The Bid logo

What is The Bid?

The Bid is BlackRock’s investment podcast where investment professionals break down what’s happening in the world of investing and explores the forces changing the economy and finance. From stock market outlooks to geopolitics and technology, BlackRock speaks to thought leaders and industry experts from about biggest trends moving markets.

AI Beyond Tech: How Artificial Intelligence Is Reshaping the Economy

The AI economy is expanding beyond technology as businesses adopt artificial intelligence across healthcare, manufacturing, financial services and more. Jay Jacobs joins The Bid to explore AI adoption, infrastructure constraints, physical AI and how the next phase of this megaforce could reshape the broader economy.

273. AI Beyond Tech: How Artificial Intelligence Is Reshaping the Economy

Web title: How Artificial Intelligence Is Reshaping the Economy

The AI economy is entering a broader phase as artificial intelligence moves beyond technology companies and into healthcare, manufacturing, financial services and other parts of the economy. At the same time, growing demand for computing power is highlighting physical constraints around electricity, semiconductors and critical materials.

In this episode of The Bid, host Oscar Pulido speaks with Jay Jacobs, BlackRock’s US Head of Equity ETFs, about how the AI economy is evolving. They discuss where AI adoption is taking hold, what can distinguish productive implementation from investment without clear results, and why infrastructure is becoming increasingly important to the AI build-out.

The conversation also examines the intersection of AI investing, physical infrastructure, megaforces and capital markets—from data centers and power generation to robotics, autonomous vehicles and digital assets.

Key insights:

How AI adoption is broadening beyond the technology sector.
Why having a defined use case can matter when companies deploy AI.
Where power, copper and specialized materials may create physical constraints.
How healthcare and manufacturing are applying AI to complex processes.
Why robotics and autonomous vehicles represent a shift toward physical AI.
How digital assets could support machine-to-machine transactions and micropayments.

Keywords: AI economy, AI investing, AI adoption, infrastructure, megaforces, capital markets, artificial intelligence

Sources: 2026 Thematic Mid-Year Update Welcome to the AI Economy, iShares.com;

Written Disclosures In Episode Description:

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. Reference to any company or investment strategy mentioned is for illustrative purposes only and not investment advice. For full disclosures, visit blackrock.com/corporate/compliance/bid-disclosures.

<<TRANSCRIPT>>

Oscar Pulido: Artificial intelligence has dominated the investment conversation for the past several years. Much of that attention has focused on the technology itself, the race to build more powerful models, the semiconductors needed to run them, and the billions of dollars being spent on AI infrastructure. But the story is getting bigger.

AI is moving beyond the technology sector and deeper into all sectors of the economy as businesses look for ways to turn that investment into real-world value. At the same time, growing demand for computing power is colliding with very physical constraints, from chips and critical materials to electricity and the power grid.

So, are we entering a new phase of the AI investment story? 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. Today, I'm joined by Jay Jacobs, BlackRock's US head of equity ETFs, to talk about the AI economy.

We'll look at where AI adoption is accelerating, how the potential winners may be changing as companies put AI to work, why the physical demands of AI are becoming increasingly important, and what this expanding opportunity could mean for investors.

Jay, thank you so much for joining us on The Bid.

Jay Jacobs: Thank you for having me back.

Oscar Pulido: Jay, AI is a topic that we spend a lot of time talking about these days. We have to. It's so pervasive across the economy. And for the last few years, when we've talked about AI, much of the conversation has been centered on technology companies, semiconductor companies, and the huge amount of money that's being spent to build all of this AI infrastructure.

You're now describing something much broader, what you're terming an AI economy. So, what has changed and what do you mean by that?

Jay Jacobs: We're now four years into this AI megaforce since ChatGPT was released to the world, and we saw this huge acceleration in the investment and adoption of artificial intelligence.

And what our thematic mid-year update is really, starting to explore is what does the impact of AI look like beyond just technology. We've, of course, seen a tremendous amount of investment in semiconductors and data centers, but there are now impacts on power companies, on materials that are important to the AI build-out.

We're seeing consumer products, we're seeing healthcare services benefiting from artificial intelligence. We're seeing financial services use artificial intelligence. So, this is becoming one of the broadest themes in the market today, and we're seeing the impact across the economy. We're starting to project out kind of what that might mean for consumers and workers going forward.

Oscar Pulido: It's not just companies that are involved in the sort of foundational building of AI, but now we're talking about companies that are not necessarily AI companies, but they're starting to utilize it and think about how it benefits, their business. And in fact, that has been one of the big questions hanging over the AI story, which is this enormous amount of capital that is being invested, by the hyperscalers, I think is the term that we often use when we think about these big companies that are investing in AI. But what evidence are you seeing that AI is beginning to move from investment and experimentation into something that businesses can actually monetize?

Jay Jacobs: We're seeing widespread adoption, so if you look across the economy, and there's different surveys of this, but anywhere from a quarter to a third of companies have really started to see meaningful adoption of artificial intelligence.

