Walter Hamilton:

Hello, and welcome to How to navigate the new financial landscape. I'm Walter Hamilton, editor and chief of Quarterly Insights Magazine, and I want to welcome you all on behalf of us at Capital Group Private Client Services.

Well, as we look back over the past quarter century, it's clear that investors have benefited from some decidedly favorable economic and market conditions. Those include everything from low inflation, rock bottom interest rates, conducive demographic trends, and the maturation of the global economy. Today, many of those dynamics face some level of uncertainty. In some cases, they're called headwinds. They are likely to remain net positives overall, though perhaps not to the same degree they have been in the past. At the same time though, some promising new opportunities have arisen. Those include the potential benefits of artificial intelligence, the extensive breakthroughs in medical research, and the recent jump in all important economic productivity.

Today, we're going to take a step back a little bit to look at this big picture, to look at these underlying factors that may well determine the direction of the economy and the markets both today and in the years to come. To help us do that, we're joined by two Capital Group investment professionals who think deeply about these issues. Joining us from our San Francisco office is Anne-Marie Peterson. Anne-Marie is a Capital Group equity portfolio manager. She has 29 years of investment industry experience and has been with Capital Group for 19 years. Seated beside me here in our Los Angeles studio is Jared Franz. Jared is a Capital Group economist specializing in the US economy. He has 18 years of investment industry experience and has been with Capital Group for nine years.

So, Anne-Marie, Jared, thanks to both of you for joining us today. And as always, thanks to all of you on the call for the questions you sent in ahead of time. We received a great many questions. I will try to weave as many of them into today's conversation as possible. Okay. So that is our, our intro. Let's, let's dive in right now. And Jared, I'm going to start with you for a little bit of history, a little bit of context. it's not like the past 25 years hasn't had its share of hiccups, global financial crisis, pandemic, obviously, spring to mine, but I think overall it's fair to say that this has been a generation of investors who have been weaned on some very favorable economy and market trends. Give us a sense, if you would, of this big picture, of some of the trends you think have been the most important and what they've meant to the US and global economies.

Jared Franz:

Sure. Walter, that's great set up. I'm a student of history. I love history and thinking about it, and I think there's a lot of lessons we can take from history, especially on the economic history. A- as you pointed out, we're in a very unique environment something that we've actually never seen before in the US. When can you remember that we've recovered from a pandemic, had breakthrough technologies like we have with ChatGPT, and are also seeing a complete realignment of the political and geopolitical system. We've just never been here. So, we like to kinda think about... You know, it has elements of the 60s with fiscal policy. It has elements of the 70s with the high inflation that we're in now. It has elements of the 90s with these technologies. And so, what, what does that mean for us, you know, these megatrends that we're seeing with you know, AI and you know, higher productivity growth potentially? You know, what does it mean from us from an investment point of view?

Jared Franz:

It means things are very uncertain, that we... You know, it's really hard to get locked into, like, one view. So, we like to be very agnostic, very thoughtful about, what do the tails look like? could inflation go down a lot? What are the conditions? Could inflation go back up again? What are the conditions? is the productivity that we're seeing now conducive because... more conducive because AI is coming on tap here? Or could this all be a façade and the hype is too much and, you know, AI goes back down? So, we're trying to be very thoughtful very I guess thoughtful about the outlook.

Jared Franz:

In terms of, like, what it means for our economic outlook, I'm just being really you know, binary in terms of, like, how I see things. Is it, you know... Are you we gonna see things improve? What are those conditions? Are we gonna see things that decelerate? What are those conditions? And just really work with our investment teams and think about, you know, what are those conditions that underpin that? So, we're trying to be thoughtful deep dives into all these trends, artificial intelligence, demographics and really bring ideas to those portfolios.

Walter Hamilton:

All right. And we're gonna dive into a, a great many of, of those today. Anne-Marie let me turn to you. Let me ask you very much the same question as I, as I did to Jared about some of the, the big trends of the past, perhaps the big, big trends of the future, and particularly from your vantage point as an equity portfolio manager. Give us a sense of, of some of the trends you think have been most important and are most important, and especially how you factor that into your investment thinking.

Anne-Marie Peterson:

Sure. Thanks, everyone, for being here today, by the way. all right. So, I mean, I'm... You know, I'm a big, long cycle investor, and I... You know, I like to identify tailwinds and headwinds, and what is exciting and what Jared outlined is we're definitely at a time of change. So, you know, whether it's from a macro stand- point or, you know, a structural cycle standpoint AI is on the scene. and it's gonna have an impact but, you know, as Jared said, it's (laughs) important in times like this to be curious, open, humble because you don't know what it's mean... what it actually means. and so, we're working hard on solving that puzzle.

When I think about, um... You know, one of my, one of my tools is sort of pattern recognition and when you look at the last decade, you know, even 15 years you had the internet, which basically evolved to the cloud and mobile, or enabled the cloud and mobile. And out of that you had these new, (laughs) massive companies that were born, Amazon Me- Meta or Facebook Google on the back of that. This enabled entirely new capabilities and business models. Social media, you know, advertising and these companies became... grew rapidly, became extremely profitable and ex- you know, sustained their (laughs) growth for a really long period of time and became massive market caps.

you also even within that construct had some incumbents, both win and lose. Microsoft you know, I- 2008 was sort of a loser, and they ended up becoming a big winner. They adjusted and changed their core business model to subscription. They invented the... They're number two player in the cloud. You know, similarly, Apple, redefined what a handset was, ecosystem, software and hardware. So, you know, things that, you know, even if you had the best research in the world (laughs), it's just been really hard to predict, you know, that this was gonna happen. But what you had t- But what you did do and what we did have at the time, and we still have and it's where we excel, is we have a research engine and multiple perspectives where we're, like, always, you know, scratching at, what does this mean and open to it? So that's sort of how we are with AI.

