Big Debates: The AI Evolution

Big Debates: The AI Evolution

In the first of a special series, Morgan Stanley’s U.S. Thematic and Equity Strategist Michelle Weaver discusses new frontiers in artificial intelligence with Keith Weiss, Head of U.S. Software Research.


----- Transcript -----


Michelle: Welcome to Thoughts on the Market I'm Michelle Weaver, Morgan Stanley's U.S. Thematic and Equity Strategist.

Keith: And I'm Keith Weiss, Head of U.S. Software Research.

Michelle: This episode is the first episode of a special series we’re calling “Big Debates” – where we dig deeper into some of the many hot topics of conversation going on right now. Ideas that will shape global markets in 2025. First up in the series: Artificial Intelligence.

It's Friday, January 10th at 10am in New York.

When we look back at 2024, there were three major themes that Morgan Stanley Research followed. And AI and tech diffusion were among them. Throughout last year the market was largely focused on AI enablers – we’re talking semiconductors, data centers, and power companies. The companies that are really building out the infrastructure of AI.

Now though, as we’re looking ahead, that story is starting to change.

Keith, you cover enterprise software. Within your space, how will the AI story morph in 2025?

Keith: I do think 2025 is going to be an exciting year for software [be]cause a lot of these fundamental capabilities that have come out from the training of these models, of putting a lot of compute into the Large Language Models, those capabilities are now being built into software functionality. And that software functionality has been in the market long enough that investors can expect to see more of it come into results. That the product is there for people to actually buy on a go forward basis.

One of the avenues of that product that we're most excited about heading into 2025 is what we're calling agentic computing, where we're moving beyond chatbots to a more automated proactive type of interface into that software functionality that can handle more complex problems, handle it more accurately and really make use of that generative AI capability in a corporate or in an enterprise software setting as we head into 2025.

Michelle: Could you give us an example of what agentic AI is and how might an end user interact with it?

Keith: Sure. So, you and I have been interacting with chatbots a lot to gain access to this generative AI functionality. And if you think about the way you interact with that chatbot, right, you have a prompt, you have a question. You have to come up with the question. going to take that question and it's going to, try to contextually understand the nature of that question, and to the best of its ability it's going to give you back an answer.

In agentic computing, what you're looking for is to add more agency into that chatbot; meaning that it can reason more over the overall question. It's not just one model that it's going to be using to compose the answer. And it's not just the composition of an answer where the functionality of that chatbot is going to end. There's actually an ability to execute what that answer is. So, it can handle more complex problems.

And it could actually automate the execution of the answer to those problems.

Michelle: It sounds like this tech is going to have a massive impact on the workplace. Have you estimated what this could do to productivity?

Keith: Yeah, this is -- really aligns to the work that we did actually back in 2023, where we did our AI index, right. We came up with the conclusion that given the current capabilities of Large Language Models, 25 per cent of U.S. occupations are going to be impacted by these technologies. As the capabilities evolve, we think that could go as high as 45 per cent of U.S. labor touched by these productivity enhancing. Or, sort of, being replaced by these technologies. That equates to, at the high end, $4 trillion of labor that's being augmented or replaced on a go forward basis. The productivity gains still yet to be seen; how much of a productivity gain you could see on average. But the numbers are massive, right, in terms of the potential because it touches so much labor.

Michelle: And finally on agentic, is the market missing anything and how does your view differ from the consensus?

Keith: I think part of what the market is missing is that these agentic computing frameworks is not just one model, right? There's typically a reasoning engine of some sort that's organizing multiple models, multiple components of the system that enable you to -- one, handle more complex queries, more complex problems to be solved, lets you actually execute to the answer. So, there's execution capabilities that come along with that. And equally as important, put more error correction into the system as well. So, you could have agents that are actually ensuring you have a higher accuracy of the answer.

It's the sugar that's going to make the medicine go down, if you will. It's going to make a lot easier to adopt in enterprise environments. I think that's why we're a little bit more optimistic about the pace of adoption and the adoption curves we could see with agentic computing despite the fact it's a relatively early-stage technology.

Michelle: You just mentioned Large Language Models, or LLMs; and one barrier there has been training these models. It requires a ton of computing power, among other constraints. How are companies addressing this, and what's in the cards for next year?

Keith: So, if you think about the demand for that compute in our mind comes from two fundamental sources. And as a software analyst, I break this down into research versus development, right? Research is investment that you make to find core fundamental capabilities.

Development is when you take those capabilities and make the investment to create product out of it. Thus far, again, the primary focus has been on the training side of the equation.

I think that part of the equation looks to be asymptotic to a certain extent. The – what people call the scaling laws, the amount of incremental capability that you're getting from putting more compute at the equation is starting to come down.

What people are overlooking is the amount of improvement that you could see from the development side of the equation. So, whereas the demand for GPUs, the demand for data center for that pure training side of the equation might start to slow down a little bit, I think what we're going to see expand greatly is the demand for inference, the demand to utilize these models more fully to solve real business problems.

In terms of where we're going to source this; there are constraints in terms of data center capacity. The companies that we cover, they've been thinking about these problems for the past decade, right? And they have these decade long planning cycles. They have good visibility in terms of being able to meet that demand in the immediate future. But these questions on how we are going to power these data centers is definitely top of mind for our companies, and they're looking for new sources of power and trying to get more creative there.