And I think what's so interesting is the biggest adopters today are tech companies themselves. What I think is interesting is the, the types of companies coming after that are not necessarily the most forward tech-oriented companies out there. We're looking at healthcare companies. We're looking at law firms.

These companies tend to be a little bit slower to adopt new technologies, but they're actually at the cutting edge of AI adoption. And so, what that signals to us is this is not just a tech theme anymore. This is a broad economic theme, and every type of industry is thinking about how to incorporate it into their business one way or another.

Oscar Pulido: And so, what actually separates those companies that are creating value from AI from those that are simply investing in it? And I think the companies that are creating value are maybe some of the ones that you just alluded to. But is there some sort of commonality between those companies? Does it start with the management teams of those companies' views on how to adopt it? What are some of those common threads?

Jay Jacobs: there's some great studies on this because, look, a lot of companies are obviously looking at artificial intelligence and trying to understand how they can incorporate it into their business. But what we've found, there was a great survey that showed that about 40% of companies that are investing heavily in artificial intelligence have had basically none to actually negative impact on their business from AI adoption, meaning it might just be an expense or a distraction that's not helping their business.

Now, the other 60% is seeing very positive gains. So, what are some of the commonalities? I think the most important aspect here is a company needs to have a plan for how they're going to utilize AI and to resource that plan appropriately. A kind of fun and unique example here is there's a potato chip company that wanted to invest in having better potato chip manufacturing, and you'd think, all potato chips look the same, but in reality, there's big differences in terms of the humidity that might be present when you're on a production line or the exact granularity of the potatoes or the salt and the other ingredients and how they're interacting.

So, what this one company did is they set up dozens of cameras along the production line. They collected a ton of information about how their potato chips are made. They created a digital twin of all their potato chips, trying to really have a more digital representation of what this whole process looks like.

And then they applied artificial intelligence to this process to figure out how exactly they could optimize making the perfect potato chip. And they saw tremendous, e- enhancements in the quality, in the ROI that they spent on artificial intelligence. This was just a great kind of small-ish example of how it's not just saying, Okay, everybody use AI. It's about having a very specific plan for what are you trying to achieve? Are you investing in it properly and implementing AI for success?

Oscar Pulido: I didn't think we'd go from AI and draw an arrow to potato chips, but I suppose your point is that this is how pervasive AI can be across the economy, and there's so many things that it can be applied to. And ultimately, potato chips, it's a manufacturing process, and AI can be very beneficial in the manufacturing process.

You also mentioned areas like healthcare and legal services before. So, as you think about, these various areas, what is this telling you about where we are in the adoption cycle of AI?

Jay Jacobs: It's just showing that you're seeing all different types of industries and companies adopting artificial intelligence.

Now, for a long time, many industry observers have really pegged the healthcare space as one of the most ripe for AI disruption sectors out there, for a variety of reasons. One is you could look at the pharmaceutical space, and you could think about mapping different proteins, trying to understand how different compounds would interact with those proteins, doing things like AI representations of lab tests, all these things that are expensive and take a lot of time.

Using artificial intelligence might be faster and more economical. But you could also look at hospital systems. hospitals are incredibly complex. Trying to understand how many doctors do you need, how many nurses do you need, how many beds do you need, how does this change by day of the week or seasonality to this.

Being able to solve a complex system with artificial intelligence could make hospitals operate more efficiently. and then, of course, you could look at the doctor-patient relationship and how, at the Mayo Clinic, thousands of medical professionals already opted into using AI to basically help take notes and help with their observations of patients to have a better process for capturing, their records and for coming up with treatment plans.

There's so much opportunity in healthcare. I think the fact that this industry is demonstrating very rapid adoption of AI is a very good sign for how we could see better medical outcomes going forward.

Oscar Pulido: And it does sound like we are in the early stages of broader adoption cycle. So, you mentioned there's a lot of opportunity, and it's ironic because when we think of artificial intelligence, we think of technology, we think of a digital world. But when we talk to Jean Boivin, who's the head of the BlackRock Investment Institute, and we talk about the, the outlook over the course of the year, he has started to remind us that we are also in a world of scarcity. When it comes to building out the AI economy, there are some physical limits that we run into.

So, when we talk about these supply chain constraints on things like chips, memory, these are different chips by the way, we're talking about semiconductor chips, electricity, copper, why are these constraints becoming such an important part of the AI story?

Jay Jacobs: You're absolutely right that, these things don't just live in the cloud, as they say. There's actual physical needs to be able to build out all of this artificial intelligence infrastructure. so, let's go through, through a few of them. I think one is access to power. AI is very power hungry. In fact, we think we might need about 121 gigawatts of power for data centers by the end of the decade. which to put that in context, about one gigawatt is about the size of a medium-sized metropolitan area, and every gigawatt of data center capacity is $40 to $50 billion of investment.

