There has never been a great technology that has not had a significant drawdown in stock prices, which is code word for saying what some would say, there's a bubble forms. We're having economic growth projections that are 50% above the consensus. Our projections are AI is going to affect 80% of the occupations at twice the rate of the personal computer in four years. The personal computer took 15. Either the trend for growth is going mature a higher because of the innovation of AI that overcomes the demographics and that levels we have. That is by far a most likely outcome. But if AI only manifests along certain techniques, if it only automates, which means it has not become a general purpose technology, we use it all. But it's like the farm tractor. That would be disappointing and then that sets an emotion this eventually, not today, not tomorrow. But you get fiscal pressures because they're already high. [swoosh] You're watching Access Returns, a channel that makes complex investing ideas simple enough to actually use where better questions lead to better decisions. I'm Matt Ziegler, Justin Carmono, is co-hosting with me today, our guest. Global Chief Economist and Global Head of the Investment Strategy Group at Vanguard down the street from me in Pennsylvania, author of the 2025 Best Seller, coming into view how AI and other mega trends will shape your investments. Joe Davis welcomed Access Returns. Thanks for having me. Pleasure to be here. I was telling you before we started recording, it's worth saying it. If you haven't seen it, copy this book, make sure you check it out. I think of the books that my team at Sunpoint are RAA, like all held up and said, "This is really, really cool. This book is one of them. Thank you for writing it." Well, again, we didn't aim to write a book. At least that wasn't the goal. Our goal was to try to get a handle on where AI could go several years ago. And how would that compete with some other serious trends, which we're going to probably talk about today. Again, all the proceeds from the book go to charity. But if it's helpful for audiences, really smart audiences, but perhaps not read an economic white papers every day, that was the goal was to make it accessible, possible to a really smart and savvy investment audience. So, I'm taking you right here first, which is basically one thing I love about your work is the embracing of quantitative frameworks. And not in the way that loses touch with reality. So, how should investors think maybe differently about macro when they zoom out to that long-term lens? Because you see it kind of in a unique way. And a lot of professionals, they just underweight the slow moving nature of the way you're purchased. And I think that was even a learning to myself. And I've been in the business over 20 years. I think there's a standard approach which looks at the near-term economic contours of the data. You can think of GDP or the inflation rate, what the federal funds rate may be doing. And then of course there's a mapping implicit mapping or explicit to the bond market and the stock market. We do all that, but what we've added and what we spend some time, which is behind the book in the analysis, is looking at the evolution of these longer-term trends too. And what I found fascinating is that when those trends start to change, which can happen on a regular basis, they themselves affect the near-term, not just some long-term assumption that say, "Hey, I'll worry about that 10 or 15 years from now." It affects the business cycle. And so, what we concluded two years ago with AI is that that was going to have implications not just for the next five or 10 years, but it was going to affect the economic growth, projections, and everything we care about in 2027, 2028. And so, here we are. So, that's been the eye-opening, is it integrating them? They tend to be separated in an academic sense, the near-term business cycle, like the federal reserve, asset prices, which all of us care about as asset allocators. And then this long-term trends are sometimes kind of left to the side, or just thought loosely, what we did is to simply integrate them in a numerical way. But that's affected our approach to not just our long-term assumptions, but our near-term ones for the next several years. So, let's talk a little bit about the four structural drivers that are in this mega-trends model. You guys came up with technology, demographics, fiscal deficits, and globalization. Walk us through the framework. Well, and again, that's taken some of these long-term trends, which we all know exists. I mean, we didn't bring anything new. We certainly didn't make up these factors. They've been known for over a century. That they can impact long-term standards of living, long-term economic growth. I mean, you can't talk about long-term productivity in standards of living without talking about technology. And yet, there's just, again, park to the side when you think about, hey, what's my outlook for the next year or the next two years? And so, we brought them in. It's effectively a fancy way for saying that there's supply factors and demand supply, the supply of workers and people. So, that's demographic factors. The Asian of society, immigration, you can think about that. Globalization factors can be in the headlines. It's the openness to trade. It's also tariff rates. And then you also, it's the rise of China into the world trade organization. That's what's behind globalization. So, you can imagine they have cyclical effects. They can also affect the long-run or medium-run trajectory of growth and inflation and interest rates. And then finally, the biggest one by four is technology. And what I'm proud of is that we look at