Thoughts on the Market

Morgan Stanley Podcasts
  • 4.9 (66)
  • INVESTING
  • UPDATED DAILY

Short, thoughtful and regular takes on recent events in the markets from a variety of perspectives and voices within Morgan Stanley.

  1. 2D AGO

    The New Playbook for Real Estate Net Lease Investing

    As real estate values reset and cap rates widen, net lease is back in focus—but the approach has changed. Ron Kamdem and Hank D’Alessandro explain. Read more insights from Morgan Stanley. ----- Transcript ----- Ron Kamdem: Welcome to Thoughts on the Market. I'm Ron Kamdem, Head of U.S. REITs and Commercial Real Estate Research.  Hank D'Alessandro: And I'm Hank D’Alessandro, Managing Director on Morgan Stanley's Real Estate Investing Team and Vice Chairman of Private Credit.  Ron Kamdem: Today: a part of real estate that's changing fast and drawing fresh attention from investors. Net lease investing.  It's Friday, May 8th at 10am in New York.  You might not think you invest in net leases. But there's a good chance you do, especially if you have money in a pension fund or another income generating vehicle. Net leases are the kinds of long-term lease assets that can help generate steady, predictable income.  They are no longer a sleepy corner of the real estate market. In fact, they're changing in some really interesting ways.  Ron Kamdem: So, Hank, for listeners who know the term but may not know the structure, what exactly is net lease investing? And why does it tend to come up more often when markets get more uncertain?  Hank D'Alessandro:   At a high level, net lease investing is typically associated with long-term leases that can offer durable income streams; typically growing streams, which is why it's often seen as a more defensive part of real estate investing. We see that when investors are thinking more carefully about geopolitical risks, market volatility or say portfolio resilience, this durable cash flow derived from mission critical assets and long lease durations with fixed annual rent bumps can become especially attractive to investors.  Also, with higher inflation likely, net leases are generally insulated from increases in expenses given these are the responsibility of tenants. But what's important today is the net lease is broader than many people realize, both in terms of the property types involved and the range of investors participating in the space.  Ron Kamdem:   Let's stay on that idea of a broader market for a moment, because one of the biggest shifts has been the growing role of private capital in the space. What are you seeing there and why does it matter?  Hank D'Alessandro: Well, listen, Ron, there's no question. The role of private capital has grown substantially, including through joint ventures and public real estate vehicles. That matters because it tells you that the sector is attracting a wider range of investors than it has in the past, such as pension funds, insurance companies, sovereign wealth funds. And retail investors are increasingly investing either through traditional locked up funds or through semi-liquid funds. But it can also change the competitive landscape and can influence how capital gets allocated across the opportunity set.  Thus, one's approach going forward from an analysis perspective will need to evolve. More broadly, it's a sign that net lease is being viewed as highly relevant in today's market, not just as a legacy category within real estate.  Ron Kamdem: And that's an important distinction that you make right there, because not all investors are approaching these assets the same way. So, when private capital comes into the space, what separates their underwriting approach from another? And we hear all the time about private credit. How does that play into this?  Hank D'Alessandro: Well, Ron, you know, as we discussed previously, the competitive landscape is changing and therefore underwriting is absolutely critical in this part of the cycle. And so, we believe underwriting both tenant credit, of course, is very important. But we equally analyze the real estate underwriting because we believe that real estate can be a real differentiator over time – both in terms of returns and risk profile.  We think that strong real estate underwriting with strong tenant credit underwriting, both enhances returns over time and reduces risks. So, therefore, that matters a lot. We also believe that by focusing equally on the real estate underwriting, you get a fuller picture of the risk and value, especially as net lease expands into newer property types.  It is an easy nuance to miss, but we believe this distinction is becoming much more important differentiator in how investors assess opportunities in the sector today. And I believe that the most successful managers will do a good job underwriting both tenant credit and real estate. So, Ron, for a long time, many investors thought of net lease primarily as a retail story. How much has that changed?  