The Bid - How to Invest in AI vs Tech In a Portfolio
Episode Description:
AI investing is a hot topic of conversation. But how should investors be considering both tech and AI in their portfolios - as part of the same allocation, or should they be separate? Jay Jacobs, US Head of Thematic and Active ETFs at BlackRock joins host Oscar Pulido to discuss whether investors should consider AI and tech as separate allocations, different investing approaches to AI and specific sectors to explore within the AI ecosystem.
Sources: The Economist IT companies log strong revenue growth outside key North America market, May 1, 2024; Profiles of the Future: An Inquiry into the Limits of the Possible, Arthur C. Clarke, 1962
Written Disclosures
This content is for informational purposes only and is not an offer or a solicitation. Reliance upon information in this material is at the sole discretion of the listener.
For full disclosures go to Blackrock.com/corporate/compliance/bid-disclosures
TRANSCRIPT
<<THEME MUSIC>>
Oscar Pulido: AI investing is a hot topic of conversation. We recently discussed AI and tech investing with Tony Kim and his insights from his annual Silicon Valley tech tour. But how should investors be considering both tech and AI in their portfolios - as part of the same allocation, or should they be separate?
Welcome to The Bid, where we break down what's happening in the markets and explore the forces changing the economy and finance. I'm Oscar Pulido
Jay Jacobs, US Head of Thematic and Active ETFs at BlackRock joins me to discuss whether investors should consider AI and tech as separate allocations, different investing approaches to AI and specific sectors to explore within the AI ecosystem.
Jay, thank you so much for joining us on The Bid.
Jay Jacobs: Thank you for having me.
Oscar Pulido: Jay, as we have five mega forces that we've been talking about that the BlackRock Investment Institute highlighted as structural drivers of return over the long term. These include things like, the aging population, the transition to a low carbon economy, and also artificial intelligence. So, when you hear artificial intelligence being dubbed a mega force, do you agree with that?
Jay Jacobs: Absolutely. And there's a few reasons why this is a mega force. I would say one reason to just brute force it is going to have trillions of dollars of impact on the global economy. So, it's big, it's powerful.
But I think secondly, this isn't just a narrow theme. This is something that is going to impact a wide range of sectors and industries as they start to adopt artificial intelligence. I think that's critical to any megaforce is that it should really have broad implications.
And then I think the third reason is that it's going to impact investor portfolios. Whether you intentionally allocate to the AI theme or not, the impact that it's having on the technology sector, the impact it's having on the energy sector, this means that it is going to impact basically all portfolios in the world one way or another. And it really is important for investors to consider that impact as they build their portfolios for the future.
Oscar Pulido: So, Jay, I'm curious to hear, what are you hearing in terms of the sentiment towards this topic from the investors that you meet with?
Jay Jacobs: there's a lot of excitement around AI right now, and I think a lot of this stems from the fact that we've really hit a new catalyst for artificial intelligence. Now, taking a step back, the idea of artificial intelligence has been around for a very long time. The Turing test, which was designed to determine if something was a computer or a human, was created in 1950. We've even had, Siri on our phones for over 10 years, but now we've hit this inflection point with ChatGPT and generative AI platforms that make it more accessible and frankly, more useful than ever before. So, I think a lot of investors are just trying to figure out, what does this mean, what does this mean for my portfolios, what does this mean for my everyday lives and how do I prepare for this?
Now what we've seen, in these first few months of this AI revolution though, is a lot of focus on just a few names, a lot of kind of concentration on household names in the AI space that's common in early days of a technological revolution. But you're starting to see now more interest in thinking about what's next, what's inning number two for artificial intelligence from an investing lens and from what this means for my everyday life.
Oscar Pulido: And we've learned a lot from folks like Jeff Shen about the history of AI and while it feels very recent to us as investors or the topic being talked about in markets, it's been around for a while, but it still feels to me like we're early in the theme in terms of capturing the investment opportunity. I don't know if you'd agree with that. And maybe if you do, how early in the theme are we?
Jay Jacobs: We're still in really early stages of the AI theme. Chat. GPT was released to the world in November 2022. We're a year and change beyond that at this point, really powerful mega forces can take decades to fully, I develop and have the full impact of it felt. So, what are some of the other things to evolve over the next decade or so? I think one is they'll continue to fine tune this technology. Large language models could get more complex and more nuanced than ever before. two, we're seeing the growth of data at an exponential rate and at its very fundamental basis, AI is just about leveraging data to generate more valuable outputs.