through the lens of three factors of technology. It's ability to substitute for human work, so automation. The ability to augment to make us better. You can think of co-pilot. Much like the personal computer for some jobs. That's augmentation. And then third, which is really the magic. And we don't see that from every technology. That is, the technology becomes a platform to enable new products, new industries. Electricity and personal computer work great examples of that, internal combustion engine. And so again, we brought all those frameworks into the modern era and then looking at AI and its ability to affect the world economy on all those three facets. And that is novel. That's generally not done even from central banks and practitioners and something that's really integrated in our system. Is technology the proverbial one mega trend to rule them all? Or is it just right now? No, it really is. I mean, what I was fascinated, for example, is, so what we are doing is, you know, all these factors are moving all the time along with GDP and inflation, stock market, interest rates. They're all co-existing. I think of a living breathing system. But because of that, we're able to attribute or assign what's pushing up and down growth. At any point in time, we look at, we look at back over well over 100 years because great technology's only come around every so often. And what I was shocked to find is, for example, that growth has been low generally speaking or has been slowing over the past two decades. And nearly every economy, we look at not just because we have fewer people entering the labor force, the agent of society. It's more important because we've had a lack of automation in a service-based economy. So that's important because given what the work we did on AI, we immediately thought, you know, before we brought data to bear, that AI could significantly lift growth over and above expectations because the lack of automation, if AI could help automate, it would actually push up growth without needing new people or the same amount of people that we saw saying the 50s and 1960s. So again, we have to, but the data is keeping us honest rather than we did not want to be in the narrative business or, hey, it's Joe's personal opinion that AI could be transformational. So it's AI certainly is technologies by far the biggest one. But it has to evolve in a certain way because there's significant liabilities in nearly every economy. And we look at on the other side, you've got agent of society, you look at the demographic patterns in China, you've got decaloblization or the threat of decaloblization and you've got the rise of debt levels. And nearly every economy around the world, those would all seem negative for growth and potentially push up interest rates and inflation. And so that's why the system is effectively doing a course race and depend on the signals of AI, could that offset? And it would do it in a certain way that would be positive for growth and labor markets or to be disrupted. That is what we're quantifying in our framework. A fascinating, and when I say fascinating, I do mean, I mean, utterly fascinating point that you bring up is that changes in mega trends explain roughly half of the S&P 500s, orderly movements. Yes. This is a wild long term means short term. This is not the hairy, dense demographics. Yeah, this is about 25 years ago. Well, and I was shocked to find I did not know this. So again, what's standard in macro and I'd say asset pricing is the short term fluctuations in GDP, for example, what what what some central banks would argue is all called demand. So in other words, if GDP is going up and must be consumers or spending more, hence we got to raise rates. What we find is that that's half that's true half the time. But the other half of the time it is it is the emergence of new ideas, its investments raised accelerating because the trend is likely to change in productivity in innovation and can drive earnings power. And so that's what you're saying. So half the time it's not necessarily and that's had that has different implications for if if if if if growth and earnings.
earnings are rising because what effectively is the supply of ideas is increasing. That means that inflation ultimately will come down. It means interest rates may not rise with that levels and you can support higher evaluation. So again, it's that horse race of the two and we have them competing in real time all the time. And that was eye-opening in the May. I thought all the near term volatility in stocks in GDP was the so-called business cycle is just purely demand. But if you think a commodity price is, I think any commodity trader would say, yeah, but it's also the supply of oil that affects the price of oil, not just how much we're driving on the road. And so it's in one sense it's natural yet it's not generally under dawn in my practice. And again, we weren't looking for this finding, but it is honed how we approach forecasting. And that's why we published a lot of this work is to hopefully other researchers could build upon it, make it even better, but it has certainly changed not only our view but our approach to forecasting. And I think that going into any conversation, especially the end of the year when we have these about your head forecasts or capital market assumptions, this is a really valuable input and you stumbled across it. One again, we're looking at every horizon, right? I mean, you know, when we think about capital market assumptions, at least historically in our publications, we've tended to focus on 10 years. No, why 10? We're forecasting stock and bond returns, interest rates, currencies at every month, you know, infinitely, in one sense, the