Ron Kamdem: Well, that's changed quite a bit. If I take you back 20 to 30 years ago when you thought of net lease, you thought of a convenience store that's, you know, 5,000 to 10,000 square feet. But today, that opportunity has expanded well beyond retail and there's much more attention now on industrial assets. And even increasing discussions around areas like data centers.  I'll give you an example. Realty income made its entry into the data center vertical in November 2023 with a $200 million build to suit JV. That shift matters because it shows net lease evolving alongside where demand and capital are moving.  It also means the sector is becoming more connected to larger structural trends in the economy, rather than being viewed through one traditional lens. At the same time as the mix broadened, investors have to be selective because not every new category will have the same long-term profile that we're used to. So, as investors look at some of these newer areas, where do you see the best opportunities, Hank? And where would you be more cautious?  Hank D'Alessandro:  So first, opportunities. The industrial segment has clearly become a major area of focus. This sector benefits from growing e-commerce penetration fueled by AI, reshoring of manufacturing, and increased defense spending. The ability to acquire mission critical distribution centers in top tier logistics markets or advanced manufacturing assets in innovation clusters is particularly appealing in today's macro backdrop.  Another area that we find very compelling is medical outpatient buildings where the aging demographics can support long-term demand. So, we have great conviction on both of those.  Now, turning to area where we're more cautious. There's been a lot of attention on data centers, you know, as you previously mentioned. But that's an area where investors really need to think carefully about long-term durability. Questions around obsolescence, technological change and whether certain assets fit a true buy and hold strategy are very relevant and need to be considered carefully by investors.  So, maybe to sum up, the opportunity set is definitely broadening, but selectivity in terms of location, asset type and asset specifications remain essential.  So, Ron, the idea of linking property types back to long-term trends feels especially important right now. How do you connect this conversation to the key secular themes Morgan Stanley research is tracking this year. AI and tech diffusion. The future of energy, the multipolar world, and societal impacts. And can you offer a few examples?  Ron Kamdem:   There's a couple ways that net lease connects to these broader themes. The first, which is probably the most obvious, is technology diffusion and the future of energy comes through in areas such as datacenters, and that's been a key focus for public investors.  When you think about societal change – that's relevant for sectors tied to demographics like medical outpatient buildings, where you know people go get different services. And multipolar world theme matters because deglobalization and geopolitical fragmentation. Or influencing how investors think about resilience, location, and portfolio construction, which is driving incremental demand for industrial real estate linked to supply chain shifts and defense spending.  So, this is no longer just a sector evolving on its own, it's becoming more closely tied to these macro issues, shaping investment decisions more broadly. And once you widen the lens to that macro backdrop, the conversation naturally becomes more global.  In fact, we saw realty income now generates 19 percent of rents across nine European countries with more than $15 billion invested since 2019. Given this, Hank, how should investors think about net lease and adjacent opportunities outside of the U.S.?  Hank D'Alessandro:   The global angle is clearly becoming more relevant. There's growing interest in Europe and the U.K. And one area that comes to mind in this context is retail parks, where rents have reset, yields are wider, and tenant resilience has improved.  Thinking more broadly, international markets can give investors a wider set of ways to think about real estate opportunities tied to the same themes that we've discussed. And add to diversification, as macro drivers continue to diverge and geopolitical risks remain elevated. Even when structures or sector exposures differ from the U.S., which undoubtedly they will, the bigger point is that investors are increasingly valuing opportunities through a global lens.  Ron Kamdem: So, if we pull all this together, what looks like a simple-income oriented category is actually becoming much more nuanced. As we wrap up, Hank, what's the main message you want investors to take away about net lease today?  Hank D'Alessandro: You know, I believe the main takeaway is that net lease remains relevant because of its defensive qualities, and predictable contractual cash flows derived from long-term leases. But the story is becoming more nuanced, requiring a granular focus on the credit, and importantly, the underlying real estate.  With real estate values down 20 to 25 percent from peak levels, replacement cost has elevat

