Navigating the Future: How AI, energy and health care will impact the corporate landscape

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Rama Variankaval: Hello, everyone. Welcome to ‘What's the Deal?,’ the investment banking series under J.P. Morgan's Making Sense. I'm your host, Rama Variankaval. I run the Global Corporate Advisory Practice at J.P. Morgan. And I'm joined by my colleague Evan Junek, who's responsible for the Corporate Finance Practice at J.P. Morgan. Welcome, Evan.

Evan Junek: Great to be here.

Rama Variankaval: I think you and I last did a podcast maybe beginning of the year, so it's been a few months.

Evan Junek: It has been. And I think we've got actually a great complementary discussion today relative to where we were back in January.

Rama Variankaval: Fantastic. This has been our summer project, what we are going to talk about today. We spent the last two, three months thinking about something we don't usually spend a lot of time on, looking at the very long term. So, why don't you tell us a bit more?

Evan Junek: So, as you mentioned, at the beginning of every year for more than a decade now, we've released a piece we now call the ‘Corporate Compass,’ which is focused on key themes and trends we see in the market, at that moment in time, that are really focused on decision-making over the subsequent, call it, year. I mean, it's really for the year ahead. And what we felt was we were kind of missing something in that work that ultimately, we are here to be advisors for the long term, strategic advice-givers. You know, those decisions really are about the impact of things well beyond just the next 12 months. And so, we've just released this piece we're calling ‘Navigating the Future,’ which is, as you note, really focused on three themes and their impact over potentially the next 10 years. And I'd say we frame this not trying to be everything to all people, but we've sort of taken sort of three fundamental views on three core topics, those three core topics being AI, energy, and healthcare. And said, "How would that set of circumstances impact businesses overall, the economy?" And really open up a conversation about where to from here?

Rama Variankaval: So, for each of these three big topics, AI, energy, and healthcare, as you said, we picked a central scenario.

Evan Junek: Yes.

Rama Variankaval: Almost certainly we'll be wrong, but this is where we feel that there is a probability of the scenario playing out. And to frame our client's ability to make decisions, we had to pick a scenario, right? So, for AI, the scenario we picked this AI is in fact transformative. It impacts productivity and the global economy in very material ways within this 10-year window.

Evan Junek: Mm-hmm.

Rama Variankaval: Whether that means AGI or not, we can debate, but transformative regardless.

Evan Junek: Right.

Rama Variankaval: That's our scenario. Clearly, there are skeptics who believe that this is, uh, hyped up too much, but again, our scenario is this is more reality than hype. Closely related, related to AI is energy, where if you look at historical data or very recent data even, what you see is energy prices are actually being quite volatile, and maybe even trending up. But our central scenario is that over the long term, energy prices actually go down. And we'll talk about why that is a central scenario. Healthcare, which is again, perhaps slightly orthogonal to the other two, but clearly a lot happening there as well. The central scenario there is that the ... just development in the last three to five years, the advent of several miracle drugs, means that the longevity of the global population increases, but almost more importantly, the quality of productive life increases and the length of productive life increases. And that, again, will have obviously quite material impacts across every economy around the globe. So those are the three central scenarios that we talk about and, again, the implications of, uh, each of them. Why don't we start with AI, if you want to kind of dive into it? What is the thesis? What are we trying to achieve here?

Evan Junek: So, let me start by talking a little bit about AI and, and the impact thereof. And obviously, we, we talked a little bit about this velocity of adoption, which is I think a common theme amongst a lot of the things we'll talk about today. The stat I'd give you kind of just right off the bat is that it took ChatGPT a matter of weeks to attract a hundred million users, even the largest social media platforms today took years to achieve the same level of user penetration. So, just that gives you some sense about the relative velocity or speed of the development of some of these new technologies.

Rama Variankaval: It is stunning. So, the impact, and again, this is a common theme across all of these topics, the impacts of these three things, AI, energy, and, uh, healthcare, is really broad. That’s what we expect.

Evan Junek: Yes. Yes.

Rama Variankaval: That this is not just impacting certain subsectors, but we think this impacts really the global economy. And that's what makes us really, uniquely interesting.