This is a massive amount of power to bring on scale, so you could see how the amount of investment in chips and power generation and power distribution, reaches the trillions of dollars relatively quickly, just to be able to support, this build-out of data centers and the necessary power

I think another angle here, though, is the commodities. The copper that needs to go into some of these data centers, and the distribution of the power, and the power generation. A lot of this copper is a common denominator. There’re even more idiosyncratic types of metals and materials that are going to be really important. I always think this inter- this example's interesting, but indium.

We all know indium, the 49th metal on the periodic table. this is basically if you think about what silicon is to semiconductors, indium is to lasers and lithography. And the reason this is important is as data centers get bigger and more powerful; you can't just rely on copper wiring anymore. You have to use things like fiber optics to move data around the data center really quickly, and so therefore, you need indium.

But this is a metal that's a byproduct largely of zinc mining, and so the economics of pulling this metal out of the ground look very different when it's only a small portion of the economic value of an overall mine. And it's very concentrated in its, geographical production.

And so, something that most people probably didn't think of five years ago could be a choke point in artificial intelligence going forward. And that's just one of dozens of examples of types of metals like that.

Oscar Pulido: I knew I should have paid more attention in science class in grade school and in perhaps in high school. But I'm remembering when we talked to Tony Kim, who's the head of the technology group here at BlackRock. he has in describing the AI build-out really talked about it's all about physics and really going back to some of the basic premises that, physics, tell us about constraints. And as we're starting to build out more data centers, more semiconductor plants, we have to be aware of the physical limits that the economy is going to provide us.

And so how do you think about that mismatch between the speed of AI demand? Because as you're saying, this is not just the technology sector story anymore. It's going beyond that in terms of the application and the demand for these types of services. So, the mismatch between the growth in demand and what's to come, and the speed at which the physical economy can actually respond.

Jay Jacobs: You're right. It's an absolute mismatch because maybe for every one person that listens to this podcast, they tell three more people that AI's coming, and they try to adopt it faster, but that doesn't necessarily change the trajectory of how many data centers could be built or how much power can be brought online or how much metal can be pulled out of the ground.

So, the digital world can obviously move much faster than the physical world. I think what gets really interesting is what are the types of solutions different companies are looking at to accelerate that process. you talked about AI becoming a physics problem. it's literally becoming a physics problem as you think about data centers in space and how do you scale rocketry to be able to bring up more GPUs into orbit where you can get access to 24/7, solar power, but you also have all kinds of economics around how do you bring up those GPUs as efficiently as possible.

So, this is very much a, a physics problem in terms of expanding where data centers can be. And then of course, we're also seeing this play out in terms of the defense space as well, which is how do you use artificial intelligence, basically in the 21st century when we have conflicts around the world?

What is the use of AI? What shouldn't be the uses of AI? How are the types of investments that defense departments are making? So, AI is really expanding into different areas, different industries right now.

Oscar Pulido: I feel when we talk about AI, it feels still a little bit abstract. We're interacting with a large language model, something like ChatGPT, and we're asking it a question, it's giving us some answers. but we're also now starting to talk about more physical forms of AI. So, I'm thinking about robots or autonomous vehicles or machines, and I'm just wondering how close are we to that becoming a more meaningful part of the AI economy? It feels very futuristic, but is that actually closer than we realize?

Jay Jacobs: For some of these things, it's already happening. autonomous vehicles, readily available autonomous vehicles already exist in about 35 cities around the world today. we're already seeing humanoid robots working in industrial manufacturing alongside humans in certain car manufacturing plants.

We're seeing 50-plus companies working on humanoid robots that could sell in the tens of thousands of dollars but could ultimately end up in a place like your house doing household chores for you. So, it's happening today. It's accelerating. I still think it's the next stage of AI adoption is going to be that move from the digital to the physical world in terms of humanoid robotics. But it’s coming, if not already here in many instances, like autonomous vehicles.

Oscar Pulido: I know when we spoke in the past, I think you were probably one of the first people to remind us that investing in AI was not just an investment in the technology sector, even though that might be where we first thought of, putting our capital to work, in that it could impact a number of different sectors.

And you're making the point that AI is touching everything from semiconductors and power to healthcare and robotics, and even the legal sector, where there's some, innovation taking place. So how should investors be thinking differently about the AI opportunity from here? How has your thinking evolved since we first spoke about that a couple years ago

Jay Jacobs: I think for a long time in technology, four years, AI was somewhat, equivalent to mega cap tech stocks. And I think we've long argued that there's more to it, but I think there's even more to it now. It's not just about looking at more semiconductor stocks or more types of large language model providers or data owners.

Now you really could look at all different types of sectors to understand who's contributing into this trillion-dollar build-out of AI, as well as which are the companies that are adopting artificial intelligence and could improve their products or become more efficient because of that AI adoption. So, in a way, I think this actually helps investors because you get more breadth, more opportunity to choose from.