As I look at the next decade, you know, we have higher rates probably, but we've already absorbed some of that versus low rates. And then you have two what I would call kind of blockbuster trends, AI, and... or b- blo- I would say more cycle than trends, AI and infrastructure. And in terms of, you know, AI, it's still... you know, they're- we're debating. We actually spent yesterday in LA as a group asking a couple questions about AI and debating it, and there were rigorous debates on who wins, who loses? What does it mean? Is it hype? Is it for real? Is it the enablers like Nvidia or is it the users like Meta? Jared was actually joined part of that day and discussion. So, the debates are happening.

But one thing that I would say that I think is probably different about this cycle versus the last decade's cycle is I think that the incumbents are probably the beneficiaries. And when I say that you know, when you look at the last decade, it was new creation. There were low rates, so you could finance, like, loss-making business models for a long time. There were new... software models were created, software to service. Like, that had, you know, kind of low-capital intensity. You just, like, plug and play. You didn't really need a labor force to do this. Um you know, I could go on and on. This trend, Nvidia so far seems to be the arms dealer to this and has unique capabilities. There may be more competition, but this is a big, established company that's been around for 30 years with a very capable leader, one.

And let's see, two the big mega cap techs seem positioned to use this to generate a return. You know, the reason Nvidia and, um Meta have been great stocks this year, one of the reasons, is, you know, one's supplying, you know, getting growth and supplying the AI revolution, and the other one, one is demonstrating an ROI on using AI tools. So, the market's saying, "Oh, is- are these the winners," right? And I mean, let's... It remains to be seen. but on the existing assets, what I think is fascinating is a lot of both healthcare and industrials, I think, you're gonna see a big impact. And in industrials, you've had the tailwind of...

You know, you already had existing tailwinds of aging infrastructure you know, pulling more commodities out of the ground to enable EVs you know, reshoring. And now, on top of that, you're getting this sort of the AI needs big data centers and it needs power you know, so even some of the utilities. So, this is... it's really fascinating when you think about it because it... You know, it's not clear that there are gonna be a bunch of new startups. There may be, but, uh... You know, I sort of almost think it's, like, the age of the incumbent is probably more likely and that's really exciting. these companies have unique assets and capabilities. So that's sort of... You know, it's... I think it's helpful to have a framework, like I said, and then kinda go after it. But the portfolios, you know, are, are naturally sort of starting to reshape themselves and the market... This might be the catalyst for, you know, a structural market broadening.

Walter Hamilton:

Okay. the- I think that's a great... That's, that's a, a great foundation and many of these topics we're gonna be really delving into. So, so thank you for that, Anne-Marie. let me talk briefly to you, Jared, to ask about inflation and, and interest rates. Obviously, inflation, way down from, from its peak, and I think still heading in the right direction. But lately, it's been slower going. inflation is still almost twice the level, the 2% level of... that the Fed would, would like. inflation data coming out on a monthly basis has, has, has surprised negatively the first three months of the, the year. In fact, last week's numbers really started to shake the market a little bit cause it, it rattled all those investors who thought, "Oh, we're gonna, we're gonna have three rates, rate cuts this year on the... They cling to that belief. So just for the present day, give us a sense of inflation and interest rates, and where we are at the moment, and what you see.

Jared Franz:

It's the big question, probably one of the questions I get asked the most internally, even externally. hopefully, it goes away at Thanksgiving or Christmas this year. But I think, you know, one way to step back and just think about this a second is to look at what happened last year. Or go back to 2022 and say, "If I had told you in two years that interest rates would be near 5.5%," what would you think the economy would be doing at that time, right, two years ago or even five years ago, right? And I think pretty much everyone would say, "We'd probably be in recession," right. And so, we look at 2020 three, what happened, we had 5.5% percent interest rates and 3.1% real GDP. Amazing, right. That's amazing by any standard for, for the US economy. This is a $30 trillion economy growing at 3% real. That's pretty remarkable. And so, something is different, right. Something is different relative now relative to where we were before.

one thing that's different, I think, is just the labor market. The labor market has structurally changed relative to where we were pre-pandemic, and that structural change has given to more demand relative to supply. So, we still have deficits in sectors of employment like nursing, like retail, for example. So, we're still seeing deficit, a lot of demand relative to supply that's keeping wages up. That... if you remember your econ 101 textbook wages flow into inflation. That's the Phillips curve, if you remember that. you know, gold star if you do. and so that's one of the reasons why inflation has been as high, as high as it is.

as we think about what, what will happen next, right we... It looks like we've gotten over the hump of higher wages for now. We are not those 6% wages that we were seeing during... at the height of the pandemic. But at the s- At the same time, we're not back to the pre-COVID wages that were more like 2 or 3%. So, we're at that... We're kinda in the middle. We're in that middling area. We're at 4%, and we're heading, I think, down to 3.5 and eventually to 3% in the next couple years. So, I'm optimistic that the labor market is slowing but not contracting. So, it's not a recession, but it's slowing as the labor market reequilibrates demand and supply. That'll... That by itself will take a lot of heat off of inflation just with the labor market slowing a bit.

the other thing that I think is remarkable as we think about the US economy relative to where, where it was and where expectations had been, that 5.5%, why are we in a recession? another thing is, is, is kinda interesting is you know, if you go back to the 70s and think, why did inflation get so deanchored? Why did inflation go up to 8-10% and why did Volcker have to slay inflation? And if we go back there, one reason at least in my view, one reason is because inflation expectations weren't anchored. And so, this is a big buzz word in economics. You'll hear it probably even in The Wall Street Journal, but ... economics, you'll hear it probably even the Wall Street Journal. But they, they weren't anchored. And what I mean by that is that, you know, people didn't, when inflation went to six and seven and eight in the '70s, people were like, "Oh, okay, that's the new normal." And there was no expectation that the Fed would come in and do anything it took to get inflation back down to 2%. And so, I think that was one of the lessons that the Fed took from the '70s, and that you see this in modern macroeconomic textbooks, is that keeping inflation anchored is job number one of the Fed.