Evan Junek: Absolutely. And so, let's, let's talk about that point about impact the broader economy 'cause this is an area we actually spent some time on in the, in the process of developing these materials. And so we leaned on some precedent research to try and compare and contrast the impact of prior technological transformations, and in particular, productivity implications of those technological implications over time and compare and contrast them to the potential impacts of AI. So, let me just give you some historical details for context. If we go all the way back to the 1700s, we talk about the instruction for the steam engine, of course, hugely important with respect to an improvement in human productivity. By most measures, it took on the order of 60 years for the adoption of the steam engine to sort of maximize its ultimate productivity impact. Now, of course over time, those impacts accelerate. So, if you look at the invention of electricity or the adoption of electricity in the late 1800s, about 30 years till we saw wide adoption and impact on productivity. And then if you talk about sort of the PC and internet era starting in the early 1980s, you're talking about 15 years between adoption and wide impact on productivity. So, let's just take some of those examples and maybe we'll even just pick electricity as an example. Let's say AI looks a lot like electricity in terms of the adoption curve and ultimate impact productivity. Well, that turns into about half a percent of GDP growth every year for the next 25 years. So, we're talking about real-

Rama Variankaval: At a global scale.

Evan Junek: At a global scale, at a global scale. And that's really on a per capita basis, is how we've measured it. But you can imagine like a real impact to, sort of,  the everyday person's productivity across the board in a material way, and I think you could make the argument, especially when you talk about the velocity of change that we just referred to, that that may be a massive underestimate of the kind of impact we could see from something like mass AI adoption.

Rama Variankaval: Right. So again perhaps we should have, you know, said this before, but the reality is there's uncertainty about a lot of this, right? You know, the, the actual pace of AI adoption, the actual impacts, eventually, it's impossible to predict, much like it's impossible to predict the future of the state of energy or the future of healthcare, right? But what we have attempted to do here is to essentially pick a scenario that we think has a high probability of playing out. And then we are providing a framework for our clients to think about their businesses, their sectors, assuming a scenario like this plays out, right?

Evan Junek: That's right.

Rama Variankaval: And for AI, the scenario we are laying out is, in fact, it is transformative. There are clearly, you know, skeptics out there and they might have a valid case why this may not really transform the globe as much as some of the optimist thing, but we are taking a little more of the optimistic view, if you will. AI in fact is transformative. The productivity impacts are quite tremendous. And again, under that scenario, really, if you're a CEO anywhere or you're a board member anywhere, any company, any sector, you have to pay very close attention to it.

Evan Junek: That's right. But we did try and go one level deeper. We did recognize that not all impacts are likely to be equal. And as an additional step in this process, we said, "Okay. If we assume that AI is going to be widely adopted, that it is going to be such a game changer," which is again, I think our underlying premise, who's gonna be impacted more, who's gonna be impacted less? We thought of this as who's gonna be most levered to AI opportunity across the market? And we did that by creating sort of a multifactor model driven by considerations like the opportunity to create efficiencies, the potential to increase innovation, the ability to adapt to changes, all in various levels of measurable ways. And we really came up with a list at, at least a sectoral level about those who are likely to have the most leveraged AI and potentially the least leveraged AI. And so, sectors like pharmaceuticals, software and services, financial services are sectors that kind of bubbled to the top in that leverage analysis, and sectors like automobiles, food and beverage, and consumer staples are names who sort of ended up on the bottom of that list. And I highlight those because we're gonna talk a little bit about the impact to things like energy consumption or energy prices a little bit later in the discussion. And I, I, I'd sort of have you place those sectors away, away in the back of your mind for a moment because we may be hearing about some of those sectors again when we talk about sort of the broader implications of other factors we've looked at.

Rama Variankaval: Makes sense. And I think, correct me if I'm wrong, what we have essentially developed here is a model that we can then go further down to a company level and start thinking about what implications AI might have to that particular company.

Evan Junek: That's exactly right.

Rama Variankaval: And that's a discussion we are having with clients, and of course we encourage other clients to reach out as well.

Evan Junek: Exactly right. Exactly right.

Rama Variankaval: See, anything else on AI before we move on to energy?

Evan Junek: Let's move on to energy-AI. I mean, I think you've, you've identified the obvious connectivity between AI and energy. It's probably the most talked about side effect, if you will, of AI adoption is the mass requirement for huge amounts of electricity to run these data centers. Why don't you talk a little bit about how we looked at the future of energy and some of the corresponding assumptions we analyzed in our work?

