In short
An encore of a live “Thoughts on the Market” panel on how AI is disrupting and funding the AI boom, with a focus on U.S. consumer companies and the labor-market outlook.
Guests
Arunima Sinha (Morgan Stanley Global & U.S. Economics Team); Simeon Gutman (Morgan Stanley U.S. Hardlines/Broadlines/Food Retail Analyst); Megan Clapp (Morgan Stanley U.S. Food Producers & Leisure Analyst).
Key claims
2025’s market resilience came from AI-driven capital spending despite weaker labor; 2026 should improve (U.S. leading, inflation easing H2). AI adoption is early (“innings”), with scaling pilots as the main opportunity. Agentic commerce may increase sales but risks cannibalization; retailers can protect share via forward-positioned inventory and infrastructure.
Notable examples
Walmart’s “Sparky” GenAI shopping assistant, OpenAI-powered search/checkout, AR shelf monitoring, LLM inventory replenishment, autonomous lifts; Hershey reallocating ad spend by zip code using real-time sell-through; General Mills “digital twins” improving forecast accuracy and savings (4% to 5%); Shark Ninja optimizing DTC for ChatGPT/Gemini; panel notes OpenAI experimenting with curated product transactions.
Written by AI. May contain mistakes. Listen to the episode to check what was said.
Chapters
Tap a time to open that second in VOAssessing AI Implementation
1:42 to 2:28
Simeon shares insights on assessing AI's implementation across companies.
“You recently put out a piece assessing the AI race.”
Framework for AI Use Cases
2:31 to 4:08
Simeon outlines a framework to categorize AI implementations across various business functions.
“And the different groups, we came up with six groups that we were able to cluster.”
Real-World AI Use Cases in Marketing
4:12 to 4:53
Discussion of real-world examples where companies are utilizing AI for marketing and product cataloging.
“And how about a couple examples of the ways companies are using these?”
Current State of AI in Food and Staples
4:55 to 6:16
Megan discusses the early stages of AI adoption in the food and staples sector and future opportunities.
“It sounds like AI, machine learning, or algorithm-driven suggestions to consumers.”
Successful AI Adoption Examples
6:20 to 8:30
Megan provides examples of successful AI adoption in the food industry, highlighting marketing and cost savings.
“I think we think about the opportunity for food and staples broadly as we put it into kind of two areas.”
Impact of Agentic AI on E-Commerce
8:38 to 11:19
Discussion on the implications of Agentic AI for e-commerce and potential sales cannibalization.
“And what they're doing actively right now is optimizing their DTC website for LLMs like ChatGPT and Gemini.”
AI's Impact on Labor Market and Economic Growth
11:23 to 14:03
Arunima discusses the potential effects of AI on the labor market and its contribution to economic growth.
“There's incentives for the hyperscalers to be part of this.”
Transcript
Automatic transcript. May contain errors.0:002025 started with an expectation of slower economic growth and stubborn inflation. While growth did cool, the real surprise was the disconnect between the economy and financial markets. Unemployment ran higher than projected, yet markets showed resilience, powered largely by an AI-driven capital spending boom. Looking ahead to 2026, the backdrop is brighter. Global growth should accelerate modestly. Inflation should ease in the second half of the year, and real incomes look poised to improve. We expect the U.S. to lead the charge and remain most constructive on the U.S. market. Thank you for listening throughout 2025 as we've navigated these issues and events that shape financial markets and society.
0:44We hope that you'll join us next year as we continue to bring you the most up-to-date information on the financial world. This week, please enjoy some encores of episodes over the last few months, and we'll be back with all new episodes in January. From all of us at Thoughts on the Market, happy holidays and a very happy new year. Welcome to Thoughts on the Market. We're coming to you live from Morgan Stanley's Global Consumer and Retail Conference in New York City, where we have more than 120 leading companies in attendance. Today's episode is the second part of our live discussion of the U.S.
1:19consumer and how AI is changing consumer companies. With me on stage, we have Arunima Sinha from the Global and U.S. Economics Team, Simeon Gutman, our U.S. Hardlines, Broadlines, and Food Retail Analyst, and Megan Clapp, U.S. Food Producers and Leisure Analyst. It's Friday, December 5th at 10 a.m. in New York. So, Simeon, I want to start with you. You recently put out a piece assessing the AI race. Can you take us through how you're assessing current AI implementation? And can you give us some real-world examples of what it looks like when a company significantly integrates AI into their business?