And the third thing is that we're getting more computing power than ever before. The semiconductors are getting more powerful. We're seeing hundreds of billions of dollars invested in data centers and really aggregating all of this compute into artificial intelligence. So, if you have better models, more data, more computing power, you really start to see exponential growth in artificial intelligence and an exponential increase in the value of artificial intelligence.
So, you put that all together and the fact that we've been at this for 20 months, 21 months, it's still very early in this mega force.
Oscar Pulido: And from your observation, what are the industries or the companies that have been most impacted by this early stage, mega force, either positively or negatively?
Jay Jacobs: Well, some of the earliest companies are in the technology space, which are actually in the software space because you could think about how, generative AI creates content, some of that content can be actually coding and programming languages for software development. So, some of the companies that have been the earliest adopters of artificial intelligence are just software companies.
Legal and consulting services, so if you can get more efficient in creating documents, more efficient in creating PowerPoints, more efficient in creating strategy documents, those segments of the economy have been affected by this already. But also, if you could look at the healthcare space, we see a ton of opportunity for artificial intelligence, how hospitals are managed to get more efficient, usage of doctors and nurses and medical devices. You look at pharmaceutical development, which is really an exercise in data, in terms of getting all this genetic and personal data and understanding how different drug compounds are going to interact with that to develop revolutionary drugs, there's billions of dollars of opportunity there as well.
So, this isn't an exhaustive list, but if you just take it as technology, healthcare professional services across legal and consulting, you're already talking about hundreds of billions of dollars of opportunity across the economy.
Oscar Pulido: And I know you're not an AI skeptic, but believe it or not, there are some of those people out there and it's natural whenever we have new technology that is unknown and we don't really know the future ramifications, but what do you say to somebody who is a skeptic or when you think about some of the industries that maybe have been negatively impacted so far.
Jay Jacobs: I guess that I would question the nature of the skepticism. I think it's fair for people to say this technology will take time to be adopted, that some of the use cases might be more valuable than other use cases, that maybe, we're being overpromised artificial intelligence in the short term.
But if you really take a long-term structural view of this theme, there's just a lot of conviction that this is going to have a major economic impact. You can see it when you use these tools, how there's really a brilliance, almost a magic to some of these artificial intelligence tools. A quote that I love is that any substantially advanced technologies indistinguishable from magic, that's where we are with generative AI today. Whether you're asking it to write a poem about financial investing or if you're, asking it to develop some strategy document for you, it's really a very powerful tool. And so, I think we learn how to harness this magic and make it an everyday tool, the use cases and the economic impact are going to be massive.
Oscar Pulido: There's a lot of interest, there's a lot of evolution. It seems like when you want to invest in AI, people think about investing in technology and I'll, maybe I'll just invest in the technology sector. are those the same things? If you want to invest in AI and just investing in the tech sector,
Jay Jacobs: A lot of AI companies are in the tech sector, but the tech sector isn't just AI. And one of the terms we use, and apologies, this is like a business consulting, a term here, but MECE mutually exclusive, collectively exhaustive.
This is how the sector world works. Every company has to be tied to one sector and every sector has to be unique in that no company can be tagged to two sectors. So, what that means in the artificial intelligence space is sometimes you have companies that are in the consumer discretionary space, but actually run really powerful cloud computing platforms that are essential to AI, or some companies maybe create software, which is really useful to AI, which is in the tech sector, but other companies might be tagged as a communication services company. So, if you just look at AI from a traditional sector lens, you're not necessarily capturing all the right companies that could exist outside of IT. And you're also going to capture companies within IT that are not AI: printer companies or companies that are, developing glass for smartphones.
Oscar Pulido: So, it's more nuanced is what you're saying. While we like to Break things up into nice, neat categories and definitions, when you talk about something like AI, it sounds like it can cut across numerous sectors.
Jay Jacobs: It does. So, you really have to look from the bottoms up with a fresh lens of identifying what are the AI companies around the world today, regardless of sector, regardless of geography. But really try to understand where these companies fit in the AI value chain.
Oscar Pulido: So, you mentioned the value chain and the AI space can cut across sectors. And so, when you think about the investment opportunities, where should people be looking?
Jay Jacobs: Right now, a lot of people are looking really at the mega cap tech names, specifically in the United States. And some of these companies have the most resources, the most data, the most software engineers, but that's really a very concentrated and limited view of AI. If you look under the hood, I think one of the most compelling opportunities right now is in the infrastructure layer of AI. What we mean by the infrastructure layer is semiconductors, digital infrastructure, even power infrastructure.