Rama Variankaval: Yeah, absolutely. So again, the scenario, that we have adopted if you will, for the energy section of this report is despite everything going on in terms of volatility in energy prices and the, you know, sudden spike in demand leading to, you know, increased prices of capacity securement in say the PJM auction, et cetera, our thesis is over the longer term, energy prices actually go down. And we'll talk about why that is the case. And the implications of a long-term downward trend on energy prices obviously is pretty wide as well.

Evan Junek: Mm-hmm.

Rama Variankaval: There are different sectors that benefit versus from AI on a relative basis. And so, that's where we are kind of, you know, zooming in and figuring out how does a longer-term reduction in energy prices impact different sectors.

Evan Junek: Yeah. So why don't you, why don't you start by setting that up for us? You know, we started this conversation by saying AI, huge demand, I think we think of supply and demand, huge, huge demand. We would think costs would go up as a result of that to meet that demand. We're kind of taking a little bit of the opposite view, at least over the long term. How do we reconcile that?

Rama Variankaval: Yeah. I think, and it's again, by no means, consensus view. There is ... And clearly, there is no immediate evidence of that happening. What's ... If you look at the historical data, what you will see is while cost of electricity generation has gone down, the cost of kind of electricity infrastructure, the transmission distribution, aspects have gone up, and retail electricity prices have actually been volatile. There is no downward trend per se. But what we have noticed is along with the CapEx at the hyperscalers of spending on data centers, there is a corresponding increase in the CapEx by utilities. So that's a factor. We, you know, it's well-advertised, perhaps over-advertised that the cost of several forms of, you know, energy like solar, wind, et cetera, is keeps coming down quite substantially. You have quite impressive amount of capital being invested on newer, even newer forms of energy, whether it's, uh, advanced nuclear, whether it's geothermal, et cetera, right? So that's another reason. The public policy around grid infrastructure and transmission, I think that while not at a great place yet, are clearly getting a lot of attention, not just in the U.S. but globally. So, all of these leaders to believe that if you kind of project forward in the kind of the five to 10-year timeframe, there is a real possibility that energy prices to the end customer actually goes down.

Evan Junek: And I think that's an important point to highlight for a second, because I don't think we're suggesting that that's necessarily a linear path from here to there.

Rama Variankaval: Absolutely.

Evan Junek: Right? That we may see a period of volatility in energy prices, maybe even more volatility than we are used to, especially in things like electricity prices, there's certainly been some recent auctions in some of the regional power markets that have raised some eyebrows in terms of their volatility. And, you know, that's certainly probably something, I think, we'd agree that you'd probably see maybe more likely to see more of than less of in the ... in terms of near to medium term. We're really talking longer term here.

Rama Variankaval: Absolutely. The near-term volatility, clearly, you know, data centers are a, are a reason for it, but the broader electrification of things, whether it's residential, industrial, I think that plays a role into it. Geopolitics, we haven't touched on geopolitics, but geopolitics is clearly a factor into all of this, right? Globally, a common theme is countries. Thinking about energy security as a top national security priority, more so than ever before. You know, it's, it's ... Rather than being just something you put in the back, I think energy security has kind of moved up to be a top priority item for pretty much every national government. And if you're a fossil energy poor country, you are especially doubling down on thinking about, you know, forms of energy that's going to sustain your country's growth. So, geopolitics introduces volatility, there is no doubt about that, on top of everything else. But it's really what we are talking about here is again, the five to 10-year look forward.

Evan Junek: Yeah. Not to take us too far off track, but I know one of the things you mentioned in some of your introductory comments is China-

Rama Variankaval: Yep.

Evan Junek:... in this process. Anything you'd highlight there with respect to energy specifically? I think as I go through our work, you know, their approach to energy generation, nuclear development all really kind of stand out in a pretty meaningful way.

Rama Variankaval: Absolutely. Look, China is unique in some sense, actually closely followed by India in terms of how much money ... how much focus and money is being spent on making sure that they can achieve a semblance of energy security. Both of these countries are largely energy poor. They don't have quite the natural resources of the U.S., for example. So, the focus on things like nuclear or even hydro or solar or wind, immense.

Evan Junek: Mm-hmm.

Rama Variankaval: But as we travel around these countries, you know, the capital formation around these themes is, is something to watch. It's, it's, again, I, I think unprecedented. It's not obvious, but if we ... if the world continues to be globally cooperative-

Evan Junek: Mm-hmm.