The pace with which data centers can be built out is a fundamental constraint in terms of how quickly this demand can be realized. So those supply constraints I don't think are going to be a immediate limiter for any of our names when we're thinking about calendar [20]25. But definitely, part of the planning process and part of the longer-term forecasting for all of these companies in terms of where are they going to find all this fundamental resource – because whether it's training or inference, still a lot of GPUs are going to be needed. A lot of compute is going to be needed.

Michelle: Recently we've been hearing about so called artificial general intelligence or AGI. What is it? And do you think we're going to see it in 2025?

Keith: Yeah, so, AGI is the – it's basically the holy grail of all of these development efforts. Can we come up with models that can reason in the human world as well as we can, right? That can understand the inputs that we give it, understand the domains that we're trying to operate in as well or better than we can, so it can solve problems as effectively and as efficiently as we can.

The easiest way to solve that systems integration problem of like, how can we get the software, how could we get the computers to interact with the world in the way that we do? Or get all the impact that we do is for it to replicate all those functionalities. For it to be able to reason over unstructured text the same way we do. To take visual stimuli the same way that we do. And then we don't have to take data and put into a format that's readable by the system anymore.

2025 is probably too early to be thinking about AGI, to be honest. Most technologists think that there's more breakthroughs needed before the algorithms are going to be that good; before the models are going to be that good.

There's very few people who think Large Language Models and the scaling of Large Language Models in themselves are going to get us to that AGI. You're probably talking 10 to 20 years before we truly see AGI emerge. So, 2025 is probably a little bit too early.

Michelle: Well, great, Keith. Thank you for taking the time to talk and helping us kick off big debates. It looks like 2025 we'll see some major developments in AI.

And to our listeners, thanks for listening. If you enjoy Thoughts on the Market, please leave us a review wherever you listen to the show and share the podcast with a friend or colleague today.

Jaksot(1538)

Why Shutdown Standoff Raises Stakes for Healthcare

Why Shutdown Standoff Raises Stakes for Healthcare

Our analysts Ariana Salvatore and Erin Wright explain the pivotal role of healthcare in negotiations to end the government shutdown.Read more insights from Morgan Stanley.----- Transcript -----Ariana Salvatore: Welcome to Thoughts on the Market. I'm Ariana Salvatore, Morgan Stanley's U.S. Public Policy Strategist. Erin Wright: And I'm Erin Wright, U.S. Healthcare Services Analyst. Ariana Salvatore: Today we'll talk about what the U.S. government shutdown means for healthcare. It's Thursday, October 30th at 12pm in New York. Thus far, it seems like markets haven't really been paying too much attention to the government shutdown. Obviously, we're aware of the cumulative economic impact that builds every week that it lasts. But we haven't seen any movement from the political front either this week or last, which signals that it could be going on for a while longer. That being said, the end of this month is an important catalyst for a few reasons. First of all, you have the potential rollover of SNAP benefits. You have another potential missed military paycheck. And most importantly, the open enrollment period for healthcare plans. Polling is still showing neither side coming out on top with a clear advantage. Absent that changing, you probably need to see one of two things happen to have any movement forward on this front. Either more direct involvement from President Trump as he wraps up the APEC meeting or some sort of exogenous economic event, like a strike from air traffic controllers. Those types of events obviously are difficult to predict this far in advance. But up until now we know that President Trump has not really been involved in the debate. And the FAA seems to be operating a little bit with delays, but as usual. So, Erin, let's pivot to what's topical in here from a healthcare policy perspective. What are investors that you speak with paying the most attention to? Erin Wright: You bring up some important points Ariana. But from a policy perspective, it's very much an always top of mind for healthcare investors here. Right now, it is a key negotiating factor when it comes to the government shutdown. So, the shutdown debate is predominantly centered around the Affordable Care Act or the healthcare exchanges. This was a part of Obamacare. It was a program where individuals can purchase standalone health insurance through an exchange marketplace.The program has been wildly popular. It's been wildly popular in recent years with 24 million members. Growing 30 per cent last year, particularly with enhanced subsidies that are being offered today. So those subsidies are expected to expire at the end of this year, and those exchange members could be left with some real sticker shock – especially when we're going to see premium increases that could, on average, increase about 25 to 30 percent, in some states even more. So, folks are really starting to see that now. November 1st will be a key date here as open enrollment period begins. Ariana Salvatore: Right. So, as you mentioned, this is pretty key to the entire shutdown debate. Republicans are in favor of letting the expanded subsidies roll off. Democrats want to restore them to that COVID level enhancement. Of course, there's probably some middle path here, and we have seen some background reporting indicating that lawmakers are talking about a potential middle path or concession. So, talk me through what's on the table in terms of negotiating a potential compromise or extension of these subsidies. Erin Wright: So, we could see a permutation of outcomes here. Maybe we don't get a full extension, but we could see something partial come through. We could see something in terms of income caps, which restrict, kind of, the level of participants in the AC exchanges. You could see out-of-pocket minimums, which would eliminate some of those shadow members that we've been seeing and have been problematic across the space. And then you could also grandfather in some existing members that get subsidies today. So, all of those could offer some degrees of positive. And some degrees of relief when it comes to broader healthcare services, when it comes to insurance companies, when it comes to others that are participating in this program, as well as the individuals themselves. So, it's really a patient dynamic that's getting real here. A lot is on the table, but a lot is at stake with the potential for the sunsetting of these subsidies to drive 4 million in uninsured lives. So, it is meaningful, and I think that that's something we have to kind of put into perspective here.So, would love to know Ariana though, beyond healthcare, what are some of those key debates in terms of the negotiations around the shutdown? Ariana Salvatore: Healthcare really is central to this debate. So aside from just the ACA subsidies that we talked about, some Democrats have also been pushing for a repeal or rollback of some of the pieces of the One Big Beautiful Bill Act that passed earlier this year. That was the fiscal bill of Republicans passed through the reconciliation process – that included some cuts to Medicaid down the line. So, there's been talk around that front. I think more of a clear path on the subsidies front, because that seems to be something that Republicans are treating as an absolute no-go. Some of the other really key debates are around just kind of how to keep the ball rolling while we're still in the shutdown. So, I mentioned SNAP at first, the potential release of some contingency funds there. Again, the military paychecks are really critical. And, of course, what this all means for incoming data, which is really important – not just for investors but also for the Fed, as it kind of calibrate[s] their next move. In particular, as we head into the December meeting. I think we got a little bit of a hawkish surprise in yesterday's meeting, and that's something that investors were not expecting. So, obviously the longer that this goes on, the more those risks just continue to grow, and this deadline that we're talking about is a really critical one. It's coming up soon. So we should have a sense of how our prognosis pans out in the coming days. Thanks for the conversation, Erin. Erin Wright: Great talking to you, Ariana. Ariana Salvatore: And to our audience, thanks for listening. Let us know what you think by leaving us a review wherever you listen. And if you like Thoughts on the Market, tell a friend or colleague about the podcast today.