computer can keep going. We focus on 10 years in part because evaluations can have some predictability. But our outlooks for capital markets, they do vary by the horizon. And you know, AI is going to play into that. You know, it suggests that AI could very well, you know, increase earnings, but it could deprive, evaluations could still mean there could be a modest headwind of the next five to 10 years. However, because our economic growth projections are so high relative to consensus over the next year, it means that there's believe it or not, there's upside risk to the equity market. I do not intend to be dissonant. It's a matter of the horizon over which we're planning. I think as an asset allocator, I think you have to take about the short term in the long run, there's a stronger signal for stocks in the long run, but they're not a market timing tool. And that's why we say everything in moderation with respect to this. I view our framework really as a scenario analysis and where are the risks that we're trying to mitigate for clients rather than trying to, you know, look around every corner because no one even with our sophisticated models, and we will certainly not be able to do that. Joe, where do you think we are sort of in the innings here? I mean, in some ways, you know, if it's a mega trend then you would expect there to be sort of some like long runway, but do you have any sense around like what ending we're in? I mean, in some ways, you know, people look at the market and say we're in a bubble when they see some of these, you know, trillion dollar companies or prices, but on the other hand, you know, if it's a mega trend, then that means there's probably a long runway here. What are your opinions on that? Yeah. And again, it's a great question. It's a tough question to understand, but I'll give you what all of our data suggests. And that is we have investment rates going back 130 years across all the great technologies in the world. And that's one of the reasons it took, you know, we really spent some time on this. And we have the deepest data set to my knowledge on the evolution of technology in macro at a high frequency. If you look at those projections and where we currently are in investment rates, because investment rates is a good example. You can compare that to railroad to electricity, a lot of transformative technologies. It suggests we're certainly not done. If I had to use a year, I would put economically, we're in the 1996, 1997, meaning the full buildout. If you use 1999, ergo is the peak. The market seemed to be ahead of that, but it suggests to me that the momentum in the market could really run. I mean, we're having economic growth projections that are 50% above the consensus. We have 3% economic growth for 2027 with zero contributions from demographics and zero contributions from globalization. That shows you how much lift we're expecting from automation and augmentation through AI. But we haven't seen it yet. It's just what it's anticipatory. So I'd say we're still in the buildout phase. At some point, every great transformative technologies has led to two things. One is an eventual rotation in the investment opportunities because we go from buying the technology to implementing it. Then secondly, you have a rash of new entrance. Then you have a peer to consolidation. There has never been a great technology that has not had a significant drawdown in stock prices, which is code word for saying what some would say. There's a bubble forms. I always hesitate to use the word bubble. For this precise reason, it's because you could lead to significant market over valuation. The market can solidate some point in the next two or three years. However, if I said the word bubble, I think some listeners would associate that potentially with tulips. In other words, there's no intrinsic value other than looking at a picture of a flower. We're talking about most of these technologies ultimately rewire the economy. In that sense, it wasn't a bubble. Yet, you still have a market consolidation for a time in the stock market. That's where the economic transformation and the equity market performance divorce during great technology periods for a time. We're going to see that very likely happen again. That's what our analytics strongly suggest. That's our theme. In the near term, we could have significant momentum, particularly in the mega-cap US growth space. However, if I'm managing risks in client portfolios as well as trying to harness AI's payoff, it's thirst to push you outside of the very area that's getting the most attention now because you're trying to get ahead of what that second phase of AI would be. Again, it's tough, but that's what I talk a little bit in the book. It starts to push you outside of the mega-cap growth area. Not because we're skeptical of AI. It's actually quite the contrary, but there is a timing element to this. Again, bottom line is if you had to pin me to the wall and say a year, it's not 1999 because of the economic buildout, it's still significant. We're still in the learning by doing phase. It's moving quickly, but our projections are, AI is going to affect 80% of the occupations at twice the rate of the personal computer in four years. It is fast. We've done this at every occupation. We have 800 occupations. We've been looking at this for a decade and we're monitoring it in real time. We're not seeing the disruptive, both saving time and some job loss, but that's going to come. It'll benefit more jobs than it'll eradicate, which is why we don't have a mass dystopia. Nevertheless, we will see transformation and disruption that's greater than personal computer. That's how we get high growth. We still have, probably, two