I think for active managers, that creates great potential for them. But also, in terms of portfolio construction, the idea that you can get AI exposure well outside of the tech sector can be really helpful because of how much concentration we have in portfolios today. So, a lot of opportunities for investors, whether you're picking stocks or whether you're, a portfolio allocator.

Oscar Pulido: And when we think about the investment opportunity in AI, we should talk about digital assets. these are two separate technological trends. They often get conflated, but where do these two worlds actually come together and intersect? And how could digital assets help support the growth of an AI-driven economy?

Jay Jacobs: a lot to unpack there, but one of the ways that we see digital assets and AI interacting is just how do AI agents transact in a commercial-driven way going forward? I'll use an example. If you were booking a trip to go to California next week, and your AI agent that's fine-tuned to Oscar Pulido's preferences knows you like a window seat, they know you like to leave in the morning, they know what meal you like to order on the plane and where you like to stay when you're in California, it could book all of that, but it actually doesn't really work in today's travel booking model, right?

Because all of these websites make their money on advertisements, and if your AI agent is booking all these things for you, those advertisements aren't going to be very useful anymore. So instead, your AI agent will probably have to buy data from some sort of data vendor to understand which flights are available, which hotels are available for which prices.

And this won't cost a lot. It could cost a few pennies, but trying to transact in that sort of sense with a credit card doesn't necessarily work very efficiently because of the way credit card, payment models work. But it could work very efficiently when you move to digital assets. You could have a very clear, smart contract that understands what type of data you're buying, what you're willing to pay for it. It knows instantly that data has been transferred to you, and you've transferred payment for that. You could use digital assets like stable coins or even Bitcoin or other digital assets to be able to do that micro payment for that data. And so, it's a very efficient way to exchange payment for data in these micro transactions.

That's just one example of how, at a very kind of individual level, digital assets and AI could be interacting. There are many more examples, but just to keep it in the micro.

Oscar Pulido: it's interesting. As I've been reflecting on some of the things that you're mentioning, when we started talking about AI a few years ago, it was a very brand-new topic, and I think if you think about it now, there are some things that, investors tend to be well aware of: the demand for semiconductors, the demand for power.

Then there are some things where maybe they're not quite aware that it's broadening out to other sectors, and there are areas like healthcare and legal services that are starting to implement AI and extract some efficiencies. And I think the point you made at the very end is that there are still even other things, on the horizon that are coming.

There's still some more work to do, but as you draw this thread throughout all of this, the economy is evolving. The ground is really shifting underneath our feet.

Jay Jacobs: I think that's well put. And look, there's entire businesses that will be created using artificial intelligence as a key component of their product offering, and these businesses don't even exist anymore.

think back to the internet, how many different types of businesses, the entire social media sector, being born overnight because of, because of the internet, because of high-speed internet, because of mobile phones. That type of innovation and business development just hasn't occurred yet and presents a ton of opportunity but will probably be towards the end of this AI cycle.

So, if you think about the build-out being the first phase, the more broader adoption, the physical implementation of AI, and then finally these entire new industries being formed, that's generally the trajectory that we're seeing for this AI, megaforce. And every time I come on here, we've made a little bit more progress. There's a little bit more innovation, a little bit more that's new, but we still have a long way to go to see full economy-wide adoption.

Oscar Pulido: It feels like we're watching a movie, and you keep fast-forwarding a few minutes, every time we talk about, and the movie is still ongoing, so we're going to have to have you back. But I think what's on everybody's mind, Jay, is do you have a favorite potato chip? Actually, I'm just reflecting on, the discussion you talked about and the manufacturing process there. Mine is salt and vinegar. I don't know if you have a particular preference.

Jay Jacobs: The cheddar and sour cream, I just can't stop eating those.

Oscar Pulido: There's a lot of good flavors to choose from, and there's a lot that we're going to need to follow with respect to the AI theme in the months and years ahead, and we look forward to having you back. Thanks for sharing your latest views and thanks for doing it here on the Bid

Jay Jacobs: Thanks for having me.

Oscar Pulido: Thanks for listening to this episode of The Bid. If you've enjoyed this episode, check out our episode with Rob Goldstein, where he discusses how tokenization is revolutionizing the infrastructure of finance. Make sure you subscribe to The Bid wherever you get your podcasts

<<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. Reference to the names of each company mentioned is merely for explaining the investment strategy and should not be construed as investment advice or recommendation. For full disclosures, visit blackrock.com/corporate/compliance/bid-disclosures

MKTG0926-H-5923872-EXP0927

273. AI Beyond Tech: How Artificial Intelligence Is Reshaping the Economy

Web title: How Artificial Intelligence Is Reshaping the Economy

The AI economy is entering a broader phase as artificial intelligence moves beyond technology companies and into healthcare, manufacturing, financial services and other parts of the economy. At the same time, growing demand for computing power is highlighting physical constraints around electricity, semiconductors and critical materials.

In this episode of The Bid, host Oscar Pulido speaks with Jay Jacobs, BlackRock’s US Head of Equity ETFs, about how the AI economy is evolving. They discuss where AI adoption is taking hold, what can distinguish productive implementation from investment without clear results, and why infrastructure is becoming increasingly important to the AI build-out.