Because it's still early days, there could be different platforms that succeed in AI. There could be different products that succeed in AI, but regardless of what platform or product or a large language model of artificial intelligence wins, we know there's a common need, which are those semiconductors, the data centers, and the power.
Right now, AI is going to really drive a lot of power, demand growth. It's going to drive a lot of demand for semiconductors particularly. General processing graphics, processing units, it could even drive a lot of demand for things like copper and other materials that are necessary for data centers and digital infrastructure. So, it's really about not just trying to predict the winners 10 years from now, but who are the companies that form that base layer of infrastructure today and are benefiting from this build out.
Oscar Pulido: And that's consistent with what you talked about earlier. You just said copper. you talked about semis, which is the technology sector. But I'm recalling a conversation that we had with Will Su from the fundamental equities team and his discussion around AI was the demand for energy, that it's going to create. And we talked about data centers as well. So I go back to this question that when you think about AI and investing in AI, it is really different than just investing in the technology sector. Maybe you can elaborate, a bit more on that.
Jay Jacobs: It is. And so, part of that is really thinking across the entire AI value chain. You absolutely have technology companies that are some of the leading voices and developers and products in the AI space today, but if you look below that, that there's companies involved in real estate that are involved in AI.
These are the data centers that own valuable properties that can host, cloud computing services and a lot of compute power in them, and have all the security and, cooling that's necessary to run those. you can look at the energy companies that are going to be supplying power to those data centers.
You can look at companies that own transmission lines that are going to connect the power to those data centers, the semiconductor developers. It's really this entire ecosystem. And so, what I would really suggest that investors do is not get laser focused on just mega cap tech. You really have to look broadly across the economy to understand what is feeding into artificial intelligence.
Not just what is feeding into it, but also what are some of the critical choke points. I think energy could be a choke point. We really have to rapidly scale energy production in the US to be able to feed all these data centers. The physical real estate itself is a choke point. It takes time to build new data centers.
It takes permitting, it takes licenses, it takes materials and labor. Even semiconductors where you see really long supply chains, where there's wait times for some of these really powerful semiconductors, that's a choke point as well. So, it's about considering the entire value chain, it's about looking at who's benefiting in the value chain today, which is really that infrastructure layer. And it's about understanding what are those pivotal choke points where there can be really powerful economic pricing because these companies really have a scarce resource.
Oscar Pulido: As you're describing AI I think of it as a technology, but you're making me think of it more as a theme, that really touches on a lot of parts of the economy and a lot of different sectors.
And so, if you're an investor and you're building a portfolio, it sounds like you have to think about an allocation to AI as distinct from an allocation to tech. And maybe should investors be incorporating both of these in their portfolio or how would you ask, how would you think an investor should think about allocating in this space?
Jay Jacobs: Well, it’s not necessarily either or, but I think because there's overlap between the technology sector and AI, people just have to consider, what is that intersection? we know that investors that are looking just broad benchmarks across US equities or global equities are going to have a lot of tech exposure 'cause these are some of the biggest companies by market cap. But if you really want to have granular exposure to AI and really benefit from this mega force, you have to really make an intentional allocation.
So, one way that we're seeing investors do this is selling down technology exposure and replacing it with an artificial intelligence basket. That's just one way to fund it, we see other people maybe even selling down core exposure and buying an artificial intelligence basket. but you really have to think about how these two areas are intersecting because there is overlap between the two.
Oscar Pulido: And is there a geographical bias when you allocate to AI, do you, inherently allocate more to one part of the world than another? Or is it pretty diverse geographically as well?
Jay Jacobs: Right now, the artificial intelligence theme is very US driven. it could broaden out and you could see more companies around the world enter into the AI space as this theme develops. But if you look right now, the leaders across these different parts of the value chain from some of the chip designers, from some of these LLM platforms, to the data centers, to the energy, a lot of that still is very US focused today.
Oscar Pulido: But presumably the second order effect the beneficiaries of AI are probably more global in nature, and maybe in that case, not just in the US.
Jay Jacobs: Oh, absolutely. technology is a huge export from the United States. If you look specifically at the tech sector, 60% of its revenues come from overseas. So, I would absolutely expect that artificial intelligence will be one of those exports going forward. in a lot of ways this is part of the artificial intelligence theme is this global race for artificial intelligence. And I think if you look at valuations today, a lot of what's baked into some of these artificial intelligence companies is the expectation that this is a global theme, not just a US theme.