how do you do that? Is to establish a lot of credibility and to prompt, you are gonna get inflation back down to 2%. So, as we got those big inflation jumps as we did during COVID, the market believed that credibility and believed that the Fed's gonna get inflation down to 2%. And so, I think that's another thing. So, labor markets are coming down. Inflation credibility is there. And there's some kind of technical things that are happening under the hood of inflation. one of which is that rents, these are, you know, when you go rent a house or, and there's a concept called owner's equivalent rent as well.

these are big parts of your budget. You know, we pay housing. that's a big part of your budget. The way the BLS is constructed. I won't get into the gory details fortunate for everyone here, but the way the BLS constructs these measures is that there's a severe lag. And so, the rents that were, you know, 5% today, let's, let's just say won't get into the BLS measure for another eight months, nine months. And so, there's a c- there's a, a built-in lag to that.

What we know now is that, that those rental measures are slowing. And so, I'm optimistic that we won't get back to 2%, a- this year. maybe we'll get closer next year, but I'm actually having us get back to a real kind of more anchored 2% until 2026. But we're gonna make progress on, on inflation. So, we're gonna be near 3% at the end of this year. And then slowly getting down to 2%, that's, that's my base case view.

And then once you have your inflation view, you can start layering on what you think interest rates are gonna do. And so, in this world if I'm right in this world, then the Fed will be able to cut rates a bit, not a lot. We're not going back to the pre COVID, 0%, 0% interest rates. but they'll be able to cut rates maybe twice this year maybe four times next year. but they'll be really focused on this inflation question because again, it's the credibility of the Fed that's enabled folks to not just extrapolate the inflation of COVID into the future and really try to get it down.

So, they'll be watching that. I have two cuts this year for cuts next year. But again, going back to what we said at the top, why is this era different than where we've been in the past? we're gonna be at higher rates for longer. And so that's the short end of the interest rate curve, you know, where, what the Fed controls. And then you have the 10-year treasury. that's that, you know, 4.7 today, that's normal to be between four and 5% with an economy that's growing at, you know, 3% real that I don't think is going back down to four or three or two or one that's gonna be higher for longer.

And so, we're gonna live with these this, this new, or we call old normal, because that's, that was normal before, you know, the GFC into the future. And that's how I'm thinking about at least the inflation dynamics and interest rate dynamics.

Walter Hamilton:

Okay. That, that, that, that all makes sense. okay. So, two things here. One, I actually do remember studying the, the Phillips curve in my Macro 101 textbook.

I believe it was Baumol and Blinder for the record, but don't hold me, hold me to that. I haven't looked at it any number of years. but more important, let's, let's take a step forward. Now, look to the future, right? You mentioned hire for longer. The, the mantra for so many years was lower, lower for longer. And, and Anne-Marie broached is part of the reason why it's important because it was, you could finance cheap money losing companies, right?

Mo- money was cheap. It's, it's still historically cheap, but it's not as cheap as, as it was, as we look forward and project down the road, how might higher for longer affect the economy, even on the, the margins in, in all these sorts of corporate decisions and other things.

Jared Franz:

Yeah. And no doubt money is gonna be more expensive going forward. and there's kind of two ways to think about that. Good, good way or bad way. the, the good version of this, of this narrative or this this scenario is that yes, interest rates will be higher, but so will real, real GDP growth, so will income growth. And so, if, if that's, if that's a good version, that means that yes, your financing costs are gonna be a little higher than they were pre COVID.

but you're, you're gonna be generating more top line revenue, right? So, you're, you're nominal your top line, your revenue growth is gonna be more like a 10%. This is a GDP 3% real at a, you know, another 3% for inflation. You're at a 6% nominal GDP economy. Company operating in that environment on average should be roughly in line with GDP. This is twice the rate that we had pre COVID, right? So, it's a much stronger top line growth.

And so that's a good version, that's a good version of yes, you're gonna pay a little higher interest rate, but your top line revenue growth is gonna be better. So, you can offset that. the bad version is that you are going to have higher, you're gonna pay higher interest rates. but we're also gonna go back to the slow growth that we had after the GFC, that slow wage growth, that slow top line growth that were in some type of what summers called se secular stagnation, which he took from the 1950s and '60s.

but that we're, we're just, this is all a blip, and we're gonna go slower into next year and into the next decade, let's call it. That's the bad version that we have all the high rates, but none of the benefits of the high, high top line growth. Now, personally I'm in the more constructive camp, and there's a, there's a couple reasons for that. And Marie pointed out already the work we've done in internally on artificial intelligence. I did my dissertation in technological change. And so, this is one of my favorite topics and what, what we've learned in economics is that we don't measure productivity well. It's really uncertain, it's really difficult. we've tried a lot; we've tried really hard, but we don't have a really great way of kind of forecasting productivity in a structured way. But what we do know is that we think it's related to technological change over very different and long lags. And so, if what Anne-Marie's saying you know, about companies and the way there, you know, taking on AI, we think as economists, the economists, we, not the capital group, we, but we think as economists, that that will have eventually feed into higher productivity growth for you and I and for the economy as a whole.