1:57Sure. So the consumer discretionary and staples teams went to each of their covered companies, and we started searching for what those companies have disclosed and communicated regarding their AIs. In some cases, we used AI to do this search. But we created a search and created this universe of factors and different ways AI is being implemented. We didn't have a framework until we had the entire universe of all of these AI use cases. Once we did, then we were able to compartmentalize them. And the different groups, we came up with six groups that we were able to cluster. First, personalization and refined search.
2:38Second, customer acquisition. Third, product innovation. Fourth, labor productivity. Fifth, supply chain and logistics. And lastly, inventory management. And using that framework, we were able to rank companies on a 1 to 10 scale across, that was the implementation part, across three different dimensions. Breath, how widely the AI is deployed across those categories. The depth, the quality, which we did our best to be able to interpret. and then the last one was proprietary initiatives so that's partnerships could be with leading AI firms so that helped us differentiate the leaders with others not necessarily laggards but those who were ahead of in the race in some cases companies that have communicated more would naturally scream more so there is some potential bias in that but otherwise the fact pattern was objective Walmart has full-scale AI deployment.
3:36They are integrated across their business. They've introduced Gen AI tools. That's like their Sparky shopping assistant, as well as integrated to in-store features. It's been driving a 25 % increase in average shopper spend. They've recently partnered with OpenAI to enable chat GBT-powered search and checkout, positioning where the customer is shopping. They're also layering on augmented reality for holiday shopping, computer vision for shelf monitoring, LLMs for inventory replenishment, autonomous lifts, the list goes on and on, but it covers all the functional categories in our framework. And how about a couple examples of the ways companies are using these?
4:16Any interesting real world use cases you've seen so far? So one of them was in marketing personalization, as well as in product cataloging. that was one of the more cited themes at this conference so it was it was good timing so the idea is when product is staged on a company's website i don't think we all appreciate how much time and many hours and people and resources it takes to get the correct information to get the right pictures and to show all the assortment those type of functions ai is helping enable and it sounds like we're on the cusp of a step change in personalization. It sounds like AI, machine learning, or algorithm-driven suggestions to consumers.
5:04We didn't get practical use cases, but a lot of companies talked about the deployment of this into 2026, which sounds like it's something to look forward to. And Megan, how would you describe AI adoption in your space in terms of innings? and what kind of criteria are you using to assess the future for AI opportunity and potential? Yeah, I would say, you know, I'd characterize adoption in the food and broader staples space today is still relatively early innings. I think, you know, most companies are still standing up the data infrastructure, experimenting with various tools. We're seeing companies pilot early use cases and start to talk about them.
5:42And that was evident in the work we did with the note that Simeon just talked about. And so the opportunity, I think, going ahead lies in kind of what we see in terms of scaling those pilots to become more impactful. And for staples broadly, and food ties into this, I think these companies start with an advantage in that they sit on a tremendous amount of high-frequency consumption data. So the data availability is quite large. The question now is, can these large organizations move with speed and translate that data into action. And that's something that we're focused on when we think about feasibility.
6:20I think we think about the opportunity for food and staples broadly as we put it into kind of two areas. One is what can they do on the top line? Marketing, innovation, R &D, kind of the lifeblood of CPG companies. And that's where we're seeing a lot of the early use cases. I think ultimately that will be the most important driver. Driving top line tends to be the most important thing in most consumer companies. But then on the other side, there are a lot of cost efforts, supply chain savings, labor productivity. Those are honestly a bit easier to quantify. And we're seeing real tangible things come out of that.
7:00But overall, I think the way we think about it is the large companies with scale and the ability to go after the opportunity because they have the scale and the balance sheet to do so will be winners here, as well as the smaller, more nimble companies that can move a little bit faster. And so that's how we're thinking about the opportunity. Can you give us also just a couple examples of AI adoption that's been successful that you've seen so far? Yeah, so on the top line side, like I said, kind of marketing, innovation, R &D. One quick example on the food side, Hershey, for example, they're using algorithms to reallocate advertising spend by zip code based on the real-time sell-throughs.