    12 min

  2. 3D AGO

    Special Encore: AI’s Next Big Leap

    Original Release Date: April 28, 2026 Tom Wigg and Stephen Byrd discuss the accelerating pace of AI breakthroughs, the forces driving them and why the next phase of development may look very different from anything we’ve seen so far. Read more insights from Morgan Stanley. ----- Transcript ----- Tom Wigg: Welcome to Thoughts on the Market. I’m Tom Wigg, Head of Specialty Sales in the Americas at Morgan Stanley, and a sector specialist in Technology, Media and Telecom. We wake up every day to new AI product releases, so it’s easy to lose sight of the unprecedented non-linear improvement in AI capabilities. But things are about to get weird. It’s Tuesday, April 28th at 8am in New York. The market has been thinking about AI in linear terms. But we need to reframe that assumption of only incremental improvement and think about exponential improvement. That was my takeaway from a conversation with Stephen Byrd, Global Head of Thematic and Sustainability Research at Morgan Stanley. In our conversation, we zeroed in on Stephen’s bull case for broader AI model improvements. Tom Wigg: First, I want to talk about one obsession that you’ve been writing about for the last several months – is this idea that we’re going to see nonlinear improvements in the frontier models coming out this spring. Stephen Byrd: Yes. Tom Wigg: There’s been, you know, some big headlines around new models, benchmarks coming out publicly. Is this, you know, your bull case playing out on these models? And what are the implications? Stephen Byrd: Yes! Absolutely, Tom. So we have, to your point, we are obsessed. And I know I’m not shy about that – with the nonlinear rate of AI improvement. It is the most important impact to so many stocks that I can think of in the sense that it can impact all industries, all business models. So, what we’ve been saying for some time is, if you look back over the last couple of years at the relationship between the amount of compute used to train these LLMs and the capabilities, we have a very clear scaling law. And approximately the law is, if you increase the training compute by 10x, the capabilities of the models go up by 2x. Now, as you and I’ve talked about this a lot; just meditate on that for a moment. I think things are about to get weird in the sense that on the positive side, we’re going to see all kinds of underappreciated capabilities across many industries. So this disruption discussion, I think, is going to spread, but it’s also going to require investors to, kind of, be more thoughtful about what they do with that concept. Meaning you can’t sell everything. In the sense that AI will disrupt some businesses. I actually think this is healthy in some ways because now it forces investors to really look at each business model and assess which is going to get disrupted, which can get supported and enabled by AI, which are immune. Because there are some business models that actually are immune. But essentially from here, Tom, I’d say we are expecting through the spring and summer to see multiple models that are able to perform a much greater percentage of the economy at better levels of accuracy at incredibly low cost. Which I know you and I have talked a lot about the cost of actually doing this work from the LLMs. This is massive. This is going to impact so many industries. I think this is all to the good for the AI infrastructure plays because it shows the importance of getting more intelligence out into the world. Tom Wigg: So, you mentioned the constraints we’re seeing across compute, memory and power. It seems like most of the CEOs of the labs and hyperscalers are talking about this. Investors are bullish in terms of the ownership in, you know, memory, optical, semi-cap, et cetera. But the question I’m getting more recently is around what’s the ROI on all this spending. And does the market action in these hyperscalers, which have been pretty bearish year-to-date, force a cut on CapEx? So, maybe if you can marry that with what you’re picking up on the ground in terms of compute spend and whether the frenzy still continues, you know, versus the ROI? And, like, what could happen? Stephen Byrd: Yeah. The short answer – I’m going to go through detail – is I think the bullishness is going to get more bullish over the coming months. And let me walk you through a couple of the mathematics and then just what I’m seeing on the ground to your point, Tom. So the mathematics. We have a token economics model that looks from the perspective of a hyperscaler or an LLM developer in terms of – if they sell their token at a certain price and you fully load the cost of a data center and all associated costs, financing, you name it – in what are the returns? And the bottom line is the returns are excellent. The other element we spend a lot of work on, and you and I talk a lot about, is the demand for compute. In this world where the LLMs are increasing in capability and the token usage goes way up with agentic AI, video world models, all that stuff, we think that there is a massive shortage of compute. So, if you’re lucky enough to be a hyperscaler with the compute, with the power, we think that they will have a lot of pricing power on the tokens. Let me explain why we see price power on the tokens. Now I’m going to flip to the perspective of an adopter. Let me give you just rough mathematics. There was a study last year from one of the big labs showing that on average, an enterprise user using an LLM might be able to replace work that would take about one and a half hours from a human. That would save about $55 of cost. A million tokens, depends on whether you’re looking at input or output – but let’s just call it $5 for a million tokens. The average usage case today for a fairly complex agentic task in an enterprise setting is in the tens of thousands of tokens. Okay? So let’s just do that math again. $55 of savings. A million tokens cost $5, and a typical agentic usage is far less than the million tokens today, though that will accelerate. The economics are a home run for adopters. So, we’re in a situation where compute is very scarce. I see pricing power all over the place for those who have the compute and have the power. Tom Wigg: So, when you put it like that, Stephen, it seems so inevitable and obvious. But I wonder why the hyperscalers are trading the way they are? And when do they see the revenue inflection you’re talking about? Is this like a stay tuned kinda 2026 event? Is this something we have to wait for for 2027-2028? Like, how do you think this flows through to the extent that the market will get more comfortable that all this free cash flow pressure is worth it on the other side? Stephen Byrd: Yeah. This is, in short, I think this is a 2026 event. But let me dive into that because what you just asked is so important for so many stocks. So, let’s talk through this. The capabilities of the models are advancing so fast that the average corporate user is not yet keeping up. There is this gap. But that will happen quickly, and we’re seeing signs from these labs of revenue at the lab level that is accelerating. So that’s a good sign. What we’re seeing, though, among fast adopters is those adopters who really understand the capabilities are quickly realizing just how economically beneficial there is. An example, one of my best friends founded a software company many years ago. Last month was – that was the last month in which his programmers wrote code. They’re done with writing code. The efficiency benefits for his business are absolutely massive. But he feels like he’s just scratching the surface, and he’s about as technically capable as anyone I know. He has two PhDs in the subject matter. He’s very, very good. So long way to say that we’re living in almost two worlds where the fast adopters will show what’s possible. The average utilization for enterprises will still take some time. But I do think that the market will react to what they see from the fast adopters in the sense of – the tangible economic benefits are so big. Now, on the ground, what I’m seeing on the infrastructure side, my friends in power tell me that a couple months ago is when they saw the sense of urgency from the AI community go up a couple of notches for them to get the infrastructure they need. So they saw this explosion in compute coming. In the last two months, the weekly usage of tokens according to OpenRadar is up a couple hundred percent in a couple months. So, I do think we’re seeing this. So, this is; it’s happening quickly. What I would say is the market will have these signposts in every industry of early adopters showing this benefit. I think that’s enough for us to start to get bullish. We also… I just think when you look at the demand for compute, the compute numbers need to go up. And with that, you know, everything in the AI value chain, infrastructure value chain, the volumes need to go up. Tom Wigg: One bear case that I wanted to interrogate was – there’s one view that, yes, there’s a token explosion right now. But it’s because the first use case is coding. Which is inherently, you know, very developer-friendly and token-intensive relative to other knowledge work. Can you talk about, you know, whether you subscribe to that? Or whether the token intensity will be as high or lower as this expands to other areas of knowledge work in the next several years? Stephen Byrd: Yeah, it’s a great question. The short version is that, yes, it’s true that software usage is more token intensive. However, what we’re going to be seeing – we’re starting to see it – is in almost every knowledge-based job, we’re going to move to agentic AI. And when we do that, you tend to see an explosion in compute. Let me walk you through the numbers. There are a couple studies that show essentially when yo