So again, we're going from a low productivity economy after the GFC, which was like 1.5% to something that I think could be double that 3% productivity. So almost like a '90s productivity boost. So, it's a much different world higher productivity means typically higher wage growth for labor. Anne-Marie also pointed out the importance of CapEx and the spending that's happening in the economy. When we get that spending going, that's like a new computer or a new pen everyone gets new stuff that usually is high, higher productivity. So, I'm in the former camp in, in the sense that I think it'll be a good version of, of the story going forward.

And then, then when I look at the US and then I look at other economies like Europe or even Japan we're just almost a singularity relative to those economies. We already have the strong productivity growth. Now we've had the decoupling in productivity for the last, you know, decade or, or more. And so, I think for me at least, I'm, I'm pretty constructive on the US.

Walter Hamilton:

Okay. That's, that's good. Good to hear. I, I was hoping you were gonna go for the former rather than the latter. So, I'm, I'm relieved. Anne-Marie, let's, if you can sum up the market in some ways in one word, over the past 10, 20 years, technology, and you, you referenced it so well in, in the opening. Let, I got a couple of questions for you. But let me start with the Magnificent Seven, right? This is the, the sort of unofficial tag name that's been given to these seven mega cap tech stocks, some of which you, you mentioned at the open.

And, you know, and for good reason, right? These are bellwether companies. They're on the cutting edge of the AI revolution. On the other hand, I mean, they, they dom- they've come to dominate the market so much. There, their valuations are sky high at the moment. and, and the level of concentration in the market is so high, they're, they're rising disproportionately to everything else, which I don't think really has, has longevity and staying power. So, give me your, your thoughts on the Magnificent Seven, what it means for the market overall, how you're viewing it.

Anne-Marie Peterson:

Yeah, sure. thanks for the question. well one, I mean, remember not too long ago the Magnificent Seven was fang and then something changed, you know, and the end came out. So, the Netflix part of it. So, I think, I mean, I think it's important to, you know, kind of understand when we're talking about these companies, really what we're talking about is big, you know, tech ex Tesla companies that have, you know, that are dominating the market cap and have dominated, you know, very, have had very strong growth.

but there, these are different businesses with different end markets. So, they're, they're not just one thing that's number one. they do benefit from some of the tailwinds. And number two, I'd say, look, you've already, you're seeing this year divergence with the Mag Seven, there have been two outperformers, you know, the Ma- it's roughly up 15%, you know, as of a couple days ago, Nvidia has been up 80 is, Meta up 40 Amazon up 20, and then the others are lagging.

And the Russell's just a couple points ahead of the s and p. So, this is the first time you've kind of seen that divergence in a while. And in fact, you know, Tesla's really had some problems and, and Google's kind of lagging. And, and so why, why is this, you know, I touched on it earlier, the market's saying it may or may not be right, but Nvidia's the winner and Nvidia, you know, based on our estimate, it's trading at 30 times earnings and growing, you know, in the '20s. So that's actually not super expensive.

You know, Meta is growing double digits and 25 times earnings. you know, Amazon and Tesla both have higher multiples. you know, Tesla, they're, you know, again, different end markets concern about maturing of the cycle, sub- subsidies, you know, coming off and foreign competition and hybrid competition. Those are, you know, fair concerns. You're at a different kind of stage. Google there's a debate. Is AI bad for their core search business or does is Google well positioned because they have the, you know, massive compute power and YouTube is fodder for AI data.

I mean, we are having these debates. So, you know, there might be a signal, there might be noise in it, but I'd say, you know, the first point is the Mag Seven, you are seeing some signs of change. The valuations aren't totally crazy. and so, you know, what I really think is, you know, just critical at times like this is we have this deep, broad research effort. It is structured in a way to see things within industries and across industries and solve the puzzle.

This is a time when our stock picking should shine both in terms of identifying, you know, new winners, old winners, (laughs), and new losers, and, you know, some of the old losers. So, you know, and our time horizon should shine too. I mean, this is a puzzle to solve that's gonna play out over multiple decades, not just in a given... I mean, I see multiple years, not just in a given year, you know, a decade's, a long time series of multiple years. So, I, I think it's kind of interesting. And then I'd say one other thing, you know, two of the strongest performers, one of the strongest performers that's massively beat the Russell over the last five years is Eli Lilly.

We can talk more about healthcare later. but there are oth there are others. There've been many stocks, so they get a lot of attention. But there's more going on, there's been more going on there. And I think you'll continue to see more happening outside of the Mag Seven where active managers can really differentiate themselves in our research in Horizon Ken. I might also point out Caterpillar's been an, you know, excellent, excellent investment, again, driven by fundamentals, low starting valuation, and we think that there's, you know, probably more opportunity there.

So, Jared, I leave it to Jared, like you listen to his incredible insights to kind of lay out the scenarios. you know, for the macro we're focused more on the micro and, you know, macro at the edges. You know, depending on, you know who you are. I'm more of a, a micro investor.

Walter Hamilton:

Okay. So, so let me, let me then stick with some more, another micro question for you. We've talked a lot about AI, but mostly through the eyes of big tech. Talk to me, if you would please, about all the other industries that are out there experimenting. What's this gonna mean for a business? How do we benefit from this? How do we adopt it and adapt to it and so forth? We ourselves, in our industry, our own company, we are going through all of these questions, and I think there's a lot of opportunity out there for, for industries, sectors, companies that can, that can get it right over time. Give me a sense of your thinking there in the exploration you're doing.

Anne-Marie Peterson:

Yeah, no, it's a great question. because, but where, where I'd start is if you kind of go back to the internet, you know, when that, you know, in the late '90s there, now it's ubiquitous. You know, everybody, we were talking about this yesterday. One of our PMs was like, look, everybody on industry strategy, you know, internet strategy. I mean, the real question on AI is who builds a competitive advantage using it? Where, where, where are their dur- where's their new durable growth because of it? So, I think that that's, you know, it's really important.

