Motley Fool Money - The AI Buildout Is Just Getting Started

Episode Date: May 31, 2026

Token consumption grew 17 times last year — not 17%, 17 times. So why are some investors still underexposed to the biggest structural shift in a generation? Motley Fool Contributing Analyst Rachel Warren talks with Jay Jacobs, US Head of Equity ETFs at BlackRock, about the firm's 2026 Thematic Outlook: why the AI infrastructure boom is still in its infancy, how thematic ETFs can give retail investors more precise exposure than traditional sector funds, and what the rise of agentic AI, physical robotics, and tokenization means for your portfolio. Host: Rachel Warren Guest: Jay Jacobs Producers: Bart Shannon, Lauren Budabin Disclosure: Advertisements are sponsored content and provided for informational purposes only. The Motley Fool and its affiliates (collectively, “TMF”) do not endorse, recommend, or verify the accuracy or completeness of the statements made within advertisements. TMF is not involved in the offer, sale, or solicitation of any securities advertised herein and makes no representations regarding the suitability, or risks associated with any investment opportunity presented. Investors should conduct their own due diligence and consult with legal, tax, and financial advisors before making any investment decisions. TMF assumes no responsibility for any losses or damages arising from this advertisement.We’re committed to transparency: All personal opinions in advertisements from Fools are their own. The product advertised in this episode was loaned to TMF and was returned after a test period or the product advertised in this episode was purchased by TMF. Advertiser has paid for the sponsorship of this episode.Learn more about your ad choices. Visit ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠megaphone.fm/adchoices Learn more about your ad choices. Visit megaphone.fm/adchoices

token consumption last year grew 17 times, not 17%, which I think most people would view as a pretty good growth company, 17 times growth of token consumption. Essentially, as much money as the major large language model providers are plowing into capital expenditures, they can't keep up with AI demand. So even just in the last several months, I think the narrative has shifted in the market from that of re-worryed companies are over-investing in CAP-X to what if companies are actually underinvesting in CAPEX. That was BlackRock's U.S. head of equity ETFs, Jay Jacobs, breaking down what the data actually says about AI's growth trajectory.

I'm Motley Fool analyst Rachel Warren. I sat down with Jay to dig into BlackRock's newly released 2026 thematic outlook, covering everything from the AI infrastructure buildout to tokenization to what retail investors should be doing with their portfolios right now. Enjoy. Hello, everyone, and welcome back to Motley Full Comptych. I'm Motleyful analyst Rachel Warren, and today I'm excited to welcome Jay Jacobs, the U.S. head of equity ETFs at BlackRock to the show. Jay oversees the overall product strategy, thought

leadership, and client engagement for the firm's index and active equity ETF business. Prior to his current role, Jay founded and led Global X ETF's research and strategy team and previously served as a business analyst at the New York Stock Exchange, where he helped launch hundreds of ETFs on the NYSC-Arca trading platform. Today, we're going to be diving deep into the massive structural shifts shaping the global economy, with Black Rock's newly released, 2026, Thematic Outlook, which details how the next leg of AI compute is colliding with physical power grid bottlenecks, surging sovereign defense spending, and a massive wave of real-world asset tokenization. Jay, welcome to the show.

Thanks for having me on. So, as you as head of equity ETFs, from your standpoint, I would love to hear your thoughts on how the view of a traditional portfolio has changed now that thematic funds have grown over 11x just in the past decade. Well, I think it's important to recognize portfolio management techniques have always been evolving as the world has evolved, as data and software has evolved to make portfolios be able to be managed in different ways and assess risk and opportunities in different ways. So you go back to some of the factor research in the 1970s, the introduction of the style box

in the early 90s, the GICS sector class. classifications that divvied up the world into different sectors in the late 90s. There's been a constant evolution of portfolio management. And what we're seeing is one of the latest evolutions is really increasingly investors are looking at the world through a thematic lens. They see the rise of artificial intelligence, the changing demographics, the changing energy needs, the future of finance, as well as geopolitical fragmentation, all being major forces that are reshaping how they can think about risks and opportunities.