30 Loka 20255min

M&A Poised to Gain Momentum

M&A Poised to Gain Momentum

Our Head of Corporate Credit Research Andrew Sheets explains why the recent revival of M&A activity has room to accelerate.Read more insights from Morgan Stanley.----- Transcript -----Andrew Sheets: Welcome to Thoughts on the Market. I'm Andrew Sheets, Head of Corporate Credit Research at Morgan Stanley. Today – a discussion of merger and acquisition activity or M&A. Last year, we had a view that this activity would pick up significantly. We think we're seeing that increase now. It has further to go. It's Wednesday, October 29th at 2pm in London. We have been firm believers at Morgan Stanley in a significant multi-year uplift in global merger and acquisition activity or M&A. That conviction remains. The incentives for this type of action are strong in our view; activity still lags what fundamentals would suggest, and supportive regulatory shifts are real. M&A has now returned, and importantly, we think there's much further to go. Indeed, M&A is very closely linked to corporate confidence, and we think investors need to consider the possibility that we'll see an even bigger surge in this confidence – or a boom. First, policy uncertainty is declining as U.S. tax legislation has now passed, and tariff rates get finalized. It's the relative direction of this uncertainty that we think matters most for corporate confidence. Second, interest rates are declining with the Fed, European Central Bank, and Bank of England all set to cut rates further over the next 12 months. Third, bank capital requirements may decline in the view of Morgan Stanley analysts, which would unlock more lending for these types of transactions. Fourth, and very importantly, the regulatory backdrop is becoming more accommodative in both the U.S. and in Europe. Indeed, we think that companies may think that this is going to be the most permissive regulatory window for transactions that they might get for some time. Fifth, private equity, which is a big driver of M&A activity, is sitting on over $4 trillion of dry powder in our view – at a time when credit markets look very wide open for financing their transactions. And finally, we're seeing a surge in capital expenditure on Morgan Stanley estimates, which we see as a sign of rising corporate confidence, and importantly an urgency to act – with corporates far less content to simply sit back and repurchase their stock. All of these favorable conditions together argue for activity to push even higher. We forecast global M&A volumes to increase by 32 percent this year, an additional 20 percent next year, and reach $7.8 trillion in volume in 2027. This is a global story with M&A rising across regions, especially in Japan. It has cross-asset implications with M&A already being one of the biggest drivers of bond outperformance within the U.S. high-yield market. And this is also a story where we see a lot of value in bringing together macro and micro perspectives. While we think the top-down conditions look favorable for all the reasons I just mentioned, we also see a very encouraging picture bottom up. We polled a large number of Morgan Stanley sector analyst teams and asked them about M&A conditions in their sector. A large majority of them see more activity. So, where could these more specific implications lie? Well, as you heard on yesterday's episode, Healthcare and Biotech may see an uptick in activity. In the U.S., we also think that Banking and Media stand out. In Europe, Business Services, Metals and Mining, and Telecom seem most ripe for more M&A. Aerospace and Defense is an interesting sector that may see more M&A within multiple regions, including the U.S. and Europe, as companies look for scale. And with smaller companies trading at a valuation discount to their larger peers across the world, Morgan Stanley analysts generally see the strongest case for activity in larger companies acquiring these smaller ones. 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.

29 Loka 20254min

A Turnaround in Sight for Healthcare?

A Turnaround in Sight for Healthcare?