I think if, you know, if it's as big as we think it's gonna be ubiquitous it's gonna play out over a long period of time. But what's interesting, forcing innovations across-

... but what's interesting forcing innovations across a variety of industries, right? So within, you know, AI requires more, it's gonna require more data center, more power. You know, we met with, you know, a big chip company and they were saying, "Look, we're working trying to figure out how the chips use more, less power," right? you know, the utilities are trying to figure out how to make power more efficient. So, there's kind of a lot going on there. in terms of the, you know, the other beneficiaries or just kind of how I think about it, I should say. You know, I start with, I, I like to see companies that have survived technological or s- some sort of disruptive change. I think really looking at the past around now is more important than ever.

I think managements and culture team, and cultures and teams this is when, you know, you can really differentiate yourself. You, you need an, an, a mindset of change, a willingness to adapt and think about, you know, creativity. How can we develop competitive advantage for the, through this? So, you know, for example, we were talking about the banks. JP Morgan has been asked by you know, the regulators to test AI. Are they advantage and testing AI? They're finding it's taking out a ton of cost outta their processes, and it's gonna allow them to underwrite loans better, you know, and reduce losses, or will that be commoditized like other innovations in, the banking industry has? So, you know, it's, it's a really, it's a complicated question.

I tend to think, you know, when I look at for example, the industrials, the industry structure matters. Usually there's like one or two players in an end market. It's really hard to, you would not be able to create like these companies from scratch their capabilities or their assets. And so, the odds of them, you know, for example, Deere is, and, you know, has AI generated services that can, you know, help the farmer get more out of there, you know, their crops. They're getting like a, you know, 60% more yield. And, you know, so the ROI for them on this little service is tiny. And Deere has another, you know, they're getting paid a little software fee, so they have another revenue stream. So, you know, it's, it's important to start thinking through the, you know, kind of details. And we have the analyst, and you know, expertise to do that.

So, but I think, you know, I... And then the other part too, on the labor, one, one thing that I think is really interesting about AI is, you know, people are like, "Oh, gosh, no, it's gonna kill a bunch of jobs eventually." Maybe. But in some cases, AI is an enhancer because labor is a constraint to growth. So, for example, Synopsis, it's a chip design company. They're already using AI to design their chips, and they can do more, because what's the constraint? Engineers are in short supply. So, it's enabling, it's a growth enabler, not a, you know, an enhancement of what they already have. so, I think it's important to just even think about, you know, I'm throwing out Walter, a bunch of different kind of angles on it, but I wanted to give you a flavor for kind of the depth and breadth and sort of second, third, fourth derivative thinking that we're, you know, exploring around these topics.

Cause it's really, it's important to kind of look for it. It's important to kind of be clear about what, what metrics you're gonna mark along the journey. What are the KPIs that we're looking for across the industries? how are we gonna know when we see it? We have inklings of things, but, you know, let's be humble as it's really early, things will evolve in ways that we can't even imagine. But again, it's exciting.

Walter Hamilton:

Yeah, no, I think that's a, that's a, a great overview, and it's actually a great segue into my next question, which I wanna pose to you, Jared. Which is one of the things that we do at Capital Group was we do deep, deep research. We think about things deeply. we, we debate them. And as you both point out, we, we're not claiming that we, we know exactly how things are gonna go. There's a, there's a lot of debate, a lot of back and forth to hopefully end up at the, at, at the right conclusions. one of the things that I know you've been focused on, I didn't know it until you mentioned it now, about you, your, your degree in it, but your dissertation is, is AI. It's something you've studied for many years.

In fact, I remember a luncheon that you appeared at for Capital Group Private client services, in which you talked about, and I'm sure many people in the audience, you know, were like, you know and not realizing the, the import that it would have in coming years. So, gimme a sense of your understanding of AI, your, your studies of it, and then definitely tackle the white-collar employment issue that you would, that, that Anne-Marie brought up. I'm sure everyone on the call, I know, I'm, I care about that, that issue. So, set our minds for ease about that.

Jared Franz:

I mean, I care about that issue.

Walter Hamilton:

Yes.

Jared Franz:

'Cause I, like my key, key badge to work every morning when I come into LA here. you know, Anne-Marie brought up some really good points, and I'll try to riff off that a little bit too. But, you know, when this latest and greatest AI version came out you know, roughly a year and a half ago there was a little bit of deja vu because we have seen this before, and folks will, will, who, who attended the PCS event will know back in 2017 that there was a prior up upswing in AI, and that was based on deep learning machine learning. and that was really important. And at that time, we had the same white collar job loss. McKinsey wrote a big report on, on it.

we also had the same questions on, you know, will the Terminator evolve out of this? Right? And so again, fast-forward to now, where are we, we're kind of asking the s- the same the similar question that we asked back then. But what I like to say about this current iteration of AI is that it's you know, it's new but not new. where we are in this arc of artificial intelligence had been seeded back in 2014, 2015. And even if you're a really a student of this, it was seeded in the '60s and '70s, right? So, it has this very long arc, and we're just seeing the, the, the latest iteration of this.

Jared Franz:

That's important because, you know, as we think about, you know, the winners and losers as Anne-Marie pointed out, it's really good to have a sense of the history, the history of artificial intelligence. If we're right, if there's a kind of a code word, and it's gonna be an Econ 101 exam, I think inadvertently. but there's something in economics called a general-purpose technology. It by randomly has the same initials as GPT, and we call it GPT. It has a different context in economics. But a general-purpose technology is something like electric, electricity. it has a large and broad impact on different industries, consumers and businesses across the economy and across the world.

