&P 500 is a very high-quality, large cap index. So, while the market may continue to consolidate in the near term, the quality rotation should ultimately support index resilience and help the S&P 500 work its way toward our 8000 year-end target.
The big market event last week was the capitulation in the historic momentum unwind. Momentum sold off hard, and semiconductors were at the center of it. That shouldn’t surprise anyone who has followed our work over the past several months. We’ve been using the silver-stock analog to think about semis, and remarkably, the semi index bottomed almost exactly where that analog suggested. That argues for a tradable bounce in semiconductors over the next few weeks. However, the more important point is that semis may struggle to reclaim leadership for the rest of the year. Semis are a classic early-cycle group, and this is increasingly becoming a mid-cycle, quality-led market. The silver-stock analog would support the same conclusion.
The provocative way to say it is this: the AI cycle is not over, but the easy money in the most crowded AI beneficiaries may be. The AI investment cycle still has plenty of runway, but the market is no longer rewarding capex blindly. It’s asking for evidence of return on invested capital, adoption, monetization, and operational discipline. Last week’s performance gap between Microsoft and Meta was a perfect example. It wasn’t random. It was about capex discipline. The market is rewarding more prudent spending and that could translate into a real overhang of the capex beneficiaries and in line with my views for the past several months.
That is why I still prefer hyperscalers over semis, with one important caveat: dispersion within the hyperscalers is rising. The group has already outperformed semis by 30% over the past four weeks, and I think it can continue over the next several months. Hyperscalers have resilient core businesses, exposure to the AI application layer, and an underappreciated ability to use AI to reduce operating expenses if needed. They’re both enablers and adopters. But the market will no longer treat them all the same. The winners will be the companies that can show return on investment, communicate capex discipline, and preserve earnings quality.
This is also why AI adoption is becoming so important. The next leg of the story is not just about who builds the infrastructure. It’s about who can use it more effectively. Our work shows that companies where AI is material to the investment thesis and pricing power is neutral to strong, are already seeing margin expectations improve. Relative net margins for that group have expanded by 50 basis points in just three months and they now sit nearly 400 basis points above the broader market. That’s not hype. That’s operating leverage with a new engine.
The Fed is the other major piece of the puzzle. Chair Warsh stayed on hold last week, but he remains tight-lipped about his reaction function. Markets are still adjusting to a Fed that wants to rely less on forward guidance and more on unfiltered market signals. I think that’s a healthy development over the longer term, but transitions are rarely smooth. The biggest risk to this consolidation turning into a correction is if 10-year yields rise above 5%. Such a rise could weigh on equity multiples and force the Fed to either change back to its old ways of guiding the markets or provide more liquidity to calm rate markets.
Bottom line, the bull market is not over, but it is changing. As we move from early to mid cycle in this recovery, the equity market wants higher quality. Semis may bounce, but they are unlikely to be the leader again. Meanwhile, hyperscalers will likely continue to trade better with the best ones exhibiting more capital discipline. More importantly, AI adoption is moving from promise to measurable margin benefit. This is what mid-cycle looks like. Less forgiving, more discerning, but still constructive for investors who follow the rotation rather than fight it.
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!
Michelle Weaver: Welcome to Thoughts on the Market. I'm Michelle Weaver, Morgan Stanley's U.S. Thematic and Equity Strategist.
Michael Zezas: I'm Michael Zezas, co-director of the Morgan Stanley Institute and Deputy Global Head of Morgan Stanley Research.
Jessica Alsford: And I'm Jessica Alsford, Morgan Stanley's Chief Sustainability Officer, and also co-director of the Morgan Stanley Institute.
Michelle Weaver: Today: how AI, energy, geopolitics, and industrial investment are competing for scarce resources – and what that competition could mean for markets.
It's Friday, July 31st at 10am in New York.
Jessica Alsford: And 3 pm in London.
Michelle Weaver:
Mike and Jess, as co-directors, you speak with people across the firm to identify the biggest questions facing companies and investors, especially the important ones that may not have clear answers yet. And to understand how those questions are shaping client conversations.
Mike,
Michelle Weaver: What's one of the questions that you think investors are wrestling with the most right now?
Michael Zezas: So, one of the biggest questions is how several major investment cycles can happen at the same time. AI, energy infrastructure, manufacturing, and defense may all be competing for the same power, the same skilled labor, equipment, and capital.
So, investors need to look beyond each theme in isolation and ask where constraints could delay projects, raise costs, or redirect spending, and which companies are best positioned to manage all of that.
Michelle Weaver: Since the institute began, you've examined a number of topics, including AI, energy resilience, and geopolitical fragmentation, just to name a few. Jess, which topic has been the most compelling to you?
Jessica Alsford: It's difficult to pick one because, to be honest, for me, it's really the way that AI, energy resilience, and geopolitics have all really become one story. If you think about the energy transition, which has been playing out for a number of years. But now we also have the AI build-out, and that depends on reliable and affordable power. And then geopolitical shocks, which are demonstrating the need for countries to have energy security.