Our U.S. Biotech and Biopharma analysts Sean Laaman and Terence Flynn discuss the latest developments that could be positioning the healthcare sector for strong outperformance.Read more insights from Morgan Stanley.----- Transcript -----Sean Laaman: Welcome to Thoughts on the Market. I'm Sean Laaman, Morgan Stanley's U.S. Small and Mid-Cap Biotech Analyst. Terence Flynn: And I'm Terence Flynn, Morgan Stanley's U.S. Biopharma Analyst. Sean Laaman: Today, we'll discuss how a rally in the healthcare sector is being driven by more favorable macro conditions. It's Tuesday, October 28th at 10am in New York. So, Terence, healthcare has lagged the broader market year-to-date, and valuations have been near historical lows. But recent weeks show strengthening performance. Policy headwinds have been front and center.What's changed in the regulatory environment and how is the biopharma sector adapting to these pricing and tariff dynamics? Terence Flynn: Sean, as you know, with many other sectors, tariffs were initially a focus earlier this year. But a number of companies in our space have subsequently announced significant U.S. manufacturing investments to reshore supply chains. And hence, the market's less focused on tariffs in our space right now. But the other policy dynamic and focus is what's called Most Favored Nation or MFN drug pricing. Now, this is where the President's been focused on aligning U.S. drug prices with those in other developed countries. And recently we've seen several companies announce agreements with the administration along these lines, which importantly has provided investors with more visibility here. And we're watching to see if additional agreements get announced. Sean Laaman: Got it. Another hurdle for Large-cap biopharma is a looming expiration of patents with [$]177 billion exposed by 2030. How is this shaping M&A trends and strategic priorities? Terence Flynn: For sure. I mean, as you know, Sean, patent expiry is our normal part of the life cycle of drug development. Every company goes through this at some point, but this does put the focus on company's internal pipelines to continue to progress while also being able to access external innovation via M&A. Recently we have started to see a pickup in deal activity, which could bode well for performance in SMID-cap biotech. Sean Laaman: At the same time, you believe relative valuations look compelling for Large-cap biopharma. Where are valuations versus where they've been historically? What's driving this and how should investors think about positioning? Terence Flynn: Absolutely. Look, on a price to earnings multiple, the sector's trading at about a 30 percent discount to the S&P 500 right now. Now that's in line with prior periods of policy uncertainty. But as policy visibility improves, we expect the focus will shift back to fundamentals. Now, positioning to me still feels light here, given some of the patent cliff dynamics we just discussed. Now, Sean, with the Fed moving toward rate cuts, how do you see this impacting your sector on the biotech side? Sean Laaman: Well, Terence, particularly in my space, which is Small- and Mid-cap biotech companies, they're typically capital consumers are not capital producers. They're particularly sensitive to the current rate environment.Therefore, they're sensitive to spending on pipeline. They're sensitive to M&A. So, as rates come down, we expect more spending on pipeline and more M&A activity, which is generally positive for the sector. Looking forward, biotech sector is generally the best performing sector on a six-to-12-month timeframe post the first rate cut. Terence Flynn: Great. You've also talked about this SMID to Big thesis on the biotech side. Can you explain what's driving that? Sean Laaman: Sure Terence. There’s three pieces to the SMID to Big thematic. So, we in SMID-cap biotech, we cover 80 to 90 companies. About a third of those are newly, kind of profitable companies. Those companies are turning from being capital consumers to capital producers. We see about $15 billion of cash on balance sheets for 2025, going to north of 130 billion by 2030. That's the first piece. The second piece is due to regulatory uncertainty at the USFDA. We're seeing more attractive valuations amongst clinical stage names. That's the second piece. And third piece relates to your coverage, Terence. I refer back to that [$]177 billion of LOE. So, we expect generally that M&A activity will be quite high amongst our sector. Terence Flynn: And let's not forget about AI, which has implications across the healthcare space. How much is this changing the dynamic in biotech, Sean? Sean Laaman: It is changing, but we're really at the beginning. I think there's three things to think about. The first one is faster trial recruitment. The second one is faster regulatory submissions. And the third one, which is the most interesting, but we're really at the beginning of, is faster time to appropriately targeted molecules. Terence Flynn: Great. And maybe lastly, what are the key risks and catalysts for SMID-cap biotech in the current environment? Sean Laaman: As always, we're focused on pipeline failures in terms of risk. Secondly, in terms of risk, we're looking at regulatory risk at the FDA. And thirdly, we're looking at the rise in China biotech and the competitive dynamic there.Whether you're watching large cap biopharma, M&A moves, or the rise of cash-rich, SMID-cap biotechs, the healthcare sector setup is unlike anything we've seen in years.Terence, thanks for speaking with me. Terence Flynn: Always a pleasure to be on the show. Thanks for having me, Sean. Sean Laaman: 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.

28 Loka 20255min

Will the Stock Market Rally Continue?

Will the Stock Market Rally Continue?