Jared Franz:

If we end up being in a situation where this is a GPT, I think there's actually a lot of good reasons to think it is gen-AI and LLMs and the things that were evolving out of LLMs, that it'll be a GPT, it will have a big impact on multiple sectors of the US economy, global economy, and that's true. one of the things that Anne-Marie pointed out, which is a great point, is that it, it affects everyone the same almost, right? And so, having that distinct advantage will be harder because everyone has it, right? You can go onto your phone, onto your laptop and look at ChatGPT and type in a type something in. Businesses will be able to do this. They're gonna partner with you know, these providers to have their own GPTs for their own companies.

Jared Franz:

And so, the advantage gets whittled away a bit. And where you want to see kind of to get that excess return, is where you have a unique advantage, right? And that's where I think Anne-Marie pointed out, like in the verticals, we might actually see some of these unique advantages, whether it's in agriculture or in industrials or what have you. We might start seeing those unique advantages, because where that comes from, and what we've learned from this is that the, the data is the gold, right? The data is the gold. And so, if that's true, then your company's data, your personal data, that is where the gold is. And having those distinct advantages over time is where we're gonna find for different companies where we're gonna find that excess return, in my view.

You know, I'm gonna just name a couple of these. I wrote these down Walter before I came here, because I think like, gen-AI era is full of these contradictions. and one contradiction is how fast the frontier is moving. The frontier is moving fast. Like what I wake up in the morning, I kind of have anxiety because I'm thinking about the latest research that has been done in gen-AI and it's just daily, you know, better models, more energy efficient different techniques. The transform architecture is changing, right? It's evolving so fast, nothing like I've seen before and much faster than in 2015 and 2016.

Yet contrast the speed with what, what's happening on the frontier with what's happening in enterprises, right, what's happening in businesses. Census just did a great survey a couple weeks ago where they, you know, surveyed a lot of firms in the US over 2000 and asked, you know, where are you in your AI transition? And roughly 5% of firms, and this is a lot of firms, right? So, it's not just big firms, you know, its small firms, medium-sized firms, different geographies, different industries, 5%, 5% have are using AI in a product or service. That's still low. That's pretty low, right? A lot of runways to go here, right? The next question, one of the other questions they ask is that what's your plan? And there you have more acceleration.

So, as they look out to 2025, 2026 you know, it's 40 to 50% acceleration in these, in these gen-AI things that they're trying to think about. So low, now, a lot of runways, so fast at the frontier slower at the enterprise. it's like prior technological revolutions. You know, Anne-Marie brought up the internet like the '90s it's, it's a big breakthrough, but it's also totally different because unlike you know, the internet revolution, you're, you know, digging ditches to lay fiber, right? We all had to figure out what a modem was, what the internet was, right? And, you know, there was this kind of a learning by doing process, right?

now the latest update is instantaneously on your phone, instantaneously. You get the latest update instantaneously on your phone. The deployment is so much faster than anything we've seen before. So, there's a couple ways in terms of like how, you know, I'm thinking about it. and, you know, I think what we try to do at Capital is also just think about these different nuances. What's different, what's the same, and how can we take advantage of that?

Walter Hamilton:

Okay. Wow. Great. Okay, so let me, let me ask you now, let me shift gears and stay with you, Jared. Let me ask you about another one of these big factors that's undergoing some significant change, and that's the, the restructuring of, of international trade. And, and to a, to a lesser degree, I mean, questioning really free market orthodoxy and even then, the need for global integration. globalization's taken hits for, from a lot of things. I mean, obviously supply chains during the pandemic and obviously ongoing our, our, our you know, trade tension with China. We could do a whole webinar on globalization itself.

But I want to ask you one thing in particular about French shoring, which is what company for example, has a factory in China, but they decide to build another one in, say, say, Mexico. They want to be closer to home, closer to their end market, and also in, in more politically friendly environments. the logic of globalization in the first place was to cut costs. We're going across the world because we want, we want cheaper labor and, and so forth. And French shoring would seem to add costs. So, looking at it strictly from an, an economic viewpoint, is French shoring as needed as it is, is it a potential economic drag? As we, as we move forward, how do you think about this?

Jared Franz:

You know, it's an, it's a really important question. The way, you know, I, I think I totally agree with you in terms of, you know, it's a drag. I wouldn't say it's a massive drag, right? So, what we're seeing in the data and what we're seeing from companies and from countries is that yes, you might move out of country X, but you're gonna move out of that country and go to a very nearby country to that. so, let's say China, you go to Thailand, right? And so, the cost of that, now you got that one-off, like cost of doing that, but they're finding is that, you know, it's roughly the same input cost as you would with China. It's not materially different.

In fact, you know, if you, what happened, you know, 20 years ago with China is that they had a very low-cost basis, right? They had very low wages in that country, and they could make things very cheaply. Over time, that's been eroded away as that economy has developed and as wages have gone up. And so, this was already happening. The dirty secret is that it was already happening kind of before all this, and there was already a progression towards, you know, other lower cost environments. But it's definitely you know; a one-off type drags for these companies. companies are finding that, you know, their supply chain matters and so they're trying to build in this resilience going forward. And so that very lean efficient supply chain with only one supplier is going to turn into maybe two or three suppliers. So, you have that redundancy built in, and maybe one that's a little closer.

In terms of the actual data trade in terms of the, the way French shoring has worked, a lot of that's gone to, to Mexico, right? A lot of French showing has gone to Mexico. Now we have supply chains in Mexico that are much closer. That was already a big part of like autos and OEMs, and so that's built on that. what we're also seeing is that China going to Mexico to start building manufacturing plants so that they can supply to the US from there. So, there's also, you know, with every reaction, there's a reaction with every, you know, supply chain change, there's also a change on the other side from the, from the country that's the recipient of it. And so that's happening.