    10 min

  3. 4D AGO

    How Long Can Markets Ignore the Oil Supply Shock?

    Despite the historical energy disruption from the Iran conflict, stocks are back to record highs. Our Global Head of Fixed Income Research Andrew Sheets and our Head of Commodity Research Martijn Rats discuss different views and fundamentals driving markets. Read more insights from Morgan Stanley. ----- Transcript ----- Andrew Sheets: Welcome to Thoughts on the Market. I'm Andrew Sheets, Global Head of Fixed Income Research at Morgan Stanley. Martijn Rats: I'm Martijn Rats, Head of Commodity Research at Morgan Stanley. Andrew Sheets: Today: oil, oil inventories, and the price at the pump. It's Wednesday, May 6th, at 2pm in London. Martijn, it's great to talk to you. We remain in this very unique market where on the one hand, the energy market is severely disrupted. On the other hand, we're making new all-time highs in the stock market. And part of this debate is a creeping sense that maybe the energy market is just a lot more resilient than many people initially thought. So, let's just jump right into it. As you look at the current state of the world, the state of things, how are you seeing the energy market at the moment? Martijn Rats: There are definitely two views in the market. I would say commodity specialists, oil traders, people that trade oil and gas equities for a living, tend to focus on the size of the supply shock. And it is neither hyperbole nor disputed that the size of the supply shock is the largest in the history of the oil market. We have the statistical data to back that up. That is not a controversial statement. But at the same time, the other view in the market, generally held by your generalist investors who invest across many markets. They tend to focus on the likelihood or possibility that this supply shock might also be uniquely short. It was there all of a sudden, from one day to the next, the strait was closed. It felt a bit man-made, so to say. It was an outcome of a political decision, and that can also be undecided. And so, this is – the to-ing and fro-ing in the market is; on the one hand, this shock is very, very large. But the other hand it may also be very, very short. Now we went into this supply shock, arguably well-prepared. In the sense that during the course of like late 2024, all of 2025, and the very early part of 2026, we were telling a story of oversupply surplus. And on top of that, given the military buildup was going on in January and February, a lot of countries in the Arabian Gulf – Saudi Arabia, the UAE, Kuwait – visibly put out a lot of oil at sea. So, in the oversupply of 2025, we put oil in storage in lots of places that we can't always see. But that seems very likely. Oil in the water was very, very high. So, we have been living off these buffers, and that has helped. And then, yeah, at any point in time, there were good enough reasons to assume that on a timeframe of a couple of weeks, this would largely be resolved. We would eat into these buffers, draw some inventory. And it has been hard for the market then to really capitalize the size of the supply shock and say, "Yeah, really oil prices need to spike very, very high." And in that sense, we’re left with this significant supply shock, but we haven't taken out the highs that we saw in 2022, for example. Andrew Sheets: So maybe a way to think about this, right, is that if we imagined all of that oil as sitting in a big tank. We've kind of stopped a lot of the flow into the top of the tank as the Strait of Hormuz has remained closed. But oil's still able to drain out of the bottom, kind of, like normal because that tank is being drained. Those inventories have been drawn down. Maybe that's a quite a crude analogy, to forgive the pun. But how long can that last? I mean, if we think about these inventories, if we think about the speed of which they're being drawn down; and I think that's an important point that you mentioned, that these inventories were unusually high going in. But they're obviously not unlimited. Where does that stand? And I guess, you know, what is the limit of that? How long can those inventory draws last? Martijn Rats: Yeah, yeah. To say that this is the billion-dollar question would be understating it, Andrew. It's also a unusually complicated question to answer in the sense that it depends very heavily on the region, on the product that you're looking at. Jet fuel in Europe, NAFTA in Asia, you might see something sooner. But other products in other regions, you know, might take longer. We often don't really know where the operational limitations of inventories are. Globally, we see something like 8 billion barrels of oil in some form of storage. That is an enormous amount. We can't draw that down to zero because a lot of that is there for operational, like working capital type reasons. Just to facilitate the operations of the industry. Is the floor seven? Is the floor six? These things are hard to answer. Andrew Sheets: You’ve got to have some oil in the pipeline to make the pipeline flow… Martijn Rats: Exactly, exactly. You can't operate a refinery if you don't have at least some storage right next to it. It just doesn't work. So, these things are hard to know. But I would say that we are eating through these buffers very, very re-rapidly now. Oil on water has largely normalized and is no longer elevated. We are seeing very large inventory draws across every data point that we have on refined products. Refined products are universally drawing. On crude, the data is more patchy. But we are seeing large inventory draws now coming through in the United States. I would say – and this is partly having worked with this data for a long time and sort of developing some market feel rather than very analytical spreadsheets, so to say. But I would say that if the flow of oil through the Strait of Hormuz does not resume on the sort of next four to six weeks, we will get very, very tight by June, early summer. And, well, look, I mean, from there, it's simply… You know, if you then were to forecast. You know, project forward from there on. It would be getting tight by August, September. But of course, that's done under the assumption that the flow remains impaired over that period, which I would say most market participants would not assume at the moment. Andrew Sheets: And another point that comes up sometimes, at least in my conversations, is, ‘Oh, but, you know, maybe Venezuelan oil is going to be coming online.’ There's more investment. The U.S. seems very focused on increasing oil output in Venezuela. You know, can that match in any sense the scale of what we've had disrupted here? Martijn Rats: No, that is a complicated issue in the sense that, you know, growing oil production takes time. It takes capital, it takes equipment, it takes a lot of people. Venezuela at the moment, produces a bit more than a million barrels a day. I'd have to say, like, relative to the size of Venezuela's production, the last two monthly data points have actually come in better than expected. But you're talking about 100,000 barrels a day, 200,000 barrels a day, that sort of thing. Relative to a supply shock that is 13-14 million barrels a day. The fastest ever single amount of production growth of any country in any year was 2018. U.S. shale with natural gas liquids included grew 2 million barrels a day in a single year. But yeah, even that… Andrew Sheets: So, 2 million barrels relative to 14 million barrels lost is… Martijn Rats: Yeah, exactly. Andrew Sheets A drop in the bucket.   Martijn Rats: And that had a huge run-up of several years of putting the infrastructure in place to do that. I mean, it…. You don't turn it on a dime either. So no, that remains difficult. Andrew Sheets: So, you know, maybe a dynamic to close with is actually another way that I think people care about the oil price, you know, besides their portfolio – which is they drive. And, you know, you had a great stat in your report that one out of every 11 barrels of oil that's produced ends up in an American car. And the U.S. is a big producer. Its inventories have been drawing down. There are clear signs that the U.S. is exporting a lot of energy, and as a result, gas prices are also going up in the U.S. So, you know, what… If you could just talk a little bit about the move in gasoline and maybe, you know, I think this could be a good segue into this idea of distillates into, kind of, parts of refined product. And how those prices can deviate or not from the barrel of oil we often talk about. And then even just more generally, kind of what is the price at the pump that people might need to think about as you head into the summer – assuming, you know, this conflict is still somewhat uncertain. Martijn Rats: Yeah. So, the United States is very interesting at the moment. In the sense that the regular discourse about the United States is that the United States is energy independent because it is a net oil producer. And at the most aggregate level, that is correct. But that doesn't mean that the United States is not connected to the rest of the world from an oil market perspective. I would say actually it's the opposite. The U.S. oil market is deeply connected to the rest of the world. It is a net exporter because there are very large imports, and there are very large exports, and it just happens so that the exports are a little bit bigger than the imports. So, it's a net exporter. But flows in both directions exist for every product – for crude, for diesel, for gasoline. So, the U.S. should be the last place to have physical disruptions because the supply is close to home. But in the end, it's so connected; that in the end, there's only one global oil price – and we all pay it, including in the United States. Now, because of the deficits at the moment, in Asia, to [an] extent in Europe, there is a very large pool on oil from the United States, and we're seeing that across the board. Crude oil exports we