Our CIO and Chief U.S. Equity Strategist Mike Wilson discusses the outlook for stocks after the preliminary U.S.-China trade agreement and ahead of the Fed meeting and big tech earnings.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 the remaining hurdles for equities after what appears to be a preliminary trade deal with China.It's Monday, October 27th at 11:30am in New York. So, let’s get after it.Over the past few weeks, trade tensions between the U.S. and China escalated once again focused on rare earths and technology transfers with each country playing its strongest card. Over the weekend, it appears that we have at least a preliminary agreement to de-escalate these tensions which means avoiding prohibitively high tariffs that were scheduled to go on at the end of this month. While we don’t have many details on what has been agreed to, it appears that critical rare earths will continue to ship to the U.S. while technology transfer restrictions by the U.S. to China will ease. Presumably, Fentanyl tariffs of 20 percent on China are likely to be part of any broader agreement between Presidents Trump and Xi, if they end up meeting at the upcoming Asia Pacific Economic Cooperation forum.Given the sharp sell-off in stocks a few weeks ago on the news of trade tensions re-escalating, it’s not surprising that stocks are rallying sharply this morning on news of a possible deal from last week’s talks. Our attention now turns to the other big events this week. First, the Federal Reserve is meeting tomorrow and Wednesday to decide its next move on monetary policy. There is a broad consensus view that the Fed will cut another 25 basis points but there are very different views about how they will address its balance sheet run-off known as quantitative tightening, or QT. Based on my conversations, there is a growing consensus view for the Fed to announce the end of QT but uncertainty around the timing. Our house view is for the Fed to wait until the January meeting to make this official with an end of the program in February. Others believe the Fed could announce something as early as this week. That dispersion in expectations does create some room for disappointment from markets, especially given the recent increase in funding market spreads. More specifically, the widening in spreads suggests banking reserves may already be too low and restrictive for the pick-up in economic activity and capital spending that requires more liquidity. Second, earnings revision breadth has rolled over sharply the past few weeks. Most of this decline is due to normal seasonality and the fact that revisions breadth had reached unsustainably high levels since bottoming out in April. Therefore, a reset should be expected as we previewed over a month ago. Nevertheless, it needs to stabilize and push higher again for stocks to continue their advance in my view. Perhaps most importantly for the S&P 500 is the fact that all of the hyperscalers are reporting this week and will likely determine if revision breadth rebounds. It will also be important to see how those stocks react to what is likely to be continued aggressive guidance on AI capex plans. Since April, the hyperscaler stocks have rewarded higher guidance on spending. Should that change, we may see a different tone to how these companies discuss their spending plans. Bottom line, I remain bullish on my 12 month view for U.S. stocks based on what I believe will be better and broader growth in earnings next year. Nevertheless, the near term window remains a bit cloudy on trade, Fed policy shifts and earnings revisions breadth. Stay patient with new capital deployment and look to take advantage of downdrafts when they arise like a few weeks ago. 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!

27 Loka 20253min

What Happens to Software Developers as AI Can Code?

What Happens to Software Developers as AI Can Code?

Our U.S. Software Analyst Sanjit Singh explains how AI is reshaping software development and why the future for the sector may be brighter – and busier – than ever.Read more insights from Morgan Stanley.----- Transcript -----Welcome to Thoughts on the Market. I’m Sanjit Singh, the U.S. Software Analyst at Morgan Stanley.Today: how AI is transforming software and what that means for developers.It’s Friday, October 24th, at 10am in New York.There's been a lot of news stories and anecdotal accounts about AI taking over jobs, especially in the software industry. You may have heard of vibe coding, where people can use natural language prompts, guiding AI to build software applications. So yes, AI is creating a world where software writes itself. But at the same time, the demand for human creativity only grows.The introduction of AI coding assistants has dramatically expanded what software can do, fueling a surge in both the volume of code and the complexity of projects. But instead of shrinking the developer workforce, AI is actually supporting continued growth in developer headcount, even as productivity soars.We’re estimating the software development market will grow at a 20 percent compound annual growth rate, reaching $61 billion by 2029. And that’s up from $24 billion in 2024. And in terms of the developer population, [research] firms like IDC expect it to jump from 30 million paid developers in 2024 to 50 million by 2029 – that’s a 10 percent annual growth rate. Even the most conservative estimates, like those from the U.S. Bureau of Labor Statistics, see developer jobs growing roughly 2 percent per year through 2033, outpacing overall employment growth.So, what does this mean for people behind the code? AI isn’t replacing developers. It’s redefining them. Routine tasks are increasingly handled by AI agents, and this frees up developers to become curators, reviewers, architects, and most important problem-solvers.The upshot? Companies may need fewer developers for repetitive work, but the overall demand for skilled engineers remains robust. As AI lowers the barrier to entry, the pool of people who can build software applications expands dramatically. But at the same time, the complexity and ambitions of projects rise, keeping experienced developers in high demand.No doubt, AI coding tools are delivering real productivity gains. Some teams are reporting nearly doubling their code capacity and cutting pull request times in half after adopting AI assistants. Test coverage has increased sharply, resulting in 20 percent fewer production incidents for some organizations. But there is a catch with all this AI-generated code. It’s creating significant new bottlenecks downstream.An example of this is code review, which is becoming a major pain point. Many organizations are experiencing pull request fatigue, with developers rubber-stamping changes just to keep up. Some teams now require three reviewers for AI-generated change, compared to just one before. And in terms of automated testing, systems are getting overwhelmed because every change made with AI sets off a complete round of test.Now we estimate productivity gains from AI in software engineering at about 15–20 percent. But in complex projects, the gains are much lower, as the volume of new code often means more bugs and more rework – and hence more human developers.So where do we go from here? In our view, the future isn’t about fully autonomous software development. Instead, large enterprises are likely to favor an integrated approach, where AI agents and human developers work side by side. AI will automate more of the software development lifecycle. And that not only includes coding – which, coding typically accounts for 10-20 percent of the software development effort – but other areas like testing, security, and deployment. But humans will remain in the loop for oversight, design, and decision-making. And as software gets cheaper and faster to build, organizations won’t just do the same work with fewer people – they likely will do more.In short, the need for skilled developers isn’t going away. But it’s definitely evolving. And in the age of AI, it’s not about man versus machine. It’s about man with machine. And so with more software, we see more developers.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.