years at least of that. At some point, however, the market will continue. If we're right, my worry is that it continues to run on an explosive basis and that's so's the seeds for eventually some market consolidation. I can't tell you no one can say the year, but I don't use the phrase bubble yet because we're still in this build out phase, which probably has another year or two to go if our projections are right. What would be those second areas of the market that may be some of the biggest beneficiaries of the AI in phase two? Where would you be paying attention to? What would you be looking at? This is what I found fascinating with some of our research. Things I didn't know. We looked back at all the technology, great technology cycles. What I found fascinating is that at some point, during the great technologies as they truly transform, what's called a general purpose technology, at some point, the benefits to stock investors accrue outside of the technology space itself for two reasons. The biggest beneficiaries are the users or adopters of technology that have unmet needs, areas where there's unmet needs, high cost to serve, or new platforms emerge that unleash new revenue opportunities, effectively new fields or industries. For electricity, the example I talk about in the book is the entertainment industry. Without electricity, we don't have movie theaters, we don't have household products like vacuum cleaners. Electricity didn't create any of that, but we will not have had those products. So it pushed you outside of electricity and utilities. The car did the same thing. It unleashed opportunities in retailing, not just in auto manufacturing. What we are looking for, again, areas where there's potentially labor shortages, difficulty, difficulties in scale.
unmet needs, which means people would buy more of the product or service if the costs came down. And so areas that immediately rise to the fold are in the service sector of the global economy. If you use the United States in leading in, airs include healthcare, they include financial services, including advice, you know, like RIA services, they would include education, and in other business services, these are areas that are going to see some automation effects. However, there's also going to be the potential for a wealth effect as consumers wish to buy more businesses, wish to buy more of those services, but at a lower price. And so that there are the areas, and by the way, those sectors, those that are publicly traded, are generally not in the growth or so-called tech space. The internet did the same thing. I mean, some of the biggest beneficiaries were now consumer products, you know, areas that sell things over the internet, rather than internet service providing. And so that's what our analytics suggest. I can't prove to you it's going to be healthcare, but if I had to overweight one sector of what AI could potentially boost the most, it would be things such as financial services, not only just to reduce the cost, but the ability to unleash new products and services, and then healthcare. Those would be the two leading candidates in my book, which is why it tends to push you ultimately into value-based orientations, not because, and the primary reason is not because AI is overvalued, it's because the benefits starts to transmit to the whole economy, which is why it's a general purpose technology. One of the things that you focus on in the book is sort of the fiscal challenges that we face as a country. And that, like you said earlier, all over the world, you know, high levels of debt at the country level. And I'm kind of wondering like in some way, you know, if AI actually delivers on growth, it kind of makes the kicking the can down the road just continuing to happen. You know, it's funny. Like I remember, I don't know if you guys remember like the Simpson Bulls, like proposal where they were trying to do. Yeah, toilet. Yeah, toilet in 2012. Yeah, and you know, we don't hear about that really any of that stuff anymore. So in some ways, you know, AI is going to be possibly great in a lot of ways and good for our economy and good for growth. But maybe in some ways, it's not going to allow us to get at some of the root cause of the these fiscal problems. I don't know what you think of that. Well, and that's where we get these non-consensious outcomes. Our most likely outcome is that AI is more transformative than the personal computer. I mean, that's our baseline and it's coming from the analytics of our projections. It's not my opinion, as we mentioned before. So we already have a very differentiated, I mean, our neck is out there, but I feel good because we're using data to bear. We have growth projections that are the highest in any consensus survey. But that allows us to your point to kick the can on fiscal deficits. What's happens in our scenarios, its structural deficits are so called the sustainable fiscal deficit, which is high in peacetime. We're close to 6% deficits the GDP. And this is with an economy expanding. You kind of hover in a 4 or 5% range. If growth goes from 2% to 3%, you get higher tax revenues higher and it allows you to to forstall. We saw this in the 90s. In fact, in the late 90s, we actually turned into a surplus. Our projections generally don't show that because of the agent of society, which we also have in our projections wanting to push the deficit up. And so you can see the importance of AI in trying to forstall these fiscal pressures, which is why, you know, I'm in one sense, I'm cheering for AI to be as transformative as it is along all three dimensions. What, you know, if we're wrong in our projections, it's that AI only automates. We don't get augmentations. So we don't