So, if you put all of this together and you can really see that there is a huge need to scale the global energy system, but using all types of power available to us, including renewables and nuclear.
Michelle Weaver: Mike, how is that intersection that Jess spoke about between AI, energy, and geopolitics altering the way that companies are thinking about investing?
Michael Zezas: So, geopolitical shocks, they're more norm than exception now. The situations in Iran, Ukraine, Venezuela, they all reflect an evolving international order where the U.S. is less interested than it used to be in preserving global security and trade standards.
And that's a particular problem in a world where companies and governments spent much of the last 50 years optimizing to benefit from globalization. So basically, looking for the lowest cost way to produce things, sourcing materials and labor in the most efficient way possible, presuming that the frictions in international goods and services trade would just keep getting lower.
That's obviously not the case now, and whether it's a good idea or not, the trend is toward governments leaning into industrial policy to prioritize supply chain security and protect whatever it sees as their national competitive advantages. And really that's correlated with higher trade barriers.
So, that means that while companies are still focused on efficiency, they have to build resilience through more regional supply chains, greater redundancy, and investment in strategically important capacity. So, the practical message from our teams is to map critical dependencies, diversify where possible, and be realistic about the extra cost of resilience rather than assuming the old globalization model will simply return.
Michelle Weaver: One of the clearest constraints on the AI build-out is energy. Our thematic research team is estimating a nearly 40-gigawatt shortfall in power needed for data centers. For context, this is multiple New Yorks worth of power.
Jess, how significant of a limiting factor is power becoming?
Jessica Alsford: Power is definitely becoming a strategic constraint. If you think about grid connections, these can take years to set up. And so, access to power really is going to determine where facilities are built and how quickly they're able to come online. And it looks like there won't be one universal solution.
You've got natural gas, nuclear, renewables, storage, microgrids. They're all going to need to play a role. And for companies, that means that they really are going to have to be planning power alongside the site and financing. For investors, it means focusing on reliability, affordability, and permitting, not just headline demand.
Michelle Weaver: So, AI, energy, and geopolitics can no longer be considered in isolation. As countries and companies rethink where they source, build, and invest, where do you see the biggest opportunities emerging?
Jessica Alsford: The opportunity is likely to be broader than any single sector, to be honest. and the institute has shown that capital really needs to be flowing towards more resilient supply chains as well as new productive capacity and also the infrastructure that supports both of these. And this covers power, grids, automation, logistics, as well as data.
I'd also say that location matters, too. And companies need to be able to weigh political stability as well as skilled labor, reliable energy, and policy support. And investors should be looking for markets and businesses that can turn those advantages into durable returns.
Michelle Weaver: The institute has also looked at founders as a source of economic information. Jess, what can their decisions reveal before those changes appear in traditional economic data?
Jessica Alsford: So, founders are often making decisions at the leading edge of growth and capital formation, and so their behavior can provide an early read on both at-risk appetite and also financing conditions.
If we take the current macro environment as an example of this, the institute has shown that many founders are adapting rather than simply waiting, and this means extending fundraising timelines, spawning investor conversations, and considering private credit, structured equity or tender offers.
For companies, the takeaway really is to preserve financing flexibility. And for investors, it's to watch how those choices can reshape private market liquidity.
Michelle Weaver: Mike, to bring this back to where we started, if power, labor, and capital are all becoming more constrained, what should investors be watching most closely?
Michael Zezas: Yeah. I'd watch whether capital spending plans are being delayed or resized or redirected in some way, and I think importantly, the reasons would be for any of those things happening.
Is there a constraint around power or labor or equipment permitting or financing? Those details help distinguish whether you'd be looking at temporary setbacks or a structural shift. So, something that would signal that we've built too much capacity in AI or manufacturing relative to demand. And that's the type of thing that would be a real headwind to the economic outlook and potentially create problems in the credit markets.
But to be clear, we don't see demand flagging anytime soon. And so, for investors, it's less about whether to be bullish or bearish on the outlook for the markets and the economy, and it's more about looking for companies that are durable beneficiaries of these trends. So those are ones with secure inputs, flexible balance sheets, and realistic return thresholds.
Michelle Weaver: Absolutely. As Mike said, we don't see demand slowing, and we're seeing a lot of encouraging data points around AI adoption. One analysis we did recently shows that around 25 percent of S&P companies are now quantifying the benefits they're seeing from AI adoption. And this diffusion story is only going to continue to grow.
Mike, Jess, thanks for joining me.
Michael Zezas: Thanks Michelle.
Jessica Alsford: It’s great speaking with you both.
Michelle Weaver: And to our listeners, thanks for tuning in. If this is all piquing your interest, you can find the institute's articles, roundtables, and future work on Morgan Stanley's website. And as always, if you enjoy Thoughts on the Market, please leave us a review and share the podcast with a friend or colleague.
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