7:41They can just be much more targeted and more efficient, honestly, with that advertising spend. I think from an innovation perspective too, these companies are able to identify on-trend things faster and kind of incorporate that and take the idea to shelf time down significantly. And then on the cost side, General Mills is a company who's actually relatively far ahead, I'd say, in the AI adoption curve in Staples broadly And what they've done is deployed what they call digital twins across their network, and it's improved forecast accuracy. They've taken their historical productivity savings from 4 % annually to 5%.
8:25That's something that's structural, so seeing real tangible benefits that are showing up in the P &L. And so I think broadly the theme is these companies are using AI to make faster, more precise decisions. And then I thought I'd just mention on the leisure side something that I felt was interesting that we learned from Shark Ninja yesterday at the conference is, you know, when asked about the role of agentic AI in future commerce, thinks it'll be huge was how he described, the CEO described it. And what they're doing actively right now is optimizing their DTC website for LLMs like ChatGPT and Gemini.
9:02And his point was that what drives conversion on DTC today may not ultimately be what ranks an AI-driven search. But he said the expectation is that by Christmas of next year, commerce via these AI platforms will be meaningful. mentioned that OpenAI is already experimenting with curated product transactions. So they're really focused on kind of optimizing their portfolio. I think he thinks brands will win, but you've got to get ahead of it as well. Yeah. And that's great that you just brought up Agenda Commerce. We've heard about it quite a bit over the past couple of days. Simeon, I know you recently put out a big piece on this theme.
9:43Agenda Commerce introduces a lot of possibility for incremental sales, but it also introduces the possibility for cannibalization. Where do you see this shaking out in your space? Are you really concerned about that cannibalization possibility? Yeah. So the larger debate is a little bit of sales cannibalization and a potential bit of retail media cannibalization. So your first point is Agentic theoretically opens up a bigger e-commerce penetration and just more commerce. And once you go to more e-commerce, that could be beneficial for some of these companies. We can also put the counter argument of when e-commerce came direct to consumer type of selling could disintermediate the captive retailer sales again.
10:29Maybe, maybe not. Part of this answer is we created a framework to think about what retailers can protect themselves most from this. Two of them, two of the five eyes, our infrastructure and inventory. So the more that your inventory is forward positioned, the more infrastructure you have, the AI and the agent will still prioritize that retailer within that network. That business will likely not go elsewhere. And that's our premise. Now, retail media is a different can of worms. We don't know what models are going to look like, how this interaction will take place. We don't know who controls the data, the transactions.
11:06Part of this conference is we were hearing more the retailers are going to control some of the data and the transaction. Will consumers feel comfortable giving personal information credit card to agents? I'm sure at some point we'll feel comfortable, but there are these inertia points, and these are models that are getting worked out today. There's incentives for the hyperscalers to be part of this. There's incentives for the retailers to be part of it, but we ultimately don't know. What we do know is, though, forward position inventory is still going to win that agent's business, If you need to get merchandise quickly, efficiently, and if it's a lot of merchandise at once, think about the largest platforms that have been investing in long tail of product and speed to getting it to that consumer.
11:53Arunima, I want to bring this back to the macro as well as AI adoption starts to ramp. The labor market then starts to get called into question. And is this going to be automation or is it going to be augmentation as you see a ramp in AI adoption? So how are your expectations for AI being factored into your forecast and what are you expecting there? There are two ways that we think about just sort of AI spending mattering for our growth forecasts. One part is literally the spend, the investment in the data centers and the chips and so on. And then the other is just the rise in productivity. So does the labor or does the human capital become more productive?
12:37And if we sum both of those things together, we think that over 2026-27, they add anywhere between 40-45 basis points to growth. And just to put things in perspective, our GDP growth estimate for the end of this year in 2026 is 1.8%. For 2027, it's 2.0%. So it's an important part of that process. In terms of the labor market itself, the work that you've led, as well as the work that we've been doing, which is this question about adoption at the macro level, that's still fairly low. We look at the census data that tracks larger companies or mid-sized companies on a monthly basis to say, how much did you use AI tools in the last couple of weeks?
13:34And that's been slowly increasing, but it's still sort of in the mid-teens in terms of how many companies have been using as a percentage. And so we think that adoption should continue to increase. And as that does, for now, we think it is going to be a complement to labor, although there are some cohorts within demographic cohorts in terms of ages that are probably going to be disproportionately impacted. But we don't think that that's a near term 2026 story. Well, thank you all for joining us, and please follow Thoughts on the Market wherever you listen to podcasts. Thank you.