    12 min

  4. 5D AGO

    AI’s Shift From Thinking to Taking Action

    Our Head of Europe and Asia Technology Research Shawn Kim discusses AI’s move from passive chatbots to active agents—and how this influences tech supply chains. Read more insights from Morgan Stanley. ----- Transcript ----- Welcome to Thoughts on the Market. I’m Shawn Kim, Head of Morgan Stanley’s Europe and Asia Technology Team.  Today: A foundational shift in the development of AI and its broad market implications.  It’s Tuesday, May 5th, at 3pm in London.  Think about the last time you asked a chatbot to write a summary or a draft. Or maybe answer a query. It was probably useful. But you were also still driving the interaction: asking, refining, copying, checking, and moving the work forward.  Now imagine a system that does not just respond, but acts. It remembers what you asked last week, understands your preferences, works across digital tools, plans a workflow, and adapts as circumstances change.  That is the shift from GenAI to agentic AI: from AI that helps with thinking to AI that helps with doing. GenAI is mostly passive. It takes a prompt and produces an answer. Agentic AI is active – less a copilot for one task but an autopilot for multi-step workflows.  The distinction is key because computing requirements are changing. In GenAI, large language models and GPUs handle much of the thinking. GPUs, or graphics processing units, process many calculations in parallel, making them central to modern AI models. In agentic AI, CPU becomes more important. CPUs, or central processing units, coordinate tasks and connect systems to the broader digital infrastructure.  Agentic AI also depends on three stacks: the brain, or the large language model; orchestration, where the CPU manages the doing; and knowledge, which is memory. Memory may be the most important layer. An agent that knows your preferences, documents, tone, and task history becomes more useful over time. That creates a context flywheel. The more context it collects, the more personalized it becomes, and the harder it is to leave.  Typically, in computing, we think of memory as storage, mainly. We need to rethink this. Memory is also continuity. When an AI system can use past experiences, memory becomes a long-term state, shared knowledge, and behavioral grounding.  And that matters because LLMs have fixed context windows. Once a conversation exceeds that window, older content falls off. For simple questions, that may be fine. But for a coding agent working across a large codebase over days or weeks, it is a major limitation. Serious work requires persistent memory, short-term orientation, and active retrieval – remembering prior decisions, understanding changed files, and finding relevant codes without the user pointing to every dependency.  For investors, the implication is clear – agentic AI changes the bottlenecks. We see CPUs as the new bottleneck, with memory seeing the highest content increase. We estimate as much as 60 percent, or $60 billion of incremental CPU total addressable market by 2030, within a total CPU market of more than $100 billion. We also estimate up to 70 percent of incremental DRAM bit shipment tied to this theme.  That makes us more positive on supply chains including memory, foundry, substrates, CPU and memory interface, and capacitors and CPU sockets. These areas benefit from content growth, pricing power, and capacity constraints into 2027.  As AI moves from answering questions to taking actions, investors should watch the infrastructure behind the shift. Because in the agentic era, the next big AI leap may be less about the prompt, but more about the processor.  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.

    5 min
  5. Hard Lessons: Rick Rieder

    5D AGO

    Hard Lessons: Rick Rieder

    Introducing a recent episode of Hard Lessons, featuring Rick Rieder, BlackRock’s CIO for Global Fixed Income and Head of the Global Allocation Investment Team, in conversation with Seth Carpenter, Global Chief Economist and Head of Macro Research at Morgan Stanley.  Watch and listen on your favorite podcast platform.

    1 min

  6. 6D AGO

    Why Stocks Keep Rallying

    Our CIO and Chief U.S. Equity Strategist Mike Wilson explains the factors behind stock gains across sectors. Read more insights from Morgan Stanley. ----- Transcript ----- 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 why earnings remain the most important variable for equity markets. It's Monday, May 4th at 2pm in New York.   So, let’s get after it. The more I think about what’s been driving this market, and the more time I spend with the data, the more I keep coming back to the same conclusion: it’s earnings. Not the headlines, not even the Fed. Earnings are doing the heavy lifting right now. When I look at this reporting season, what stands out isn’t just resilience, it’s strength that’s broader than most people appreciate. The typical company in the S&P 500 is growing earnings at about 16 percent, and the median earnings surprise is running around 6 percent. That’s the strongest we’ve seen in four years. What’s really interesting to me is that this strength is no longer confined to just the biggest tech names. Yes, hyper scalers and semiconductors are still playing a leading role, but the story is expanding. We’re seeing earnings revisions move higher across Financials, Industrials, and Consumer Cyclicals, in particular. That kind of breadth tells me this isn’t just a narrow leadership story; it’s something more sustainable. At the same time, many investors are focused on the geopolitical backdrop, particularly the Iran conflict and what it means for oil, inflation, and supply chains. To be fair, companies are feeling some of that pressure. When you listen to earnings calls, you hear about rising freight costs, tighter supply chains, and higher input prices across industries like chemicals and machinery. But here’s the nuance: those impacts are uneven. They’re not hitting the entire market in the same way. In fact, at the index level, they’re being offset. Energy has become a positive contributor to earnings growth, and the higher-end consumer remains relatively strong. Even with higher fuel costs, we’re not seeing a meaningful pullback in overall consumption – at least not yet.  That tells me that we’re not dealing with a classic demand shock. We’re dealing with a redistribution of pressure, and companies are adapting. In many cases, they’re passing through higher costs. Revenue surprises are running above historical norms, which suggests pricing power is improving. Now, of course, earnings aren’t the only piece of the puzzle. Policy still matters, and the shift in rate expectations this year has been meaningful. The Fed has clearly become more concerned about inflation, and the market has repriced expectations to fewer cuts, and maybe even a higher probability of hikes. That repricing is a big reason why valuations corrected so sharply over the past six months. It’s notable that even with that headwind, equities have managed to stabilize, thanks to earnings. When earnings are growing at an above-trend pace, equities can deliver solid returns regardless of whether the Fed is cutting or not. That said, I do think that there’s one area of risk that deserves further attention, and that’s liquidity. We’ve seen periods of funding stress over the past six months, and those moments have coincided with pressure on valuations. The Fed and the Treasury have stepped in at times to stabilize these conditions, helping to reduce bond volatility and support equity multiples. Bottom line, we have already had a meaningful correction in valuations this year with price earnings multiples falling 18 percent from their peak last fall. That adjustment occurred as the market digested the many risks that we have been highlighting. Meanwhile, earnings are not only holding up, they’re accelerating and broadening across sectors. The risks that we’ve all all focused on – geopolitics, oil, supply chains – are real. But they’re being absorbed at the company level. As a result, the price declines were much more modest than the compression in valuations.  Meanwhile, monetary policy is providing some headwinds, but it’s not overwhelming the earnings story. Equity markets move on two things: earnings and liquidity. Right now, earnings are more than offsetting the lingering liquidity concerns. In short, earnings growth is greater than the valuation reset. This is classic bull market behavior and as long as that continues, I think the U.S. equity market will grind higher for the rest of the year with intermittent bouts of volatility.  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!