24 Loka 20254min

Should AI Spending Worry Investors?

Should AI Spending Worry Investors?

Our Head of Corporate Credit Research Andrew Sheets wades into the debate around whether the boom in artificial intelligence investment is a warning sign for credit markets. Read more insights from Morgan Stanley.----- Transcript ----- Andrew Sheets: Welcome to Thoughts on the Market. I'm Andrew Sheets, Head of Corporate Credit Research at Morgan Stanley.Today – the debate about whether elevated capital expenditure and AI technology is showing classic warning signs of overbuilding and worries for credit.It's Thursday, October 23rd at 2pm in London.Two things are true. AI related investment will be one of the largest investment cycles of this generation. And there is a long history of major investment cycles causing major headaches to the credit market. From the railroads to electrification, to the internet to shale oil, there are a number of instances where heavy investment created credit weakness, even when the underlying technology was highly successful.So, let's dig into this and why we think this AI CapEx cycle actually has much further to run.First, Morgan Stanley has done a lot of good collaborative in-depth work on where the AI related spend is coming from and what's still in the pipeline. And importantly, most of the spending that we expect is still well ahead of us. It's only really ramping up starting now.Next, we think that AI is seen as the most important technology of the next decade by some of the biggest, most profitable companies on the planet. We think this increases their willingness to invest and stick with those investments, even if there's a lot of uncertainty around what the return on all of this expenditure will ultimately be.Third, unlike some other major recent capital expenditure cycles – be they the internet of the late 1990s or shale oil of the mid 2010s, both of which were challenging for credit – much of the spending that we're seeing today on AI is backed by companies with extremely strong balance sheets and significant additional debt capacity. That just wasn't the case with some of those other prior investment cycles and should help this one run for longer.And finally, if we think about really what went wrong with some of these prior capital expenditure cycles, it's often really about overcapacity. A new technology – be it the railroads or electricity or the internet – comes along and it is transformational.And because it's transformational, you build a lot of it. And then sometimes you build too much; you build ahead of the underlying demand. And that can lower returns on that investment and cause losses.We can understand why large levels of AI capital investment and the history of large investment cycles in the past causes understandable concern. But when tying these dynamics together, it's important to remember why large investment cycles have a checkered history. It's usually not about the technology not working per se, but rather a promising technology being built ahead of demand for it and resulting in excess capacity driving down returns in that investment, and the builders lacking the financial resources to bridge that gap.So far, that's not what we see. Data centers are still seeing strong underlying demand and are often backed by companies with exceptionally good resources. We need to watch if either of these change.But for now, we think the AI CapEx cycle has much further to go.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