portfolio. And as they assess those risks, they increasingly see how valuable thematic ETFs can be for fine-tuning their exposure to these themes of their portfolios. Well, one of the things I wanted to talk about your internal model portfolios hit a seven and a half percent allocation, but the average moderate U.S. advisor model sits at just 3.6 percent thematic exposure. And your data actually shows that about 12 percent of analyzed U.S. advisor portfolios currently hold any thematic ETFs at all. So I wonder if you could talk through maybe what's causing this gap? And does this mean that, you know, sometimes we're seeing an under allocation to structural growth? I would say there is an under

allocation or the way that people are getting exposure to these growth opportunities is through not always the most precise tools. I do think a lot of people out there think they're getting exposure to AI by allocating to the technology sector. And in some ways you are. Yes, the technology sector has exposure to names that are building large language models or building some of the important hardware that goes into data centers. But as we've also seen this year, the tech sector also has exposure to software names that are disproportionately hurt by the rise of artificial intelligence of the risk that that presents to SaaS business models. So I think what many people are learning in real time is just there's a difference between

sector investing and thematic investing. And for some of these really disruptive themes, it takes a dedicated them thematic ETF to be able to target them appropriately. we are seeing a gradual shift of more adoption of thematic ETFs amongst advisors. So, you know, yes, the average allocation is 3.6% as of our last reading. But you go back a few years ago, it was less than 3%. So we're seeing a tick upwards. It's just somewhat lagging what we've seen in our own models, which have more rapidly deployed thematic exposures, given this market environment.

I would expect this growth in advisors' use of thematic to continue, though, in the coming years. Well, you know, switching gears completely, we have to spend some time talking about AI, which obviously was something that was a really significant focus in the report, which I found incredibly interesting. So what I want to start with, you know, market skeptics scream that tech companies are overspending on AI. We keep seeing those CAPX figures multiply.

But what was interesting was your report shows that in the U.S., Gen AI infrastructure spending is just about 0.8% of GDP compared to, say, 4.5% for UK railroads in the 1860s, about 2% for U.S. electricity, if you go back to the 1920s. So should one take away from this that the physical AI buildout is actually in its infancy? What are these numbers telling us? That's exactly right. On the scale of other major transformational events within the United States, AI CAPX has still not reached the upper echelons of that type of investment. And part of it is we're early. This AI boom has really only started since the end of 2022. So we're a few years into it, we're seeing some of these capital expenditure numbers really accelerate upwards

at a tremendous rate. So I think we're going to see that percentage of GDP invested in AI continue to rise over the next several years. But the fact that it's still below what we saw as investment in railroads, investments in automobiles from a historical context just shows we're early. This country has been through transformations before. It's taken a tremendous amount of investment, each of these transformations. But the impact of those transformations can span many decades, as we've of course seen with the automobile, as we've of course seen with telephones. So it's a reminder that we're early and it's still going to play out over the next several years.

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Obviously, Gen A.I spending is sitting about half of that right now. It's not a one-to-one comparison either, but I'm curious what structural protections, say, prevent AI infrastructure from suffering dangers of overcapacity crashes we have seen with past buildouts. Frankly, I think a lot of this buildout is just a lot speculative because so much of this compute that is being built out is almost instantaneously being monetized because of AI demand. You know, what we show in the report is that token consumption last year grew 17 times. Not 17 percent, which I think most people would view as a pretty good growth company, 17 times

growth of token consumption. And essentially, as much money as the major large language bottle providers are plowing into capital expenditures, they can't keep up with AI demand. So even just in the last several months, I think the narrative has shifted in the market from that of we worried companies are over-investing in CAP-X to what if companies are actually under-investing in CAP-X? Could we start to see bottlenecks in artificial intelligence? Or some of the most powerful models, frankly, have to be throttled because there's so much demand to use them versus the compute that's actually available across the economy. So, yes, the CAPEX is accelerating. The numbers are quite staggering of what we see being invested each year. However, the demand is