Rama Variankaval: ... on technology transfer, then I think the benefits of all this capital formation happening in China and India can spread to the rest of the world. So, we can all benefit from the fact that there is capital formation and innovation happening under these technologies in different parts of the world.

Evan Junek: Let's bring this conversation a little bit back to, more microlevel, if you will. You know, how are companies thinking about their own energy needs and demands, how are they approaching that? And then maybe walk us through some of the work we did about who might be the most impacted by a significant shift in the cost of energy over time.

Rama Variankaval: Yeah. Look, I think it's interesting. The number of sectors and companies we end up now talking about energy keeps increasing. And it used to be that we talked about energy with energy clients, now we talk about energy with really every client.

Evan Junek: Yeah.

Rama Variankaval: And the technology sector being the obvious place, but it's not just limited to technology, right?

Evan Junek: Mm-hmm.

Rama Variankaval: Much like what we have done in the AI space, we have developed a framework to map out relative winners and losers, if you will-

Evan Junek: Mm-hmm.

Rama Variankaval:... if our central scenario of energy prices actually will trend down over long term plays out. And where we are spending time is then taking that and going the company level, right? Again, the, the list is not ... there is no, you know, big surprises. If, if your input cost has a lot of energy, uh, related items, then clearly, energy prices going down is going to be a big positive for you. The transportation sector, the automotive sector, you know, clearly is a big winner. Technology sector given their reliance and need for energy clearly kind of stands out. So again, the idea is to take some of these perhaps intuitive points and then quantify it. And then provide a framework to kind of think about the future.

Evan Junek: And, and just again, connecting back to our earlier discussion, it is notable that some of the names or some of the sectors at the top of this list who would benefit the most from lower-cost energy are not coincidentally also at kind of the bottom of our AI leverage list.

Rama Variankaval: Mm-hmm. Yep.

Evan Junek: And that's ... that is somewhat intuitive in the sense that those who have high-fixed costs in the form of commodities probably have less flexibility to do a lot with AI in terms of leverage to the upside. But probably tells you a little bit of something that, especially if you're in one of those sectors, how you might be thinking about the next three, five, or 10 years, frankly, the kind of transformation you might need to be thinking about within your own business to manage through that.

Rama Variankaval: Absolutely. All right. So, AI done, energy done. Let's move on to healthcare. Again, not a sector you and I spend a whole lot of time on, but it's been a sector that's impossible to ignore in the last at least couple years for even, you know, casual, casual observers, with the, you know, the GLP-1s being really the center of the conversation, by no means the only piece of conversation. Let's get into it. So why do we think healthcare belongs in this list of, you know, sectors and areas that we want to focus on?

Evan Junek: Yeah. Well, I, I think going back to where we started this process, we were thinking a lot about what are the kinds of questions that every client or every company is asking themselves at this moment in time? And the kind of fundamental question that I think emerged from that to some extent is, what does the future of work even look like? And of course, there's an AI component to that question, but I think there's also a fundamental embedded question there of who is gonna be working? And for how long? And that really took us down kind of this healthcare route and the idea of saying, "Look, we see so much development." We saw the, the common theme that we see in AI with this rapid adoption. We've seen such a rapid adoption, rapid development of kind of what I, you know, what I think most people call are miracle drugs, miracles of medicine, even just in the last five years. Of course, it doesn't feels like a lot longer than it now but, you know, of course COVID with the mRNA vaccines, the GLP-1s that you've talked about that continue to have really just an impressive amount of, quote/unquote, side effects that seemed to be only beneficial for most people who take them. CRISPR technology, sort of, the list goes on and on, and I'm really only talking about things that have been done in the last three to five years. So, just really an amazing set of developments. And it really seemed to map very nicely to a lot of the other kind of themes we were talking about. Now, that said, I'm not sure a lot of our clients think about healthcare in quite the same way they might be thinking about AI, although I think we would make the argument that they probably should, right? And that, especially as you think about the translation of healthcare into well-being, and of course the length of people's employment with you, and of course the corresponding liabilities that come with things like pensions and Medicare and social security and entitlements, right, there's again, bringing it back even to the geopolitical theme, these are real meaty topics that all seem to have a place in this conversation.

Rama Variankaval: Absolutely. And again, after debating this long and hard, I think the, the central scenario that we settled on is these miracle drugs, as you call them, are going to transform human life for the better. People are going to live longer, but not just live longer, but live better quality of life towards the back end of our lives. And so that's going to be a massive positive, of course, to say the obvious. The benefits of these miracle drugs is going to be disproportionate in different parts of the world, likely-

Evan Junek: Mm-hmm.