23 Loka 20253min

The Next Turning Points in Tech

The Next Turning Points in Tech

Our analysts Brian Nowak, Keith Weiss and Matt Bombassei break down the most important tech insights from Morgan Stanley’s Spark Private Company Conference and industry shifts that will likely shape 2026 and beyond. Read more insights from Morgan Stanley.----- Transcript ----- Brian Nowak: Welcome to Thoughts on the Market. I'm Brian Nowak, Morgan Stanley's Head of U.S. Internet Research. I'm joined today by Keith Weiss, Head of U.S. Software Research and Matt Bombassei from my team.Today we're going to talk about private companies and technology – and how they're showing us the direction of travel for disruptive technologies and emerging investment opportunities.It's Wednesday, October 22nd at 10am in New York.Keith and Matt, we just returned from Morgan Stanley's Spark Private Company Conference last week in Los Angeles. It had over 85 private tech companies, 150 plus investor firms. There were a lot of themes that were discussed across the entire tech space impacting a lot of different sectors, including energy, healthcare, financial services, and cybersecurity.Keith, what were some of the biggest takeaways you took away from Spark this year?Keith Weiss: I'd say just to start off with, the Spark Conference is one of my favorite conferences of the year. It's a more intimate conference where you really get to spend time with both the private company executives and founders, as well as investors from the VC community and public company investors. And the conversations are more broad ranging; they're more about the thematics in the industry. They're more long term in nature.So, it's not just a conversation about what's next quarter going to look like, or what data points are you drumming up. You're having these thoughtful conversations about what's going on in the industry and how that's going to impact business models, how it's going to impact innovation cycles, how it's going to impact pricing models, within these companies. So, it tends to be a very interesting conference for me to attend.So, for me, some of the key takeaways. Typically, when we're in these innovation cycles, it feels like everybody's rowing in the same direction. We all understand where the technology's heading, we're all understanding how it's going to be delivered, and it's a race to get there. And you're having a conversation about who's doing best in that race, who's best positioned, who's got a better motor in their race car, if you will.So, to me, one of the big takeaways was we don't have that agreement today, right? There's different players that are looking at this market evolution differently. On one side of the equation, the application vendors – and a lot of this debate is in SaaS based applications. They see SaaS based applications having a very big role in taking these models that are inherently in-determinative and making them to be more determinative and useful within an enterprise context.Bringing them the data that they need to get the job done and the right data; bringing them the context of the business process being solved; bringing the governance that's necessary to use in an enterprise environment. But most importantly, to make it effective and efficient for the large enterprise.On the other side of the equation, you have venture capital investors and more early-stage investors who are looking at this as a huge phase shift, right? This is going to fundamentally change how we build software, how we utilize software, and they worry about a deprecation of that SaaS application layer. They think the model itself is going to start to encompass, it's going to start to subsume a lot more of that application functionality, a lot more of that analytics. And they see a lot more disruption going forward.So that debate within the marketplace, that's something that's interesting to me. It's something that we don't typically see in these innovation cycles. So that's takeaway number one.Takeaway number two, we're still really early days, and that's a little bit implied in in the first statement; I definitely hear a lot of it when I talk to the end customer. When I talk to CIOs. This wasn't necessarily at Spark, but earlier in the week, I was at a CIO conference, there was 150 CIOs in the room. One of the gentlemen on stage asked a question. ‘Who in the room has a good understanding of what we're talking about when we mean Agentic AI, when we mean agentic computing within our enterprise.’ Of the 150 CIOs, four raised their hands. Still very early days in understanding how this is going to evolve, how we're going to actually deliver these capabilities into the enterprise.And the last takeaway I would say is more excitement about the federal government becoming a better customer for software companies overall. People are more interested in new avenues into that federal government. There's been some very successful companies that have opened the door to getting into these federal government contracts without going through the primes, without doing the typical federal government procurement cycles.And that's very interesting to the startup community, which tends to move faster, which tends to drive on innovation versus relationship building; versus being in an existing kind of incumbent prime. So, I thought that opening was – it was pretty interesting as well.Brian Nowak: it sounds like it's still very early, there are a lot of different points of view and no real consensus as to where technologies could go next. However, one theme with an enterprise software – [it] does seem like cybersecurity has a little more of a unified view.So maybe walk us through what you learned from a cybersecurity perspective and what should we be focused on there?Keith Weiss: Yeah, absolutely. If there is a consensus, the consensus is that generative AI and these innovations and the fast pace of innovation is going to be a positive for cybersecurity spending, right? The reason being, there's three main factors that are driving that overall spending.One is expansion of surface area, right? Cybersecurity in one dimension, you can think of how much is there to be protected, right? And if we think about the major themes that we're talking about, we're going to be developing a lot more software, right? The code generation tools are improving software developer productivity. You have an expanding capability of what you can actually automate.We'll be building a lot more software. That software needs to be protected, right? We have new entities that are going to be operating inside of enterprises, and that's the agents. So, CIOs are thinking about this future state where you have tens, thousands, maybe hundreds of thousands of agents operating in the environment, doing work on behalf of end users, but having permissions and having ability to execute business processes. How do we secure that side of the equation? We're talking about outside of just the four walls of the large enterprise, going into more operational technologies, being able to automate more of that work. That needs to be secured as well.So, an expanding surface area is definitely good for the cybersecurity budget. You can almost think of cybersecurity as a tax on that surface area. We generally think about it; somewhere between 4 and 6 percent of IT spend is going to be spent on overall security. So, that's one big driver.The second big driver is the elevated threat environment. So, while we're excited to get our hands on these extended capabilities of generative AI, the bad guys are already there, right? They're taking advantage of this. The sophistication, the volume and the velocity of these attacks is all increasing. That makes a harder job for the existing infrastructure to keep up, and it's going to likely necessitate more spending on cybersecurity to tackle these newer challenges; the newer dynamism within the cybersecurity threat appropriately. So, you're going to have to use generative AI to counter the generative AI.And then the last component of it; the last driver would be the regulatory environment. Regulatory tends to have some cybersecurity angles. If we think about it here, we're seeing it in terms of data governance is probably the big one. Where does this data go when it goes into the model? Are we putting the right controls around it? Do we have the right governance on it? So that's a big area of concern.A lot of complaining going on at the conference about the lack of consistency in that regulatory environment. All these different initiatives coming up from the state – really creates a challenging environment to navigate. But that's all good-ness for cybersecurity vendors that can help you get into compliance with these new regulations that are coming up. So overall, a lot of positivity around cybersecurity spending and startups definitely look to take advantage of that.Brian Nowak: Matt, so Keith says there's lack of consensus and boats being rode in every direction on what should be adopted first. And only 3 percent of CIOs know what agentic AI means. What did you learn about early signal on adoption? And some of the barriers to adoption? And hurdles that companies are talking about that they need to overcome to really adopt some of these new tools?Matt Bombassei: Yeah. Well, to Keith's point, it is really early, right? And that was a consistent theme that we heard from our companies at the conference. They are seeing early signs of cost efficiency, making employees more productive as opposed to maybe broad scale layoffs. But it's the deployment of these model technologies into specific sub-verticals – so accounting, legal engineering – where that adoption is driving greater efficiency within the organization.These companies are also adopting models that are smaller and a bit more fine tuned to their specific work product. And so that comes at a lower cost. We heard companies talking about costs at 1/50 of the cost of the broader foundational models when they're deploying it within the organization. And so, cost efficiency is something that we're seeing.At the same time, to speak to how early it is, one of the biggest hurdles here is change management and actually adoption. Getting people to use these products, getting them to learn the new technologies, that is a big hurdle. You know, you can lead a horse to water, you can't make it drink, right? And so, getting people to actually deploy these technologies is something that organizations are thinking through. How do we approach [it]?Brian Nowak: And you make an autonomous car drive? I know you've been doing a lot of work on autonomous driving more broadly. There were some autonomous driving and autonomous driving technology companies at Spark. What were your takeaways on autonomous driving from last week?Matt Bombassei: Yeah, well, not only can you make an autonomous car drive, you can make a truck drive and a bunch of other physical equipment. I think that was one of the takeaways here was that these neural nets that are powering autonomous vehicles are actually becoming much more generalizable. The integration of the transformer architecture into these neural nets is allowing them to take the context from one sub-vertical and deploy it in another vertical.So, we heard that 80 to 90 percent of the software, the underlying neural net, is applicable across these verticals. So, think applicable from autonomous ride sharing to autonomous trucking, right? What that means from our point of view is that it's important to get the scale of total miles driven – to establish that kind of safety hurdle if you're these companies.But also, don't necessarily think of these companies as defined by the vertical that they're operating in. If these models truly are generalizable, a company that's successful and scaled and autonomous ride hailing can switch or navigate verticals to also become successful potentially in trucking and other industries as well. So, the generalization of these models is particularly interesting for scale, and long-term market position for these companies.Brian Nowak: It's fascinating. Well, from consumer and enterprise adoption, the future of agentic computing and autonomous driving, there will be a lot more themes we all have to stay on top of. Keith, Matt, thanks so much for taking the time today.Keith Weiss: Great speaking with you Brian.Matt Bombassei: Thanks for having us.Brian Nowak: 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.