backing it up and the revenue from demand is immediately backing it up. So this is not the same as speculatively building telecom infrastructure. And then, you know, if we build it, they will come kind of scenario, this is meeting real demand in real time. Yeah, I think the other thing as well that I would like to dig into a bit more is this growth coming from agentic workloads, which, you know, is essentially AI that can complete multi-step tasks on its own. The report notes this can increase relative token intensity by, you know, a thousand times. So we're seeing everyone from corporate America, you know, the big tech companies and beyond deploying AI agents. So what parts of the tech stack can capture this exponential surge in data processing? Where,

you know, where are the beneficiaries and what can retail investors take away from that? Well, it looks across the entire artificial intelligence tech stack. I mean, it starts with some of the lowest levels, which is really in the infrastructures. I think about the power that's applying data centers, the data centers themselves, the real estate, the hardware going into those data centers. Think about all the semiconductors, whether it's memory, whether There's GPUs, whether it's CPUs that are powering those data centers. On top of that, there's the data layer. Think about the proprietary data that's training a lot of large language models.

There's the large language models themselves that are being more and more powerful. We're seeing that software improve significantly year over year. And then, of course, you have the applications and products that are using those large language models to utilize agents. whether that's, you know, imagine having a financial analyst that can help you pour through news or earnings reports, sell side reports, et cetera, consolidate all that information, put it into an Excel file or a PowerPoint presentation, you name it. There's a lot of things that an AI agent can now be programmed to do and really take on a significant amount of tasks for people in a wide variety of different industries. And so that's why we're so focused across the entire AI value

chain because as you see more adoption of agents, it's really going to flow across that entire value chain where you see companies profiting off of that. So there was data in the report from McKinsey that projected cumulative global infrastructure investment is set to top about $100 trillion by 2040, and that's driven by a range of factors, including, you know, AI compute, national security, supply chain resilience initiatives. How can a long-term investor evaluate these sectors across this really? truly massive capital rollout we're seeing. Well, interestingly, despite the amount of capital we're seeing allocated to infrastructure,

it remains a relatively small part of people's portfolios. In fact, average infrastructure allocation in the SP500 is about only 3%. So less than some of the MAG7 names alone. And yet we just see tremendous amounts of drivers for more infrastructure spending. We have changing demographics around the world, which is, you know, growing economies, growing populations that need more infrastructure, We have aging infrastructure, particularly in the developed market, where a lot of it was built in the 1960s and needs to be refreshed. We have changing infrastructure demands where it's not only about physical infrastructure.

There's also a needs for digital infrastructure going forward. And so there's really a lot of tremendous tailwinds behind infrastructure, and yet it remains a relatively small part of people's portfolios. So I think we're going to see a significant amount of investment over the next several decades. I think a lot of that is going to increasingly come from the private sector, given that. a lot of governments just simply can't afford to keep building more infrastructure. And that should likely drive more and more investors to allocate to infrastructure as an asset class in their portfolios. I want to switch a bit to talk about the relationship between what we've been speaking of and tokenization digital assets. So the report noted that the I shares Bitcoin

trust ETF became the fastest growing ETP in history. It surpassed $70 billion in AUM in just 341 trading days across 2024 and 2025. What is that level of speed and adoption tell us about the current capital demand for digital assets? Well, Ibit was a product, is a product that really bridges between traditional finance and decentralized finance. The idea that we could take a decentralized finance asset like Bitcoin, wrap it in the exchange traded product and make it available to basically anyone with a brokerage account, brought defy into the Tridefi world. And we expect that trend to likely to continue. There's a lot of demand for assets that can behave differently than stocks and bonds. And so we've seen a tremendous amount of interest from the

traditional finance space in an asset like Bitcoin where it's more driven by things like geopolitical uncertainty, rising distrust in institutions, the risk of debasement of currencies or rampant inflation. All of those things tend to be providing tailwinds for an asset like Bitcoin. And we live in an environment where I think those are very real risks. So increasingly, very traditional portfolio managers are looking at Bitcoin as a way to hedge out some of those risks in their portfolio. In Toronto, every arrival is a statement, and nothing says it better than this. Cadillac Optic was the number one selling luxury EV in Canada for 2025. Find your rhythm across a seamless 33-inch display and an immersive 19 speaker AKG surround audio system. This city demands agility,