14:19Thank you to our panel participants for this engaging discussion. And to our live and podcast audiences, thanks for listening. If you enjoy Thoughts on the Market, please leave us a review wherever you listen and share the podcast with a friend or colleague today. The preceding content is informational only and based on information available when created. It is not an offer or solicitation, nor is it tax or legal advice. It does not consider your financial circumstances and objectives and may not be suitable for you.
From the publisher
Original Release Date: November 13, 2025
Live from Morgan Stanley’s European Tech, Media and Telecom Conference in Barcelona, our roundtable of analysts discusses tech disruptions and datacenter growth, and how Europe factors in.
Read more insights from Morgan Stanley.
----- Transcript -----
Paul Walsh: Welcome to Thoughts on the Market. I'm Paul Walsh, Morgan Stanley's European Head of Research Product.
Today we return to my conversation with Adam Wood. Head of European Technology and Payments, Emmet Kelly, Head of European Telco and Data Centers, and Lee Simpson, Head of European Technology.
We were live on stage at Morgan Stanley's 25th TMT Europe conference. We had so much to discuss around the themes of AI enablers, semiconductors, and telcos. So, we are back with a concluding episode on tech disruption and data center investments.
It's Thursday the 13th of November at 8am in Barcelona.
After speaking with the panel about the U.S. being overweight AI enablers, and the pockets of opportunity in Europe, I wanted to ask them about AI disruption, which has been a key theme here in Europe. I started by asking Adam how he was thinking about this theme.
Adam Wood: It’s fascinating to see this year how we've gone in most of those sectors to how positive can GenAI be for these companies? How well are they going to monetize the opportunities? How much are they going to take advantage internally to take their own margins up? To flipping in the second half of the year, mainly to, how disruptive are they going to be? And how on earth are they going to fend off these challenges?
Paul Walsh: And I think that speaks to the extent to which, as a theme, this has really, you know, built momentum.
Adam Wood: Absolutely. And I mean, look, I think the first point, you know, that you made is absolutely correct – that it's very difficult to disprove this. It's going to take time for that to happen. It's impossible to do in the short term. I think the other issue is that what we've seen is – if we look at the revenues of some of the companies, you know, and huge investments going in there.
And investors can clearly see the benefit of GenAI. And so investors are right to ask the question, well, where's the revenue for these businesses?
You know, where are we seeing it in info services or in IT services, or in enterprise software. And the reality is today, you know, we're not seeing it. And it's hard for analysts to point to evidence that – well, no, here's the revenue base, here's the benefit that's coming through. And so, investors naturally flip to, well, if there's no benefit, then surely, we should focus on the risk.
So, I think we totally understand, you know, why people are focused on the negative side of things today. I think there are differences between the sub-sectors. I mean, I think if we look, you know, at IT services, first of all, from an investor point of view, I think that's been pretty well placed in the losers’ buckets and people are most concerned about that sub-sector…
Paul Walsh: Something you and the global team have written a lot about.
Adam Wood: Yeah, we've written about, you know, the risk of disruption in that space, the need for those companies to invest, and then the challenges they face. But I mean, if we just keep it very, very simplistic. If Gen AI is a technology that, you know, displaces labor to any extent – companies that have played labor arbitrage and provide labor for the last 20 - 25 years, you know, they're going to have to make changes to their business model.
So, I think that's understandable. And they're going to have to demonstrate how they can change and invest and produce a business model that addresses those concerns. I'd probably put info services in the middle. But the challenge in that space is you have real identifiable companies that have emerged, that have a revenue base and that are challenging a subset of the products of those businesses. So again, it's perfectly understandable that investors would worry. In that context, it's not a potential threat on the horizon. It's a real threat that exists today against certainly their businesses.
I think software is probably the most interesting. I'd put it in the kind of final bucket where I actually believe… Well, I think first of all, we certainly wouldn't take the view that there's no risk of disruption and things aren't going to change. Clearly that is going to be the case.
I think what we'd want to do though is we'd want to continue to use frameworks that we've used historically to think about how software companies differentiate themselves, what the barriers to entry are. We don't think we need to throw all of those things away just because we have GenAI, this new set of capabilities. And I think investors will come back most easily to that space.
Paul Walsh: Emmet, you talked a little bit there before about the fact that you haven't seen a huge amount of progress or additional insight from the telco space around AI; how AI is diffusing across the space. Do you get any discussions around disruption as it relates to telco space?