become better as workers. It just saves us time so much so that we have some job loss in some professions. We have seen technologies like that. The assembly line was one. The farm tractor was the others, you know, forgive the 100 year old examples, but it was true. If AI only automates, again, that is not our likely that's that's the second most likely, but it's not nearly as likely as our baseline. It's half as likely. The fiscal deficit issues come in the come in the come into the fore again in about two or three years because you have growth. The AI build out still occurs, but the 3% GDP fades back after kind of the initial build out. We don't get the new industries that our projections, you know, generally anticipate and we get less benefit for us as workers. And so what happens is trend growth doesn't ultimately change. We get this little I'll call it a sugar high for two or three years and we fade back down. Now you have a structural deficit. That's going to 6% to 8% to 10% deficit to GDP because the Asian of society and our fiscal commitment, Social Security Medicare and Medicaid. And so what happens is now you start to get pressure on our currency. You start to get pressure in the bond market and you have the Federal Reserve trying to fight those inflationary pressures and they're forced to keep industries higher than they would to keep long-term interest rates kind of low, but there's fiscal pressures. And so that's this economic scenario I don't like talking about, but that's really I in the book I call it deficit dominate. If I was writing the book today, I would just call AI only automates because it's the same scenario. And so again, it's that deficits are serious issue. So I wouldn't want to portray our deficit issues are like there's not a problem. It's just that deficits are conditional and other things going on in the world. And so we could we could have five or 10 years with they don't mature all eyes in terms of higher interest rates and so forth. And we have seen it before, but it does rest on AI becoming a general purpose technology like the personal computer and it's got to augment our work. It can't just save us time. I want to take you back onto some of the quants of what you just said because there's a few more stats that really I think are eye opening. 2% growth and 2% of inflation going forward. You said a 10% probability of being correct. And then I'm lumping in too much. We're going to unpack these together on the deficit point. A 20% probability that the 10 year treasury yield could reach over 9% the next five to 10 years if AI disappoints. These are not your standard consensus takes here. No, and again, we weren't. Oh, and again, we were I was not and we were not a Vanguard looking for this economic diagnosis. I was very comfortable in my 2% growth, 2% inflation planning world. That always it always seems made sense to me. Me get a little bit of technology left. Yeah, but we got all these negatives that we mentioned before on the other side. Like like I wasn't like taking it not seriously. Like I always thought 2% growth, 2% inflation. I feel out these consensus surveys. That was our forecast until this work. What it's been eye opening through the data is that it's just very difficult to generate that sort of steady states that is quote forecast. Because of the pusher pull, either the trend for growth is going mature higher because of the innovation of AI that overcomes the demographics and the debt levels we have. But if it only if AI only manifests along certain technology, if it only automates, which means it has not become a general purpose technology, we use it all. That would be disappointing. And then that sets in the motion this eventually not today, not tomorrow. And other things would have to occur. But we saw a little bit of this with so again, I don't know. That's more scenario planning and stress testing our portfolios. Should that scenario occur. It's not nearly as likely as our baseline, which is AI transforms. But this is client portfolios where they have fixed income exposure, equity exposure. We want to look at that. Another ironic thing is that in our simulations, what's the optimal investment strategy? If we go down this disappointing AI only, you know, shave jobs and doesn't make us more productive, Iron, you mentioned higher interest rates. However, it would push you into fixed income actually. If you're if you're trying to optimize and avoid that world, short duration fixed income. Why? Because you have given that interest rate reset at some point. For a temporary period, you have equity market that has significant drawdown risk. You're talking about a world where AI has not become a general purpose technology that has led to massive earnings disappointment in the US equity market, particularly in the large cap growth universe. And so you have a higher discount rate or the pressure for that. You have higher short term interest rates and you don't have the earnings growth and you have the earnings multiples coming down in that world. And so that it's trying to it would push you into fixed income only because it's trying to mitigate some of the drawdown in US stocks. So it may seem counterintuitive. Hey, in a fiscal pressure scenario, you actually want to go into short duration fixed income. It's a gap. But most clients have exposure risk to equity market drawdown. And so it's going defensive in that way. But the broader risk is in equity market. Again, this is a world that AI flashes brilliance, but ultimately only automates. Because we have higher unemployment without the growth left for new stuff.