The conversation also examines the intersection of AI investing, physical infrastructure, megaforces and capital markets—from data centers and power generation to robotics, autonomous vehicles and digital assets.

Key insights:

How AI adoption is broadening beyond the technology sector.
Why having a defined use case can matter when companies deploy AI.
Where power, copper and specialized materials may create physical constraints.
How healthcare and manufacturing are applying AI to complex processes.
Why robotics and autonomous vehicles represent a shift toward physical AI.
How digital assets could support machine-to-machine transactions and micropayments.

Keywords: AI economy, AI investing, AI adoption, infrastructure, megaforces, capital markets, artificial intelligence

Sources: 2026 Thematic Mid-Year Update Welcome to the AI Economy, iShares.com;

Written Disclosures In Episode Description:

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. Reference to any company or investment strategy mentioned is for illustrative purposes only and not investment advice. For full disclosures, visit blackrock.com/corporate/compliance/bid-disclosures.

<<TRANSCRIPT>>

Oscar Pulido: Artificial intelligence has dominated the investment conversation for the past several years. Much of that attention has focused on the technology itself, the race to build more powerful models, the semiconductors needed to run them, and the billions of dollars being spent on AI infrastructure. But the story is getting bigger.

AI is moving beyond the technology sector and deeper into all sectors of the economy as businesses look for ways to turn that investment into real-world value. At the same time, growing demand for computing power is colliding with very physical constraints, from chips and critical materials to electricity and the power grid.

So, are we entering a new phase of the AI investment story? 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. Today, I'm joined by Jay Jacobs, BlackRock's US head of equity ETFs, to talk about the AI economy.

We'll look at where AI adoption is accelerating, how the potential winners may be changing as companies put AI to work, why the physical demands of AI are becoming increasingly important, and what this expanding opportunity could mean for investors.

Jay, thank you so much for joining us on The Bid.

Jay Jacobs: Thank you for having me back.

Oscar Pulido: Jay, AI is a topic that we spend a lot of time talking about these days. We have to. It's so pervasive across the economy. And for the last few years, when we've talked about AI, much of the conversation has been centered on technology companies, semiconductor companies, and the huge amount of money that's being spent to build all of this AI infrastructure.

You're now describing something much broader, what you're terming an AI economy. So, what has changed and what do you mean by that?

Jay Jacobs: We're now four years into this AI megaforce since ChatGPT was released to the world, and we saw this huge acceleration in the investment and adoption of artificial intelligence.

And what our thematic mid-year update is really, starting to explore is what does the impact of AI look like beyond just technology. We've, of course, seen a tremendous amount of investment in semiconductors and data centers, but there are now impacts on power companies, on materials that are important to the AI build-out.

We're seeing consumer products, we're seeing healthcare services benefiting from artificial intelligence. We're seeing financial services use artificial intelligence. So, this is becoming one of the broadest themes in the market today, and we're seeing the impact across the economy. We're starting to project out kind of what that might mean for consumers and workers going forward.

Oscar Pulido: It's not just companies that are involved in the sort of foundational building of AI, but now we're talking about companies that are not necessarily AI companies, but they're starting to utilize it and think about how it benefits, their business. And in fact, that has been one of the big questions hanging over the AI story, which is this enormous amount of capital that is being invested, by the hyperscalers, I think is the term that we often use when we think about these big companies that are investing in AI. But what evidence are you seeing that AI is beginning to move from investment and experimentation into something that businesses can actually monetize?

Jay Jacobs: We're seeing widespread adoption, so if you look across the economy, and there's different surveys of this, but anywhere from a quarter to a third of companies have really started to see meaningful adoption of artificial intelligence.

And I think what's so interesting is the biggest adopters today are tech companies themselves. What I think is interesting is the, the types of companies coming after that are not necessarily the most forward tech-oriented companies out there. We're looking at healthcare companies. We're looking at law firms.

These companies tend to be a little bit slower to adopt new technologies, but they're actually at the cutting edge of AI adoption. And so, what that signals to us is this is not just a tech theme anymore. This is a broad economic theme, and every type of industry is thinking about how to incorporate it into their business one way or another.

Oscar Pulido: And so, what actually separates those companies that are creating value from AI from those that are simply investing in it? And I think the companies that are creating value are maybe some of the ones that you just alluded to. But is there some sort of commonality between those companies? Does it start with the management teams of those companies' views on how to adopt it? What are some of those common threads?

Jay Jacobs: there's some great studies on this because, look, a lot of companies are obviously looking at artificial intelligence and trying to understand how they can incorporate it into their business. But what we've found, there was a great survey that showed that about 40% of companies that are investing heavily in artificial intelligence have had basically none to actually negative impact on their business from AI adoption, meaning it might just be an expense or a distraction that's not helping their business.