Emmet Kelly: Very, very little. I think the biggest threat that telcos do see is – it is from the hyperscalers. So, if I look at and separate the B2C market out from the B2B, the telcos are still extremely dominant in the B2C space, clearly. But on the B2B space, the hyperscalers have come in on the cloud side, and if you look at their market share, they're very, very dominant in cloud – certainly from a wholesale perspective.
So, if you look at the cloud market shares of the big three hyperscalers in Europe, this number is courtesy of my colleague George Webb. He said it's roughly 85 percent; that's how much they have of the cloud space today. The telcos, what they're doing is they're actually reselling the hyperscale service under the telco brand name.
But we don't see much really in terms of the pure kind of AI disruption, but there are concerns definitely within the telco space that the hyperscalers might try and move from the B2B space into the B2C space at some stage. And whether it's through virtual networks, cloudified networks, to try and get into the B2C space that way.
Paul Walsh: Understood. And Lee maybe less about disruption, but certainly adoption, some insights from your side around adoption across the tech hardware space?
Lee Simpson: Sure. I think, you know, it's always seen that are enabling the AI move, but, but there is adoption inside semis companies as well, and I think I'd point to design flow. So, if you look at the design guys, they're embracing the agentic system thing really quickly and they're putting forward this capability of an agent engineer, so like a digital engineer. And it – I guess we've got to get this right. It is going to enable a faster time to market for the design flow on a chip.
So, if you have that design flow time, that time to market. So, you're creating double the value there for the client. Do you share that 50-50 with them? So, the challenge is going to be exactly as Adam was saying, how do you monetize this stuff? So, this is kind of the struggle that we're seeing in adoption.
Paul Walsh: And Emmet, let's move to you on data centers. I mean, there are just some incredible numbers that we've seen emerging, as it relates to the hyperscaler investment that we're seeing in building out the infrastructure. I know data centers is something that you have focused tremendously on in your research, bringing our global perspectives together. Obviously, Europe sits within that. And there is a market here in Europe that might be more challenged. But I'm interested to understand how you're thinking about framing the whole data center story? Implications for Europe. Do European companies feed off some of that U.S. hyperscaler CapEx? How should we be thinking about that through the European lens?
Emmet Kelly: Yeah, absolutely. So, big question, Paul. What…
Paul Walsh: We've got a few minutes!
Emmet Kelly: We've got a few minutes. What I would say is there was a great paper that came out from Harvard just two weeks ago, and they were looking at the scale of data center investments in the United States. And clearly the U.S. economy is ticking along very, very nicely at the moment. But this Harvard paper concluded that if you take out data center investments, U.S. economic growth today is actually zero.
Paul Walsh: Wow.
Emmet Kelly: That is how big the data center investments are. And what we've said in our research very clearly is if you want to build a megawatt of data center capacity that's going to cost you roughly $35 million today.
Let's put that number out there. 35 million. Roughly, I'd say 25… Well, 20 to 25 million of that goes into the chips. But what's really interesting is the other remaining $10 million per megawatt, and I like to call that the picks and shovels of data centers; and I'm very convinced there is no bubble in that area whatsoever.
So, what's in that area? Firstly, the first building block of a data center is finding a powered land bank. And this is a big thing that private equity is doing at the moment. So, find some real estate that's close to a mass population that's got a good fiber connection. Probably needs a little bit of water, but most importantly needs some power.
And the demand for that is still infinite at the moment. Then beyond that, you've got the construction angle and there's a very big shortage of labor today to build the shells of these data centers. Then the third layer is the likes of capital goods, and there are serious supply bottlenecks there as well.
And I could go on and on, but roughly that first $10 million, there's no bubble there. I'm very, very sure of that.
Paul Walsh: And we conducted some extensive survey work recently as part of your analysis into the global data center market. You've sort of touched on a few of the gating factors that the industry has to contend with. That survey work was done on the operators and the supply chain, as it relates to data center build out.
What were the key conclusions from that?
Emmet Kelly: Well, the key conclusion was there is a shortage of power for these data centers, and…
Paul Walsh: Which I think… Which is a sort of known-known, to some extent.
Emmet Kelly: it is a known-known, but it's not just about the availability of power, it's the availability of green power. And it's also the price of power is a very big factor as well because energy is roughly 40 to 45 percent of the operating cost of running a data center. So, it's very, very important. And of course, that's another area where Europe doesn't screen very well.