Again, the thundersineer I like talking about, but it is, you know, that's that 20, 25% probability. It pales in comparison to our baseline, but it's the second most likely outcome. And we have the data to look in real time. It's to say, which where is the, where are the winds blowing? Right now, it's still tracking as AI will transform along three dimensions, but two of them we haven't seen yet, the augmentation and the new industries. We haven't seen them yet emerge. What type of things would you be looking at to get a sense that that augmentation, implementation is actually starting to bear fruit? Like where would, what would you be paying attention to in the data? Some leading indicators that I would be looking at that everyone could look at would be three come the mine. One would be, you know, you're going to see disruption in the labor market. However, if you're going to see job loss, it would generally be older workers, not the new entrance college graduate, a lot talk about why that would be. They still have new tools being adopted. And so you would have, but if augmentation is still winning, it means that new entrance to the workforce, I mean, I mean, to be honest, they're not as expensive and there's an ROI to them embracing these AI tools as a compliment, not just as a substitute. You would see new business creation not just in the tech field, not just in Silicon Valley. You would start to see massive job creation or just startup creation outside of AI startup, so which have been massive, 4,000 or so in the past three or four years. You would start to see it in the areas I mentioned before. It could be in healthcare, it could be in finance because that's where the diffusion. Now we're starting to see that the sort of green shoots of these new fields emerging, new platforms, new applications that are revenue producing, not just cost saving. And that's the key. And then finally, there would be headlines in the new somewhere that a new product, a new solution has been discovered by human beings using AI. So not just solving math problems, which is very nice, but say a new medical treatment, for example, comes up in part because AI tools were powered with, say, medical professionals. And so again, I'm just trying to paint a brush of those would be consistent of us continuing down this AI transform path. You got to see the business star creation. And as well as the job application outside of the tech field, it's up. The tech field will disrupt its own field the most. So the pressures we've seen on software, company stocks is not surprising at all. We've seen in every technology cycle. And we could give examples. And we're not just seen in the disruption of even software and IT jobs. Again, that is not surprised us given the work we did in the past. But what we got to see is these augmentation and new platform effects outside of the AI space. I'm not criticizing the excitement of AI space, but tell me how it's being used for new revenue purposes. It's both the alpha opportunity if you're actively and actively managed and climbed, as well as indicators to watch if we're going down that path. Zoom me out because a lot of what we're talking about feels like a US centric story. But this is a truly global trend. Talk about globalization or de-globalization. How this fits in the context. One, again, there's obviously pressures on de-globalization. It's the clear, we've called it secular for some time tensions in some ways between the United States and China from an economic perspective and other dimensions just economic. However, when we look at the countries that could benefit the most from AI, I think again, if you have to look, I would urge us to look in two phases. One is the production of AI as a technology. That's chips, that's picks and shovels, that's software. Obviously, that's beneficial to China and some dimensions as is United States. Besides those two, and I talk about the book, it's a race for a distant third. No third country is even close. Maybe when you look at Taiwan through that same lens, but other countries know. But other countries could benefit in a second half of the cycle. If you look out beyond two years, and that tends to again be on the consumption. There, it's going to be economies that, as we go in the face too, it's funny. It starts to push you a little bit outside of the United States, not because AI has been transformational. It's been juxtaposed. But it's countries that have very poor demographic profiles. Maybe they do have some debt headwinds. They have the need for greater automation because of poor demographics and a high service based economy. So, as I talk about in the book, if that sounds familiar, that's some countries in Europe. That's areas such as Japan. And again, emerging markets, it's mixed. It could be beneficial for, again, for China, but it may not do as much for Brazil. So, it's country by country. But at least I try to provide a little bit of a framework of what those criteria are. And so, this is a global phenomenon. General purpose technologies, if we're right in our baseline, they are global by nature. And the same way electricity was or their computer was. And so, AI won't be anything different. We were always taught in economics. I'm not an economist, but I did take economics in college. That free trade was good. Your country's want to focus on where their comparative advantage is. Terriffs are bad. Deadweight loss. But it seems like it's weird. It seems like the market, maybe because of this delay, it's kind of shrugged off all that trade-related economic theory, I guess. It's been a low perplexing. I mean, I can tell you what our projections, we saw the, I mean, the tariffs increases we saw last year were multiple state or deviations, even in our long run data set. We never had a recession as a baseline in part