Oscar Pulido: And Jay, you spend a lot of time, talking about this theme and thinking about it and helping investors think about how to allocate in their portfolios. But what's that one thing you would want to leave the audience with when they're thinking about artificial intelligence in their portfolios.
Jay Jacobs: I think the one takeaway for investors is to really consider, do they have exposure to the full value chain of artificial intelligence? I'm willing to bet most investors have some exposure just because of how dominant some of the mega cap tech names in the United States are in broad us, US or global benchmarks, but likely investors are missing that longer tail of artificial intelligence names. Again, the semiconductors, the digital infrastructure names, some of the energy names that are going to benefit from this theme. So, it's really, you have to look across the entire value chain rather than just a concentrated handful of mega cap tech stocks.
Oscar Pulido: And you alluded to this, but the BlackRock Investment Institute has also recently talked about the fact that there's a lot of money being invested in this space in AI and all the value chain to use your term, but the return on investment from that might not be immediate. It might take some time before companies benefit from that investment. And I wonder, do you share that viewpoint and how long do you think people have to wait before we really start to see that return on investment?
Jay Jacobs: It depends on what part of the value chain you're looking at. if you look at this massive amount of Capex that's being spent by some hyper-scalers to develop artificial intelligence models, they're spending money today on building data centers, on securing energy, on getting semiconductors.
So, some of those companies are making money right now in artificial intelligence. I think where some of the lag is going to be is in the enterprise or government or in the consumer space, really starting to use these artificial intelligence products, the output from all that Capex, that could take time. It takes time for people to change their habits, it takes time for enterprises to adopt a new technology, to feel comfortable with it, to roll it out to their employees, to encourage its use. There will be a lag, but I think it's a well-deserved lag in the sense that its people taking their time to adopt a new technology and understand how to best use it.
Oscar Pulido: And perhaps, tying it to your comments about the investment opportunities, the companies that are benefiting from it right now are maybe the ones you hear more about. They're getting an immediate benefit, but the ones that have more of a lagged impact of it, it might be the future investment opportunity when it starts to improve their productivity and, when it's accretive to the growth of the overall company.
Jay Jacobs: I think that's right. If we look at today's winners, it's really focused on those artificial intelligence infrastructure companies. It's the semiconductors that are. Very powerful data processors that are powering kind of the training behind these large language models. it's the data centers that are in short supply as we look to rapidly scale computing power across the country.
it's some of the energy companies which are finding really a new growth avenue that they haven't had for the last 15 years in terms of. Growing energy demand from artificial intelligence. Those are today's winners that are collecting revenue really in this near-term timeframe. But if we look longer term, you know that healthcare use case for pharmaceuticals, it might be five years before we realize profitability from that.
Because you have to develop a new drug, you have to develop a new drug, cheaper or better than before. By harnessing this artificial intelligence power that's going to take a little bit of time. So, there's absolutely a, a. A different timescale that some of these companies are operating on in terms of when they will realize the benefit from this theme.
Oscar Pulido: And Jay, how are you finding artificial intelligence? Enter your day-to-day life or has it yet? do you find yourself. Using it or being impacted by it in your personal life or maybe even in your work life.
Jay Jacobs: I'm never going to create an itinerary for a trip again. I, that is something I fully outsource to, to the large language models. even writing emails, it, it takes a little bit of rewiring how you think about using this new tool.
I think we take for granted tools sometimes, we, we know how to use calculators, we know when to use calculators. We know how to interact with them. in a lot of ways AI is just another tool, but we have to get used to it. We have to start thinking about how we use it in our everyday lives to incorporate it, and then we can start to really enjoy the productivity gains of outsourcing some of the less efficient tasks we do, and creating more time for the more complicated, nuanced tasks that we do every day.
Oscar Pulido: In fairness, you might be a little bit ahead of me in terms of the adoption of AI in your everyday life. I still feel like I'm coming up the curve.
But I'm sure we'll hear more about the applications of AI in the world and how to think about it in investor portfolios. in the meantime, Jay, we really appreciate you joining us on the Bid.
Jay Jacobs: Thanks, Oscar.
<<SPOKEN DISCLOSURES>>
This content is for informational purposes only and is not an offer or a solicitation. Reliance upon information in this material is at the sole discretion of the listener.
For full disclosures go to Blackrock.com/corporate/compliance/bid-disclosures
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