    5 min

  7. MAY 1

    AI and Jobs: What Data and History Say

    Our Global Chief Economist and Head of Macro Research Seth Carpenter discusses whether the economy can adapt fast enough to turn AI into a productivity boom rather than a labor market shock. Read more insights from Morgan Stanley. ----- Transcript ----- Seth Carpenter: Welcome to Thoughts in the Market. I'm Seth Carpenter, Morgan Stanley's Global Chief Economist and Head of Macro Research.  Today we're going to try to look past the hype and the anxiety around AI and ask what will be the effect on the labor market.  It's Friday, May 1st at 10am in New York.  Now, odds are that you've used AI to draft an email or summarize a document, maybe learn about a new topic, help plan a trip. The new technology is clearly lowering the cost of certain tasks. And I think the research shows that there are plenty and an increasing number of tasks that AI can do better than most humans. But that's not really the question.  What I hear all the time is, ‘Well, if we can get the same amount of output with less labor, then surely millions of people will lose their job.’ I think the same logic also implies that we can just get a lot more output from the economy using all the labor that we have. And the difference between those two views really is at the heart of the debate.  So far, I would say the data allow for some cautious optimism. Despite rapid advances in AI capability and evidence that adoption is spreading, the broad labor market indicators still show remarkably little disruption. Economic growth is holding in there. The unemployment rate is not rising rapidly. If anything, it's ticked down recently. Job openings are not soaring, and separations do not suggest that there's systematic weakness in AI exposed industries.  Now, productivity data are beginning to show perhaps a bit of AI's positive effects, but they don't show the mass displacement that many people fear. According to our research, industries with higher AI exposures have recorded stronger labor productivity gains, driven mainly by faster output growth rather than fewer hours worked. And that distinction for me is critical. So far, the evidence looks like workers are producing more than firms are cutting back on labor.  There's also a physical constraint. AI adoption depends – and will continue to depend – on infrastructure that is still being built. Of the more than $3 trillion in expected data center and related infrastructure CapEx from 2025 through 2028, only about a quarter of that has been deployed so far.  The future remains opaque. No two ways about it. The biggest productivity gains from my perspective are likely still ahead of us, and some job losses are likely unavoidable. Earlier, innovation waves unfolded over decades, and AI is moving much faster, compressing the adjustment period. And that does create the central risk to the labor market; that job destruction happens faster than new job creation happens.  And so, what our research has been doing is to try to look beyond the immediate effects. Yes, some jobs and tasks will likely be disrupted. But higher productivity can also mean higher incomes. Higher wealth. With higher income and higher wealth can also mean higher spending, which, in turn, drives the economy faster.  Inside corporations, new tasks and new roles will likely emerge giving some of the displaced workers somewhere else to go. And even if employment does slow down for a while – and that could put downward pressure on inflation and maybe upward pressure on the unemployment rate – I don't really think policy makers are simply going to sit back on the sidelines. Central banks can respond by trying to stimulate the economy and bring it back towards full employment.  This is something that economists call General Equilibrium. We can't look simply at one side of the equation. We have to think about the system as a whole. And I have to say, if monetary policy runs out of room, fiscal policy makers can get into the game as well. Between automatic stabilizers like unemployment benefits and directed targeted government action, there's another way in which the economy could be pushed back to full employment.  So, the bigger point is this, AI clearly has a chance to create some labor market disruption, but the economy has all sorts of other systems and levers in place that can pull us back to full employment.  And with those buffers in place, any rise in the unemployment rate from AI is probably going to end up being smaller, shorter, and easier to manage – at least for the next couple of years than maybe some of the first pass analysis that I've seen suggests.  AI's labor market impact is not predetermined. The debate will almost certainly come down to speed. How fast is AI adoption relative to the economy's ability to adapt? History suggests that productivity ultimately wins. The economy gets bigger and people stay employed. History also tells us that not everyone benefits equally. And more importantly, not every transition is smooth.  So, what does that mean? Should we be just blithely optimistic? Absolutely not. For now, the early evidence is reassuring, but the story is still being written.  Thanks for listening, and if you enjoy this show, please leave us a review wherever you listen. And share Thoughts on the Market with a friend or a colleague today.