because trade, although very important is a small share, at least of the US economy, five or perhaps 10 percent by certain measures, higher from an S&P earnings footprint, but nevertheless. But I would say the same thing with oil prices as well, given recent events. Both tariffs and oil prices have not had a material dent in the economy. But again, I think that depends, they could have, if we didn't have AI investment, continue, etc., which is why I think the power of having all these factors in the same ecosystem, you know, we're not going to be able to anticipate all these, you know, geopolitical shocks, but when they occur, you can at least say, this is all around a magnitude question. The direction of tariffs can be negative for growth, negative for inflation, but oil is equal. And we know that the world we never live in that world. And so how strong or weak are the other forces? And so it hasn't been a surprise to us that growth has held up generally because of our investment expectations on the AI front, which are actually-- Yes, it's a trillion hours and growing. But if those shocks had occurred for tariffs and oil prices, if those shocks had occurred, I'd say five years ago, we could have very well been talking about recession or being very nervous about it. It's not that those forces don't matter. It's just that what's helping potentially to offset it. But again, some of those effects were delayed. And some of the fact is that those two factors, oil prices and tariffs, they matter for the US economy, but it is so diversified that it matters less to the United States than say the UK or parts of Europe, which we're seeing significant effects of those two shocks. And so it does vary where we are in the cycle. What else is offsetting potentially some of these headwinds? But I think it's a very important point because as investors, when we're looking at the headlines or watch it, it's that point in time that a lot of times investors are paying attention to so the tariffs or the spike in oil, but to your point, it's like in the context of the entire economy and the market, there's so many different moving pieces. And the magnitude of different things, investors can kind of lose sight, I think, of some of those things that can be different than what people think are having to play out. Yeah, and if someone's trying to do, again, I've been in the business 20 years, and again, we have some deep empirical frameworks, but I'd say, let's say we even have those frameworks. What I, and look at, I'm a personal investor too. I'm talking with my advisor, help me get closer to retirement. I would argue we all have, even mentally, a multi-factor scorecard, really simple. So you can have your oil price that you're concerned about. You can have geopolitical tensions that you care about or worry about. You can have our deficit issues that you worry about. And you have your other factors too. You have the AI threat as well as opportunity. And you go down the line. Why I think it's important to put all those factors good and bad on one ledger is that, and our framework empirically is doing this, like, naturally, is that what that, what I've always felt when I do that is that it doesn't lead to drastic changes in one's portfolio. If I had just rather, versus if I had just been looking at one of those factors in isolation, right? Because if you see those headlines, it could come out tomorrow. Oil price is hitting 120, not $100, 110. You say, oh, wow, this is going to be really going to hit growth. Equity market. I'm going to get defensive. Okay, but that factor versus those other ledgers.
Now if you put that up against the AI investment in the six months, which is unlikely to slow down, now you may get to a different conclusion. So I think at least having her euristic, though that will tend to keep you closer to the policy portfolio. It doesn't mean, at all, by the way, that one doesn't change one's investment exposure, but you may view it from a risk management perspective or more at the margin or less near-term-oriented. You may still be worried about fiscal deficits, for example, in that rubric regardless of what's in the headlines today, but there would be ways that you could kind of mitigate that or I would say for listeners with your advisor, they would be able to walk them through that, along with all the other goals, the day would no better than anyone with you. I think that's how I would think about how macro meets the portfolio is doing that in context, also versus the market euphoria or pessimism at any point in time. Again, generally when I do that, it keeps me closer to my benchmark. It does not mean I'm not going to make some changes for opportunities or for risk management, but they're not going to be as drastic if I had just looked at one factor in isolation. That would lead me to really whipsaw portfolio more often than not. That being said, what's it mean for the standard, quote unquote, 60/40 portfolio? And what's it mean for what an updated policy portfolio could look like reflecting all that you just shared? Well, I think that's a, you know, that's still a viable portfolio. I mean, you can pick your sort of real return target as listeners. Like, for example, for me personally, given my goals for the request for myself or my retirement income, my wife and I, and in our goals in life, I'm closer to an 80/20 period, regardless of my views on the market. That's just given our personal situation and my risk tolerance. But let's say it's 60/40, but I just picked that in the book as just a fine, representative benchmark. You know, there's great, they'll be a fine portfolio. There's some risk to the 60/40 effect to any, it's really because they're worse than the