I think an interesting dynamic kind of underlying all this is that, you know, there's gonna be a political trade off. There's gonna be a political trade off here. How much can a given political system sustain from very low-cost inputs? Because that disrupts, you know, the labor market in the domestic... low-cost inputs, because that disrupts, you know, the labor market in the domestic country, right? They- they want ... Every country wants high wages and their people to be happy, I think. maybe most. but so that ... It does change the dynamic so that instead of getting very low-cost goods from China, or from other countries there might be a trade-off where they say, "Okay, we're not gonna just ship this from our country. We're also gonna build a factory in your co- in your country. So, we're also gonna build a factory there." And so, that- that's something we're seeing. That's something we're seeing that's going to be part of the debate in the US, it's going to be part- part of the debate in Europe.

And kind of to wrap around this is that the friendshoring question is complicated. We're not de-globalize- de-globalizing right now. We're actually just reallocating; we're reallocating these supply chains differently than we did in the past. Now, will it have a higher inflationary impact? Yeah. And so, one of the big changes that I, that I did before you know, I guess five years ago, I ... I'm a techno-optimist, you know, guilty as charged. I'm, I've been in the techno-optimist camp for a while. And we know technology tends to have a disinflationary or a deflationary impulse. But what happened, you know, five years ago was that, you know, this reallocation of supply chains, that looked more permanent.

That looked like something that wasn't just gonna be something that is temporary. And what I ended up doing was saying, okay. Well, my low inflationary forecast that I had kind of gone with for a while, you know, being under a close 50%, probably not going to be the same anymore. And so, I'm taking that friendshoring, taking that reallocation question and actually building it into my longer run forecast so that inflation is gonna ... That 2% which we struggled to get up to after the global financial crisis, we struggle to get up to that, I think it's gonna be we're, we struggle to get below it is going forward. And friendshoring is just one of the many reasons that could be the case. But that's how I'm thinking about it now.

Walter Hamilton:

Right. That- that all, that all makes- makes great sense. okay. I think I have a- a couple of questions left. So, we have a little bit more than- than 10 minutes or so to go. So, I want to stay first on the friendshoring question with- with you Anne-Marie, because the- the flip side of all this is it, is it does spell opportunity. we mentioned Mexico. recently Mexico surpassed China as the biggest importer into- into the US. And I think that's all a part of this- this friendshoring issue. And it also has great opportunity, I think you mentioned infrastructure before. Infrastructure and industrial-type companies. You know, when you build a facility, you need construction activity, you need HVAC, you need transportation, distribution, all of these things. Give me a sense of the opportunities in some of the sectors or industries that might benefit from this friendshoring dynamic.

Anne-Marie Peterson:

I feel like I keep talking about industrials, but, eh, I think all roads lead to a potential golden era in industrials in the next decade. you know, you ... Over the last decade, you've had, you know, kind of basically sluggish demand and there's been lots of outsourcing and superfic- ... This is a Capex cycle. There are many factors driving a Capex cycle, where you have constrained capacity and constrained capabilities. So, you know, for example, Eaton, and this isn't a reshoring thing, but this is just giving you a constrained, um you know, point on constraint. They are sold out, one of their, you know, capabilities for data centers for five years. This is this kind of stuff is sort of happening. So, the reshoring is just yet another factor.

All the companies we meet with say that they're looking at, you know, how can we build in resilience? And some of the companies, some of the outsource suppliers, this is sort of the boon to them, and, you know, pharmaceutical manufacturing. I mean, this will be good for, you know, the, like the tool’s companies and, that have, you know, capabilities like all over the world or where things are specked in. So, I- I just think that there's like a ton of ... I don't have ... You know, Jared really captured it. There are lots of things that are happening, but if the headline is, you know, the industrials were GDP-plus cyclical growers their GDP-plus-plus-plus with a secular tailwind. That has positive implications for the growth rates over the long-term, but I believe we're underappreciated at many of the multiples. It has positive implications for the quality of the businesses. So, there's lots going on when you, you know, kind of look at that sector. and it's very exciting. But there is other, you know ... For example, Apple, I think there are a lot of concerns that, "Gosh, they are incredibly dependent on China, and it's really hard ... " That- that can't be solved ... You know, they're working on it, but that can't be solved overnight. Not just in terms of, you know, phone sales, but in their manufacturing capabilities. So, we're really asking a lot of hard kind of questions around that.

Anne-Marie Peterson:

But I- I do think one of the things that our system's really good at and our analysts are very (laughs) good at is when something's changing, the market takes a long time to kind of figure that out, the nature of something. They started to have a stale voiceover on, "Oh, Caterpillar's a cyclical," or, um ... But there, um ... You know, and then the growth starts showing up. And- and in the meantime, these companies have become much more efficient in their manufacturing operations and- and how they utilize their plants and even streamlining their product lines and innovating in their capabilities. So, Walter, I feel like I'm over-talking the industrials-

Walter Hamilton:

No, no, I think you're doing a great job. You're- you're- you're- you're capturing a lot and I always know it's a good session when I have a list of questions, many of which were not even gonna- gonna have time to get to. So- so, we'll m- we'll- we'll have a part- part two of this at- at some point. So, let me ask I think one final question. I'm gonna di- I'm gonna direct it to you, Anne-Marie, because I do want to talk about the medical breakthroughs that we talked about at the, at the, at the open. A lot of great medical innovations. the weight loss drugs are the- ... Have gotten all the- the headlines. Rightfully so. But there are a lot of others. Talk about the medical breakthroughs, what you're seeing, how you're thinking about it and approaching it.