Now, the other 60% is seeing very positive gains. So, what are some of the commonalities? I think the most important aspect here is a company needs to have a plan for how they're going to utilize AI and to resource that plan appropriately. A kind of fun and unique example here is there's a potato chip company that wanted to invest in having better potato chip manufacturing, and you'd think, all potato chips look the same, but in reality, there's big differences in terms of the humidity that might be present when you're on a production line or the exact granularity of the potatoes or the salt and the other ingredients and how they're interacting.

So, what this one company did is they set up dozens of cameras along the production line. They collected a ton of information about how their potato chips are made. They created a digital twin of all their potato chips, trying to really have a more digital representation of what this whole process looks like.

And then they applied artificial intelligence to this process to figure out how exactly they could optimize making the perfect potato chip. And they saw tremendous, e- enhancements in the quality, in the ROI that they spent on artificial intelligence. This was just a great kind of small-ish example of how it's not just saying, Okay, everybody use AI. It's about having a very specific plan for what are you trying to achieve? Are you investing in it properly and implementing AI for success?

Oscar Pulido: I didn't think we'd go from AI and draw an arrow to potato chips, but I suppose your point is that this is how pervasive AI can be across the economy, and there's so many things that it can be applied to. And ultimately, potato chips, it's a manufacturing process, and AI can be very beneficial in the manufacturing process.

You also mentioned areas like healthcare and legal services before. So, as you think about, these various areas, what is this telling you about where we are in the adoption cycle of AI?

Jay Jacobs: It's just showing that you're seeing all different types of industries and companies adopting artificial intelligence.

Now, for a long time, many industry observers have really pegged the healthcare space as one of the most ripe for AI disruption sectors out there, for a variety of reasons. One is you could look at the pharmaceutical space, and you could think about mapping different proteins, trying to understand how different compounds would interact with those proteins, doing things like AI representations of lab tests, all these things that are expensive and take a lot of time.

Using artificial intelligence might be faster and more economical. But you could also look at hospital systems. hospitals are incredibly complex. Trying to understand how many doctors do you need, how many nurses do you need, how many beds do you need, how does this change by day of the week or seasonality to this.

Being able to solve a complex system with artificial intelligence could make hospitals operate more efficiently. and then, of course, you could look at the doctor-patient relationship and how, at the Mayo Clinic, thousands of medical professionals already opted into using AI to basically help take notes and help with their observations of patients to have a better process for capturing, their records and for coming up with treatment plans.

There's so much opportunity in healthcare. I think the fact that this industry is demonstrating very rapid adoption of AI is a very good sign for how we could see better medical outcomes going forward.

Oscar Pulido: And it does sound like we are in the early stages of broader adoption cycle. So, you mentioned there's a lot of opportunity, and it's ironic because when we think of artificial intelligence, we think of technology, we think of a digital world. But when we talk to Jean Boivin, who's the head of the BlackRock Investment Institute, and we talk about the, the outlook over the course of the year, he has started to remind us that we are also in a world of scarcity. When it comes to building out the AI economy, there are some physical limits that we run into.

So, when we talk about these supply chain constraints on things like chips, memory, these are different chips by the way, we're talking about semiconductor chips, electricity, copper, why are these constraints becoming such an important part of the AI story?

Jay Jacobs: You're absolutely right that, these things don't just live in the cloud, as they say. There's actual physical needs to be able to build out all of this artificial intelligence infrastructure. so, let's go through, through a few of them. I think one is access to power. AI is very power hungry. In fact, we think we might need about 121 gigawatts of power for data centers by the end of the decade. which to put that in context, about one gigawatt is about the size of a medium-sized metropolitan area, and every gigawatt of data center capacity is $40 to $50 billion of investment.

This is a massive amount of power to bring on scale, so you could see how the amount of investment in chips and power generation and power distribution, reaches the trillions of dollars relatively quickly, just to be able to support, this build-out of data centers and the necessary power

I think another angle here, though, is the commodities. The copper that needs to go into some of these data centers, and the distribution of the power, and the power generation. A lot of this copper is a common denominator. There’re even more idiosyncratic types of metals and materials that are going to be really important. I always think this inter- this example's interesting, but indium.

We all know indium, the 49th metal on the periodic table. this is basically if you think about what silicon is to semiconductors, indium is to lasers and lithography. And the reason this is important is as data centers get bigger and more powerful; you can't just rely on copper wiring anymore. You have to use things like fiber optics to move data around the data center really quickly, and so therefore, you need indium.

But this is a metal that's a byproduct largely of zinc mining, and so the economics of pulling this metal out of the ground look very different when it's only a small portion of the economic value of an overall mine. And it's very concentrated in its, geographical production.

And so, something that most people probably didn't think of five years ago could be a choke point in artificial intelligence going forward. And that's just one of dozens of examples of types of metals like that.