equity market. But that's only if AI only automates, so it disappoints in some of its hope for a time. It's manageable, but there would be a period of disappointment. That's really all in the 60 area, not so much on the 40, which is why, you know, I talked about it in the book. If you're going to worry about all states of the world, you would, you would, you would, you want to fade a little bit the euphoria that is in the mag, and I'm not picking on these companies on the magnificent, you know, the large cap growth companies, not because they're not adding value. It's quite the contrary. It's because as it spreads, opportunities will unfold. So again, you know, the baseline is that it'll be fine. We may have some turbulence here, but you know, on the near term, it's upside risk on the 60 segment. But at some point there's going to be a market consolidation. So I'd say just thinking about balance and risk mitigation, and I think the biggest question for, I think value having with clients is two things. One is, tell me, talk to me about the two or three states of the world that have a significant odds or non, non-diminimous odds of happening. And how would my portfolio weather them? And is there mod as sort of tilt in the portfolio that I could add for risk or mitigation or alpha, you know, generation, including active management? But I think that's like almost regardless of what AI does as a consideration set. But 60, 40, I don't see changing as the reference portfolio. The fact is most active managers don't outperform it, but there are opportunities for investors regardless of how AI plays out. - So Joe, we have two standard closing questions we like to ask Oliver Desp of before. I get to that, I do just want to point out to the listeners in the audience. That in addition to the book, Vanguard has an excellent, what I would call like a Megatrends research hub, where there's data, there's some actually other videos of Joe, and there's some interesting research and PDF. So that's just free on Vanguard sites. So we certainly encourage people go there to buy the book too. But of course, if you want to start with the research hub, that's a great place to get some really cool information. So the first closing question we like to ask Oliver Guest is what is one thing you believe about investing that most of your peers would disagree with? - Disagree with. - I do like that question. I would say that there's a strong linkage all the time between what's going on in the economy and what's going in the stock market. The fact is that those two can move in different waves in part because the stock market can be anticipatory of what has not yet transpired in the economy. I think we're seeing some of that today and quite an enemy can go in the universe at some point in time. So that would be something I would argue. There's two or seem to occur one for one, GDP with stock markets, but I think most readers ultimately would appreciate that those two don't always move and lock stuff. But there are one thing you could teach the average investor. Put another billboard, fly it on a little plane on the sky over the Jersey Shore. - I would, I'd tell you, it comes from Ben Franklin, but Jack Bogle would beg advocate for this too and you've talked about it yourselves. That's a power compounding. I mean, even I could be the most savvy investor and move around the market in time. The fact is how much money I put into my own portfolio and saving and letting it rest and let the capital markets do their job is going to dwarf any so-called alpha or outsavying the average investor. And so that's something I continue to remind myself, put as much money in as you can and let it do the hard work for us. A compound interest, it is the biggest asset we have as long-term investors. - One more thing about the book before we let you go. The proceeds going to charity. What was the thought there? What was the strategy? What was the idea? - Well, again, no one even asked me, you only get one check at Vanguard. I'm a Vanguard employee. So that was the first order. Secondly, it was just as Vanguard, we believe in our community as well as our clients. And so all the proceeds go for Vanguard, strong start for kids. So this is young children that may not have the financial and their parents, the financial resources for early childhood education. And so if that could help some young children, I couldn't think of a better place for the proceeds to go. - I think that's a very important point to end design. Joe, thank you so much for your time today. - Thank you for having me. - Hey, if people want to bug you on the internet, find out more research on this. Can you tell them one more time where they can get this? - Well, yeah, I think what you said on the Vanguard hub, and in every year we'll have our annual outlook, but you will see AI and these other factors prominently in there, we're looking at not just for the next year, but of the next several, as we all are trying to navigate this universe. - Advisors, allocators, do it yourselfers. You want to check out these resources. They are very, very cool. This is one of the reasons why Vanguard's such an interesting company is because of how much of this stuff they put out there. Joe, thank you so much for the time. You are watching "XS Returns, Like", comment, subscribe, all the things below, and we are out. - Thank you for tuning into this episode. If you found this discussion interesting and valuable, please subscribe on your favorite audio platform or on YouTube. You can also follow all the podcasts in the "XS Returns Network at accessforturnspod.com". If you have any feedback or questions, you can contact us at
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