Anne-Marie Peterson:

Yeah. Well, it's really interesting about these GLP-1s, is one, there are two companies, you know, Eli Lilly and Novo Nordisk that have, you know, capabilities in like insulin and diabetes. but they have parlayed into these weight loss drugs. it's a duopoly. I won't go into the details, but it's really hard. And one of the reasons, which is, which is different than the past. Now, they have patents that are protected, but there are reasons to believe that they're ... the life will live, you know, even beyond the patents, that they're not going to be subject to the generic, which is really interesting because when you think of pharma in the past, and this is another industry where I think there's, you know, something's powerfully changing.

In the past, you know, they, the ... Generics would come along the- ... Part of the reason that's not gonna happen is these guys have to manufacture the ca- this themselves. The capital requirements for drug development and the complexity requirements are really high. So, that's number one. Number two not only are these, you know, weight loss, but the indications, you know, just today came out that, you know, that the drugs address sleep apnea. Lilly put out data saying, "Okay. What does that mean?" That's like a-, you know, another place they can treat, if not cure. What happens? ResMed, the sleep apnea stock goes down. So, there are whole new sets of winners and losers.

And then when you look at pharma as a percentage of the healthcare pie, healthcare's 17% of GDP in the US. Pharma's 10% of the healthcare pie. It's a small piece. It does all the innovation, all the risk-taking, spends all the R& D. Does it deserve to be a bigger piece? Potentially. You know, pharma has grown the last couple of years at 8%. There, the en- ... That segment, the others have grown at half that rate. Some people say, "Oh, the- the drug costs are high," but the ROI and what they do, it's just huge because they solve so many other problems. So, it's really interesting. Just for fun, one of our colleagues yesterday said ... Made the point that which was interesting. He said, you know, "The iPhone when it came out, it sold for, you know, 700 bucks or whatever."

I'm just doing the math. He's like ... But, you know, simplifying, you know, that some are expensive. But he said that, you know, "GLP-1s, like, can cost like 500 bucks a month to take and you're on them forever." So, it's like 40- ... You know, and the iPhone replacement cycle was every couple of years. So, it's like 40X over a couple of years of dollars, versus an iPhone. Like, think about that. That's- that's pretty profound. And then, you know, the knock-on effects of just lifestyle and solving problems. So, I- I- I think it's, I think it's really interesting. And the other thing I'd say is now I'm gonna tie it back into AI, is AI is, has the potential to fundamentally change how drugs are developed.

Earlier this year we had Nvidia's head of their healthcare practice, they're developing tools for industries. They have different industries that they target. And came and talked to us and a bunch of pharmaceutical companies, executives and scientists, and they ... We had a panel, and they were talking about the ex- the hardest part of drug development (laughs) is just finding the target. And AI enables that and they're ... These companies have higher R&D budgets. The average pharmaceutical company I think spends, you know, roughly 20% of their sales on R&D and the hit rate is just so low. So, what could happen if this industry had longer cycled, higher hit rates? You know, they're so many other thi- ... You know, and then other ...

so, it just, it's- it's- it's really exciting and curative for disease and it have kind of negative knock on ... Positive knock-on effects on- on people and their health and disease. And negative knock-on effects on the other part of the industry. So, it's a really exciting, it's a really exciting time. I mean, it could, you know, it also could be ... Someone pointed out the other day, "Well, maybe AI means the ends of pa- end of patents." Maybe that's bad. Just to give you, y-, uh ... I'm saying all this to give you a flavor for how much great work we have to do ahead of us to solve this puzzle. It's really exciting.

Jared Franz:

Can I, can I jump in on-

Walter Hamilton:

Yeah, please-

Jared Franz:

... on the macro?

Walter Hamilton:

... please do.

Jared Franz:

I'm so glad Anne-Marie brought this up, because being the nerdy economist that I am, I wrote a report internally called GPT, GLPs and GDP, because I like alliteration.

And just to riff off what you said, I agree with her kind of on this GLP thing. Like, we're only scratching the surface and these drugs will get better and over, in- in time. But then you think about the macro implications, right? if people are living longer lives, what does that mean for retirement? if people are living healthier lives, what does that mean for productivity, right? And so, then you get into this snowball effect of you know, when you have these, these continuous changes going from zero to one, something not happen- ... Something not being there to something being there and you really think about how that impacts not only the companies that Anne-Marie pointed out, but also the economy. It's really interesting and you take that out, you know, den- 10, 20, 30 years you could be, you could see very different types of dynamics than we're seeing now.

Walter Hamilton:

Okay. Wow, these are I think a- a great upbeat way to- to end the session. As I, as I say, I mean, there- a lot is gonna be left on the cutting room floor today, because there are entire topics (laughs) we didn't even get to. But I guess I'll- I'll wet everyone's appetite for- for next time. And I would point out that the one word that no one uttered today, and we gave you a- a break from it for 60 hours, is the election. Now, part of it is because so many of these- these topics are ongoing and- and really aren't affected by- by politics and so forth. But also, because we do have coming up for all of our clients a couple of election specific webinars coming up in current months as we get ever- ever closer to that.

So, that's what, that's what's on the- the doorstep to- to look forward to. So Jared, Anne-Marie, I want to thank you for- for being with us today, for- for sharing your thoughts. Again, to our audience, thank you for- for joining us today and- and for the great questions. If you didn't have time to get to your specific question, please do reach out to your, to your private wealth advisor, because- because as we said today, there are a range of things that our people spend a lot of time thinking about and- and researching. Before we let you go, we have one last request of you please. A brief survey will appear shortly on your screen, we would greatly appreciate you taking just a moment to fill it out. Your response provides really valuable feedback that helps us shape future events. So, once again, thank you all for being here today. We look very forward to seeing you at our, at our next event.