Oscar Pulido: I knew I should have paid more attention in science class in grade school and in perhaps in high school. But I'm remembering when we talked to Tony Kim, who's the head of the technology group here at BlackRock. he has in describing the AI build-out really talked about it's all about physics and really going back to some of the basic premises that, physics, tell us about constraints. And as we're starting to build out more data centers, more semiconductor plants, we have to be aware of the physical limits that the economy is going to provide us.

And so how do you think about that mismatch between the speed of AI demand? Because as you're saying, this is not just the technology sector story anymore. It's going beyond that in terms of the application and the demand for these types of services. So, the mismatch between the growth in demand and what's to come, and the speed at which the physical economy can actually respond.

Jay Jacobs: You're right. It's an absolute mismatch because maybe for every one person that listens to this podcast, they tell three more people that AI's coming, and they try to adopt it faster, but that doesn't necessarily change the trajectory of how many data centers could be built or how much power can be brought online or how much metal can be pulled out of the ground.

So, the digital world can obviously move much faster than the physical world. I think what gets really interesting is what are the types of solutions different companies are looking at to accelerate that process. you talked about AI becoming a physics problem. it's literally becoming a physics problem as you think about data centers in space and how do you scale rocketry to be able to bring up more GPUs into orbit where you can get access to 24/7, solar power, but you also have all kinds of economics around how do you bring up those GPUs as efficiently as possible.

So, this is very much a, a physics problem in terms of expanding where data centers can be. And then of course, we're also seeing this play out in terms of the defense space as well, which is how do you use artificial intelligence, basically in the 21st century when we have conflicts around the world?

What is the use of AI? What shouldn't be the uses of AI? How are the types of investments that defense departments are making? So, AI is really expanding into different areas, different industries right now.

Oscar Pulido: I feel when we talk about AI, it feels still a little bit abstract. We're interacting with a large language model, something like ChatGPT, and we're asking it a question, it's giving us some answers. but we're also now starting to talk about more physical forms of AI. So, I'm thinking about robots or autonomous vehicles or machines, and I'm just wondering how close are we to that becoming a more meaningful part of the AI economy? It feels very futuristic, but is that actually closer than we realize?

Jay Jacobs: For some of these things, it's already happening. autonomous vehicles, readily available autonomous vehicles already exist in about 35 cities around the world today. we're already seeing humanoid robots working in industrial manufacturing alongside humans in certain car manufacturing plants.

We're seeing 50-plus companies working on humanoid robots that could sell in the tens of thousands of dollars but could ultimately end up in a place like your house doing household chores for you. So, it's happening today. It's accelerating. I still think it's the next stage of AI adoption is going to be that move from the digital to the physical world in terms of humanoid robotics. But it’s coming, if not already here in many instances, like autonomous vehicles.

Oscar Pulido: I know when we spoke in the past, I think you were probably one of the first people to remind us that investing in AI was not just an investment in the technology sector, even though that might be where we first thought of, putting our capital to work, in that it could impact a number of different sectors.

And you're making the point that AI is touching everything from semiconductors and power to healthcare and robotics, and even the legal sector, where there's some, innovation taking place. So how should investors be thinking differently about the AI opportunity from here? How has your thinking evolved since we first spoke about that a couple years ago

Jay Jacobs: I think for a long time in technology, four years, AI was somewhat, equivalent to mega cap tech stocks. And I think we've long argued that there's more to it, but I think there's even more to it now. It's not just about looking at more semiconductor stocks or more types of large language model providers or data owners.

Now you really could look at all different types of sectors to understand who's contributing into this trillion-dollar build-out of AI, as well as which are the companies that are adopting artificial intelligence and could improve their products or become more efficient because of that AI adoption. So, in a way, I think this actually helps investors because you get more breadth, more opportunity to choose from.

I think for active managers, that creates great potential for them. But also, in terms of portfolio construction, the idea that you can get AI exposure well outside of the tech sector can be really helpful because of how much concentration we have in portfolios today. So, a lot of opportunities for investors, whether you're picking stocks or whether you're, a portfolio allocator.

Oscar Pulido: And when we think about the investment opportunity in AI, we should talk about digital assets. these are two separate technological trends. They often get conflated, but where do these two worlds actually come together and intersect? And how could digital assets help support the growth of an AI-driven economy?

Jay Jacobs: a lot to unpack there, but one of the ways that we see digital assets and AI interacting is just how do AI agents transact in a commercial-driven way going forward? I'll use an example. If you were booking a trip to go to California next week, and your AI agent that's fine-tuned to Oscar Pulido's preferences knows you like a window seat, they know you like to leave in the morning, they know what meal you like to order on the plane and where you like to stay when you're in California, it could book all of that, but it actually doesn't really work in today's travel booking model, right?

Because all of these websites make their money on advertisements, and if your AI agent is booking all these things for you, those advertisements aren't going to be very useful anymore. So instead, your AI agent will probably have to buy data from some sort of data vendor to understand which flights are available, which hotels are available for which prices.