I was looking at statistics just last week on the countries that have got the highest power prices in the world. And unsurprisingly, it came out as UK, Ireland, Germany, and that's three of our big five data center markets. But when I looked at our data center stats at the beginning of the year, to put a bit of context into where we are…
Paul Walsh: In Europe…
Emmet Kelly: In Europe versus the rest. So, at the end of [20]24, the U.S. data center market had 35 gigawatts of data center capacity. But that grew last year at a clip of 30 percent. China had a data center bank of roughly 22 gigawatts, but that had grown at a rate of just 10 percent. And that was because of the chip issue. And then Europe has capacity, or had capacity at the end of last year, roughly 7 to 8 gigawatts, and that had grown at a rate of 10 percent.
Now, the reason for that is because the three big data center markets in Europe are called FLAP-D. So, it's Frankfurt, London, Amsterdam, Paris, and Dublin. We had to put an acronym on it. So, Flap-D. Good news. I'm sitting with the tech guys. They've got even more acronyms than I do, in their sector, so well done them.
Lee Simpson: Nothing beats FLAP-D.
Paul Walsh: Yes.
Emmet Kelly: It’s quite an achievement. But what is interesting is three of the big five markets in Europe are constrained. So, Frankfurt, post the Ukraine conflict. Ireland, because in Ireland, an incredible statistic is data centers are using 25 percent of the Irish power grid. Compared to a global average of 3 percent.
Now I'm from Dublin, and data centers are running into conflict with industry, with housing estates. Data centers are using 45 percent of the Dublin grid, 45. So, there's a moratorium in building data centers there. And then Amsterdam has the classic semi moratorium space because it's a small country with a very high population.
So, three of our five markets are constrained in Europe. What is interesting is it started with the former Prime Minister Rishi Sunak. The UK has made great strides at attracting data center money and AI capital into the UK and the current Prime Minister continues to do that. So, the UK has definitely gone; moved from the middle lane into the fast lane. And then Macron in France. He hosted an AI summit back in February and he attracted over a 100 billion euros of AI and data center commitments.
Paul Walsh: And I think if we added up, as per the research that we published a few months ago, Europe's announced over 350 billion euros, in proposed investments around AI.
Emmet Kelly: Yeah, absolutely. It's a good stat. Now where people can get a little bit cynical is they can say a couple of things. Firstly, it's now over a year since the Mario Draghi report came out. And what's changed since? Absolutely nothing, unfortunately. And secondly, when I look at powering AI, I like to compare Europe to what's happening in the United States. I mean, the U.S. is giving access to nuclear power to AI. It started with the three Mile Island…
Paul Walsh: Yeah. The nuclear renaissance is…
Emmet Kelly: Nuclear Renaissance is absolutely huge. Now, what's underappreciated is actually Europe has got a massive nuclear power bank. It's right up there. But unfortunately, we're decommissioning some of our nuclear power around Europe, so we're going the wrong way from that perspective. Whereas President Trump is opening up the nuclear power to AI tech companies and data centers.
Then over in the States we also have gas and turbines. That's a very, very big growth area and we're not quite on top of that here in Europe. So, looking at this year, I have a feeling that the Americans will probably increase their data center capacity somewhere between – it's incredible – somewhere between 35 and 50 percent. And I think in Europe we're probably looking at something like 10 percent again.
Paul Walsh: Okay. Understood.
Emmet Kelly: So, we're growing in Europe, but we're way, way behind as a starting point. And it feels like the others are pulling away. The other big change I'd highlight is the Chinese are really going to accelerate their data center growth this year as well. They've got their act together and you'll see them heading probably towards 30 gigs of capacity by the end of next year.
Paul Walsh: Alright, we're out of time. The TMT Edge is alive and kicking in Europe. I want to thank Emmett, Lee and Adam for their time and I just want to wish everybody a great day today. Thank you.
(Applause)
That was my conversation with Adam, Emmett and Lee. Many thanks again to them. Many thanks again to them for telling us about the latest in their areas of research and to the live audience for hearing us out. And a thanks to you as well for listening.
Let us know what you think about this and other episodes by living us a review wherever you get your podcasts. And if you enjoy listening to Thoughts on the Market, please tell a friend or colleague about the podcast today.