and Optic delivers with precision to make every drive extraordinary. Let's take the Cadillac. Find out more at Cadillac Canada.ca. Luxury sales claim based on S&P Global Mobility, Canadian new vehicle total registrations for calendar year 2025 for the Cadillac definition of luxury. A significant share of tokenized real world assets currently reside on the Ethereum blockchain. And we're also seeing expectations that tokenization will continue to expand across asset classes. So how do you see tokenization reshaping access, liquidity, and transparency for a broader range of investors? Well, it's likely to evolve. You know, right now we largely see as tokenized cash or stable coins, and that's where the massive amount of volume is occurring today. There needs to be a market that develops around this. When you have tokenized assets, you need to have the infrastructure behind it. You have to have the market-making capabilities.

There needs to be sensible regulation around it. So there's a whole ecosystem that has to develop around it, but there's certainly the promise of tokenization that could allow for the 24-7 trading of assets, trading around the world, instantaneous settlement, perhaps easier access to decentralized finance tools like lending through smart contracts. So there's a lot of promise through tokenization, but it's also about really having an ecosystem develop around it to support it appropriately. A couple more questions for you as we draw to the close of our discussion today.

One, you know, the 2026 outlook really did a brilliant job of connecting the dots between compute, power grids, and geopolitics and how all of these themes interplay. But looking beyond that, looking ahead to the next three to five years, what are maybe one or two emerging or under the radar themes or maybe tech breakthroughs that you think maybe investors should be paying close attention to? First of all, I would say, I think there's a lot of durability to the themes we talked about today. Yes, we call it the 2026 outlook, but in reality, these are things that we see multi-year, if not decades-long horizons behind. So we are not trying to, you know, immediately pivot away from our interest in things like artificial intelligence or geopolitics or tokenization

and beyond. What I will say is I think the intersection of those themes and how they evolve in the next few years will be really interesting. One of the areas we did not talk about is the intersection of artificial intelligence and health care. This is one of the sectors that you could see both revenue acceleration through artificial intelligence. Think about developing revolutionary new drugs that hopefully treat various different diseases or ailments, but also you could see cost-cutting benefits through artificial intelligence. Could it be faster with less trial and error developing those drugs that reduce the amount of costs to bring them to market?

So there's both a revenue and a cost opportunity in the healthcare space. And then we talked a little bit about it in the AI section as well. I think this from just digital AI to physical AI with robotics, with autonomous vehicles, that's something that we think is going to become an increasingly important part. of the conversation with AI going forward. Well, and finally, what do you think are one or two important frameworks we should use to really filter out some of the short-term market noise and write out these generational mega forces over the long run?

I think the important thing to look at is what is the state of the technology? What's the use case? What's the size of the opportunity behind that use case? And then ultimately, what's the probability that it gets fulfilled? The earlier you are in a theme, potentially the more opportunity you have, but also the more risk you have that it doesn't play out. Where we are with artificial intelligence today is really in a sweet spot where it's still very early. It still hasn't seen, you know, economy-wide adoption and disruption yet.

But we have enough evidence to believe that this is here to stay, that this is a real technology with many different use cases that continues to improve at light speed. And when you combine those factors together, that creates the conditions for a really important theme and potentially an important allocation in people's portfolios. Fantastic. Well, I think you've given our list. and viewers a lot to think about as we move ahead into the next decade of investment. Jay, thanks so much for joining me today. Thanks for having me. As always, people in the program may have interests in the stocks they talk about, and the Motley Fool may have formal recommendations for or against, so don't buy ourselves

stocks based solely on what you hear. All personal finance content follows Motley Fool editorial standards and is not approved by advertisers. Advertisements are sponsored content and provided for informational purposes only. To see our full advertising, advertising disclosure, please check out our show notes. For the Motley Fool Hidden Gems investing team, I'm Rachel Warren. Thanks for listening. We'll see you next time.