And this won't cost a lot. It could cost a few pennies, but trying to transact in that sort of sense with a credit card doesn't necessarily work very efficiently because of the way credit card, payment models work. But it could work very efficiently when you move to digital assets. You could have a very clear, smart contract that understands what type of data you're buying, what you're willing to pay for it. It knows instantly that data has been transferred to you, and you've transferred payment for that. You could use digital assets like stable coins or even Bitcoin or other digital assets to be able to do that micro payment for that data. And so, it's a very efficient way to exchange payment for data in these micro transactions.

That's just one example of how, at a very kind of individual level, digital assets and AI could be interacting. There are many more examples, but just to keep it in the micro.

Oscar Pulido: it's interesting. As I've been reflecting on some of the things that you're mentioning, when we started talking about AI a few years ago, it was a very brand-new topic, and I think if you think about it now, there are some things that, investors tend to be well aware of: the demand for semiconductors, the demand for power.

Then there are some things where maybe they're not quite aware that it's broadening out to other sectors, and there are areas like healthcare and legal services that are starting to implement AI and extract some efficiencies. And I think the point you made at the very end is that there are still even other things, on the horizon that are coming.

There's still some more work to do, but as you draw this thread throughout all of this, the economy is evolving. The ground is really shifting underneath our feet.

Jay Jacobs: I think that's well put. And look, there's entire businesses that will be created using artificial intelligence as a key component of their product offering, and these businesses don't even exist anymore.

think back to the internet, how many different types of businesses, the entire social media sector, being born overnight because of, because of the internet, because of high-speed internet, because of mobile phones. That type of innovation and business development just hasn't occurred yet and presents a ton of opportunity but will probably be towards the end of this AI cycle.

So, if you think about the build-out being the first phase, the more broader adoption, the physical implementation of AI, and then finally these entire new industries being formed, that's generally the trajectory that we're seeing for this AI, megaforce. And every time I come on here, we've made a little bit more progress. There's a little bit more innovation, a little bit more that's new, but we still have a long way to go to see full economy-wide adoption.

Oscar Pulido: It feels like we're watching a movie, and you keep fast-forwarding a few minutes, every time we talk about, and the movie is still ongoing, so we're going to have to have you back. But I think what's on everybody's mind, Jay, is do you have a favorite potato chip? Actually, I'm just reflecting on, the discussion you talked about and the manufacturing process there. Mine is salt and vinegar. I don't know if you have a particular preference.

Jay Jacobs: The cheddar and sour cream, I just can't stop eating those.

Oscar Pulido: There's a lot of good flavors to choose from, and there's a lot that we're going to need to follow with respect to the AI theme in the months and years ahead, and we look forward to having you back. Thanks for sharing your latest views and thanks for doing it here on the Bid

Jay Jacobs: Thanks for having me.

Oscar Pulido: Thanks for listening to this episode of The Bid. If you've enjoyed this episode, check out our episode with Rob Goldstein, where he discusses how tokenization is revolutionizing the infrastructure of finance. Make sure you subscribe to The Bid wherever you get your podcasts

<<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. Reference to the names of each company mentioned is merely for explaining the investment strategy and should not be construed as investment advice or recommendation. For full disclosures, visit blackrock.com/corporate/compliance/bid-disclosures

MKTG0926-H-5923872-EXP0927

Who hosts The Bid investment podcast?

Oscar Pulido

Oscar Pulido

Global Head of Product Strategy for Fundamental Equities
Oscar D. Pulido, CFA, Managing Director, is the Global Head of Product Strategy for the Fundamental Equities (FE) business. In this role, he is responsible for commercial strategy, product development, and business activities to drive growth across the FE platform. He is also the host of BlackRock's flagship investment podcast, The Bid.

What topics does The Bid cover?

About The Bid (FAQs)

  • The Bid breaks down what’s happening in the world of investing and explores the forces shaping the economy and financial markets. From market outlooks to geopolitics and technology, it features insights from BlackRock experts and global thought leaders on the trends moving markets.

  • The Bid is for anyone interested in understanding markets, investing, and the global economy. From finance professionals and business leaders to students, policymakers, and lifelong learners, the podcast provides expert perspectives on the trends and issues shaping our world.

  • The Bid covers a wide range of topics shaping markets and the global economy, including macroeconomic trends, equity and fixed income markets, geopolitics and policy, technology and innovation, energy and the energy transition, and long-term “mega forces.”

  • The Bid is hosted by Oscar Pulido, Managing Director and Global Head of Product Strategy for Fundamental Equities at BlackRock, and produced by Stevie Manns.

  • New episodes are released weekly, with regular drops on Fridays across platforms including Spotify, Apple Podcasts, and YouTube.

  • Investors listen to The Bid for expert perspectives from BlackRock and global thought leaders, clear explanations of complex market trends, and timely insights on the forces shaping economies and portfolios.

  • The Bid has earned multiple awards and honors from the Webby Awards and the Financial Communications Society, where it has been recognized as a leading branded podcast for its content, storytelling, and audience engagement.