22 Loka 202511min

How to Navigate U.S.-China Tensions

How to Navigate U.S.-China Tensions

Our Global Head of Fixed Income Research and Public Policy Michael Zezas discuss the latest developments in U.S.-China relations and how they could affect investors.Read more insights from Morgan Stanley.----- Transcript ----- Welcome to Thoughts on the Market. I’m Michael Zezas, Global Head of Fixed Income Research and Public Policy Strategy. Today, we’re talking about the U.S. and China—why the relationship remains complicated, and what it means for markets. It’s Tuesday, Oct 21st, at 12:30pm in New York. If you’ve been following headlines, you know that U.S.-China relations are rarely out of the news. But beneath the surface, the dynamics are more nuanced than the daily soundbytes suggest. Investors often ask: Are we headed for a decoupling of the two economies, or is there room for cooperation? The answer, as always, is—it’s complicated. Let’s start with the basics. The U.S. and China are deeply intertwined economically, but strategic competition has intensified. Recent years have seen tariffs, export controls, and restrictions on technology transfer. Yet, there’s still plenty of trade between the two countries, and both economies are dependent on each other for growth and innovation. So what’s going on now? In recent weeks, China has moved to tighten rare earth export controls and the U.S. has proposed 100 percent tariffs in return. If this came to pass, these events could mark a clear economic split. But given the interdependencies we just cited, neither Washington nor Beijing seems eager for a true split, at least not anytime soon. The economic costs would be staggering, and both sides know it. So, a truce seems more likely, perhaps with somewhat different terms than the narrow semis-for-rare earths agreement they made this spring. And longer term, this episode seems to be a part of a broader dynamic, where rolling negotiations and truces are more likely than either a durable trade peace or a hard economic decoupling. For fixed income investors, this drives some important considerations. First, U.S. industrial policy is ramping up, with clear implications for AI infrastructure. AI is an area where the U.S. views it as essential that they outcompete China. Supported by renewed CapEx incentives from the latest tax bill, it’s clear to us that U.S. companies will be pushing further into AI development, where my colleagues have identified $2.9 trillion of data center financing needs over the next three years, about half of which will come from various credit markets. And for credit investors, this presents an important opportunity. Another consideration is how markets will balance near-term growth risks with an array of medium term growth possibilities. As our U.S. economics team has pointed out, the evidence suggests that corporates haven’t yet been forced to make tough decisions about passing on or absorbing tariff costs, underscoring that trade-related growth pressures aren’t yet in the rearview. The ongoing U.S. government shutdown doesn’t help either. It’s all a good argument for why bond yields could move lower in the near term. But also, we should expect yield curves could steepen more, with higher relative yields in longer maturities. This would reflect greater uncertainties around higher fiscal deficits, inflation, and economic growth. Our economists have been calling out the mixed messages in economic data, as well as a U.S. fiscal sustainability picture that appears reliant on acceleration in corporate CapEx for a manufacturing and AI-driven growth burst. In sum, the U.S.-China relationship is evolving, with global implications that don’t lend themselves to easy narratives or quick fixes. Our challenge will continue to be crafting investment strategies that reflect durable policy undercurrents, the signal amid news headline noise. 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.

21 Loka 20253min

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