Rama Variankaval: ... as access to drugs is obviously not consistent around the globe. But, you know, while the developed world will see lots of benefits, the developing world where the starting point is lower might actually see even more benefits. And the productivity gains and the GDP gains coming from these cannot be underestimated. And so that's again, the reason why we think this is something everyone should pay attention to.

Evan Junek: Yeah. And, and just to that point, I mean, we went back and found some different bits of research on this and tried to do our best to say, "What is the impact of people living longer?" Like, what's the economic impact to the economy and to companies overall. And again, using some, some different research that we reference in the materials, we found that a two-year increase in life expectancy generates an incremental seven to $21-trillion just in U.S. economic gains. So that, of course, comes with costs, as people live longer. And those costs are equally significant, but we still see the net effect being very positive. And so, when you take out things like incremental social security costs, Medicare, public pensions, housing, et cetera, you're still talking about a net effect anywhere from two to $16 trillion that, you know, has real meaningful effect on an economy that today is a $30 trillion a year economy, right? So  the punchline here is that this is something to watch, especially with the pace of change we're seeing. And as companies adopt, I think, more holistic thinking around their own scenario planning, and we'll talk about that, I think, as we think about sort of key takeaways from this report, it's an important piece of the puzzle that people have to have, you know, top of mind or at least front of mind when they do their work.

Rama Variankaval: Makes sense. Maybe, maybe time to switch to kind of key takeaways. As, again, the, the premise of all of this work been that these topics impact everyone, everywhere in the world, and in many sectors, the impacts of these changes are gonna be transformative. And so if, again, if you are a CEO or a CFO or a board member, how you incorporate these possible scenarios into your long-term planning is going to be very, very critical. And that's kind of the discussion we are having with clients. So give us maybe, you know, couple high-level takeaways of all the details and the analysis is in the deck that's in the link here.

Evan Junek: First and foremost, with the pace of change, there's no better time to step back and reevaluate your mid to long-term planning than today, right? What we're offering here is three views of the world. You could find who other people on the street could have radically different views, but that's kind of the point, which is that ultimately, you need to be revisiting some of these long-term views at a moment in time where things are changing very quickly. The second point is we're not sitting here suggesting that you've gotta change your forecast to assume that all your human employees are gonna be replaced by AI or that people are gonna live 10 more years and you've gotta adapt to that today. That's not really the takeaway. The, the point here is to say you should probably be thinking on a more open-minded way about the kinds of scenarios you're putting in front of your executive team and maybe even your board, right? Is there a scenario where there's market disruption because of AI? Is there a scenario where there is a radical shift in profitability because of a change in electricity costs or energy costs, right? These are the kinds of questions I think are more readily, or, or we can more readily discuss today and I think are very important to bring into that context, just frankly as the question about what happens if we have a very different trade regime that we did six months ago, right? I think there's a lot of reasons today to revisit this idea of scenario planning, in a, not just the short-term, but the long term. And the final piece of this is, you know, how does this inform your action plan, right? Whether that be from a strategic perspective, does this inform who I might think about opportunistically approaching or the businesses that I'm investing in? Or does this actually tell me that I should be breaking up my business? Should I be more focused in what I do because of the exposure to these different potential future scenarios? How do I think about it financially, et cetera, right? So really, this is all about taking it back to, not just revisiting the planning process, but maybe even thinking about it in a new way altogether.

Rama Variankaval: Makes sense. And again, the key point is one you mentioned, to be able to think about the future in multiple time scales.

Evan Junek: Yes.

Rama Variankaval: We can't lose focus on what the Fed is going to do, you know, in, in September or December, but we can't equally lose focus of where AI is going and where the world might be in 10 years.

Evan Junek: Yeah. Absolutely right.

Rama Variankaval: Evan, thank you. Thank you for joining me today.

Evan Junek: Thanks for having me.

Rama Variankaval: And to our listeners, thank you for tuning in. And for anyone who wants to learn more about this report, “Navigating the Future,” there is a link in the description. Thank you.

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This material was prepared by the investment banking group of J.P. Morgan Securities LLC, and not the firm's research department. It is for informational purposes only and is not intended as an offer or solicitation for the purchase, sale, or tender of any financial instrument.

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