    5 min

  8. APR 30

    The Metric Taking Over Earning Season

    Capital spending usually signals how a company is positioning itself for the future. Our Global Head of Fixed Income Research Andrew Sheets explains why this metric is getting more attention from investors. Read more insights from Morgan Stanley. ----- Transcript ----- Andrew Sheets: Welcome to Thoughts on the Market. I'm Andrew Sheets, Global Head of Fixed Income Research at Morgan Stanley.  Today: Why capital expenditure is rapidly becoming one of the most important numbers in earning season across asset classes. It's Thursday, April 30th at 2pm in London.  This is a high-risk episode in the sense that it may already be obsolete by the time that you hear it. But then again, maybe that's fitting for a discussion of record capital spending on cutting edge technology. We are in the middle of the busiest part of earning season, and yesterday four of the largest companies in the world reported numbers. These companies – Alphabet, Amazon, Microsoft, and Meta – have a combined market cap of nearly $12 trillion.  Yet, while the focus of earning season is traditionally about earnings, another line item is rapidly rising in importance. Capital spending on AI infrastructure – the chips, power cooling, and connections that are required to build and run AI models is soaring. And the companies that reported yesterday are at the leading edge of this trend.  The first thing about all this spending is simply the scale. For this year alone, Morgan Stanley estimates that it will amount to over $600 billion across the largest U.S. hyperscalers. To put that in perspective, that means just a handful of U.S. tech companies are now set to spend almost as much on capital and equipment this year as every non-technology company in the S&P 500 did in 2025. And as big as that spending is, it's been accelerating.  That over 600 billion spending number that we forecast for 2026? Well, a year ago we thought it would be roughly half that, and that estimate was well above consensus at the time. U.S. companies have repeatedly guided their spending higher as they seek to capture the AI opportunity. And we think that continues.  By 2028, my Morgan Stanley colleagues estimate that this U.S. hyperscaler capital spending could hit an annual rate of $1 trillion. In other words, as big as these numbers may seem, much of the spending story still lies ahead.  All of that investment, both recently and in the future, has big implications. First, one company's spending is another company's revenue, and many of the stock markets recent winners have been directly tied to this historic buildout.  As of this recording, U.S. semiconductor stocks have risen over 30 percent this month alone.  Second, while these large U.S. tech companies have enormous financial resources, this spending is at a scale that still requires significant borrowing. Our credit strategy teams expect record bond issuance this year, with U.S. tech borrowing a big part of that.  And so far, it's playing out. The first quarter was the busiest quarter for U.S. investment grade bond issuance on record. Which brings us back to these recent earnings – and a dilemma that seems negatively skewed for credit relative to equities.  If these companies continue to sound confident about their capital spending plans or even raise expectations further, that could support AI suppliers and the broader equity market. But it would mean even more borrowing needs to be absorbed by the corporate bond market, a credit negative. The results we got yesterday certainly hint at a continuation of this trend.  On the other hand, if capital spending is guided down, that could undermine a key pillar of recent market strength and broader risk appetite, which could drag credit wider by association. In the near term, the risk reward seems better in other parts of fixed income, such as mortgage-backed securities.  The implications of yesterday's results may also extend to the Federal Reserve. As we discussed last week, Kevin Warsh, nominee to be the next Fed Chair, believes that large levels of investment can boost productivity, lowering inflation, and thus justifying lower interest rates.  And so, what these large spenders do, how confident they feel about the future, and what all of this spending can ultimately deliver – well, the implications of that may extend even into the monetary policy story.  Thank you as always, for your time. If you find Thoughts of the Market useful, let us know by leaving a review wherever you listen. And also tell a friend or colleague about us today.

    5 min
See All (1.6K)

Trailer

Hosts & Guests

4.9
out of 5
66 Ratings

About

Short, thoughtful and regular takes on recent events in the markets from a variety of perspectives and voices within Morgan Stanley.

Information

More From Morgan Stanley Podcasts

You Might Also Like