AI podcast episodes

256. AI and Bond Markets: How Artificial Intelligence Is Reshaping Fixed Income Investing

Episode Description:

AI and bond markets are becoming increasingly interconnected as artificial intelligence reshapes capital demand, market structure, and investing approaches across fixed income. As inflation regimes shift and traditional diversification dynamics evolve, investors are rethinking the role bonds play in portfolios.

In this episode of The Bid, host Oscar Pulido speaks with Jeff Rosenberg, Senior Fixed Income Portfolio Manager at BlackRock Systematic, about how AI and bond markets are evolving together. They explore how the rise of artificial intelligence is driving a new wave of capital investment, influencing real interest rates, and increasing debt issuance as companies finance AI infrastructure through bond markets.

The conversation also examines how AI and bond markets intersect at the investment level. Rosenberg explains how advances in machine learning and generative AI are enhancing systematic investing, improving tools like sentiment analysis, and enabling deeper insights across thousands of issuers, central banks, and global markets. Finally, they discuss how modernization in fixed income — including electronic trading and the growth of bond ETFs — is transforming liquidity and price discovery. Together, these shifts are creating new opportunities and challenges for investors navigating a more complex and data-driven bond market.

Key insights in this episode:

How bond markets have changed over time

The shifting role of bonds in portfolios

Inflation, rates, and diversification challenges

How AI is impacting bond markets – Both Micro and Macro

Debt issuance and AI financing trends

Using AI in fixed income investing

Systematic investing and data-driven strategies

The future of bond markets and technology

Sources: Stock-Bond Diversification Offers Less Protection From Market Selloffs, IMF article, February 2026; On Secular Stagnation in the Industrialized World, Paper released by Harvard and Bank of England, 2019; Financing the AI boom: from cash flows to debt, BIS Bulletin paper, January 2026; ‘AI is eating software’ and it is redefining supply chain decision-making as a result, Supply Chain Management Review article, 2026; How AI is transforming Investing, BlackRock 2026; The economic potential of generative AI: The next productivity frontier, McKinsey 2026; 40 years of innovation in pursuit of alpha, BlackRock, 2025; Key Trends in Credit Markets for 2025 Barclays 2025

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. In the UK and non-European Economic Area countries, this is authorized and regulated by the Financial Conduct Authority. In the European Economic Area, this is authorized and regulated by the Netherlands Authority for the Financial Markets. For full disclosures, visit blackrock.com/corporate/compliance/bid-disclosures.

TRANSCRIPT

Oscar Pulido: Today's bond market looks very different from what it did just a few decades ago. Not only has the structure of the market evolved, but so has the role bonds play in portfolios. Trading is increasingly electronic. Data is more abundant. The number of bonds available to investors has grown dramatically At the same time, the dynamics shaping returns have become more complex with shifting inflation and policy regimes, the rise of the AI investment cycle and an ever-evolving mix of risks and opportunities.

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.

On this episode, we're taking a closer look at how bond markets have changed and what that means for investors. From the evolving role, bonds play in portfolios to the expanding use of data and AI. In investing, we'll examine today's fixed income landscape and the growing role of systematic data-driven approaches within it.

Joining me is Jeff Rosenberg, senior fixed income portfolio manager for BlackRock. Systematic. Jeff has watched these shifts unfold over the course of his career and is seeing how investors are adapting to a world. Bonds may behave differently than they have in the past.

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

Jeff Rosenberg: Oscar, great to be back on The Bid.

Oscar Pulido: Well, Jeff, you're a bond investor and you've had a front row seat to many of the transformative shifts that have been shaping the bond market recently. Maybe we can just take a step back and when you think back to the start of your career or even earlier, what was different about the bond market then as compared to today.

Jeff Rosenberg: Yeah. I like this question. My perspective goes back over 30 years and you think about that history in terms of specific periods and one period that we came out of was the post-GFC to the COVID period, we saw very low levels of inflation. We saw very strong levels of bond market diversification. So, bonds really featured in, portfolios as almost the perfect portfolio hedge. It was insurance where the premium paid you. You come out of the post COVID environment and we've seen some dramatic shifts- Inflation is now too much inflation rather than too little inflation.

And we're seeing positive stock bond correlation. We've seen it in the 2022 environment. We've seen it recently, coming out of the Iran war shock that bonds aren't necessarily the hedge that they used to be. And it's forcing a whole rethink of the role of bonds in investors portfolios.

Oscar Pulido: And that's consistent with what Jean Boivin talked about in the 2026 BII global outlook where he talks about a diversification mirage and that it's, it seems harder to diversify in today's environment. And as you're mentioning bonds haven't played the traditional hedge role in a portfolio that maybe they did for much of the last 10, 15 years. So, given that transformation, Jeff, and what's happened in bond markets, how are investors approaching their investments in bonds and the markets overall?

Jeff Rosenberg: It's this movement, away from the kind of traditional role of thinking about bonds in a portfolio from a total return investing perspective and more towards thinking about bonds more from the specific outcomes that they can provide and that range of outcomes can be income, which is their traditional role, or other specific outcomes. And it's really the shift in the conversation towards systematic investing where we bring in that approach where it's really about engineering for specific types of outcomes.

Oscar Pulido: Jeff, I think there's a saying Bonds for ballast is often how people have thought about the role of bonds in their portfolio. I think what you're saying is that bonds may still play that role, but they can also play other roles as well.

Jeff Rosenberg: Yeah, and it's not only just that the bonds are playing other roles and the biggest one of that is, is going to be thinking about them more from income than from ballast. But also what we do in systematic investing in fixed income to use different techniques in the bond markets to deliver the more traditional outcomes to bring back some of the ballast that the asset class is lost as a function of the, primarily the shift in the inflationary environment from too little to too much inflation. It's undermined the asset class characteristic, by using techniques like long-short investing, you can kind of bring some of that ballast technique back, or ballast outcome, I should say back to fixed income.

Oscar Pulido: So far it sounds like what you're describing is a transformation that has been driven by a change in the economic environment. You mentioned the GFC, the global financial crisis through COVID was a period of, low inflation, low real interest rates, and now we've been in a different regime and that's been part of the transformation.

But let's talk about technology and AI, which presumably has had a transformative impact on the bond market. What are you seeing from that lens?

Jeff Rosenberg: Let me talk a little bit about the impact that it's had on the bond market and then the how, which is how it's changing how we invest in bonds using AI and technology.

First on the what, there's two aspects. There's a macro aspect, and that is part of that kind of post GFC to COVID environment was this period of very little or low investment demand. Relative to a lot of supply. And so, the impact of that intersection between low demand and high supply was very low and even negative real interest rates. So you come out of the COVID period and you've got a lot of factors, but AI we can clearly see is this massive capital investment regime, and it's happening globally in terms of the scale of capital investment required. So that's shifting upward, the demand for capital, and it's happening in an environment of other factors as well that we used to talk about- globalization changes, reshoring, securing energy sources, partly driven by AI. All of this is shifting up the demand for capital and that from the bond market's perspective is a huge impact with regards to what is the outlook for real interest rates. Real interest rates are low, but they're rising and they're coming off this period of zero and negative levels to increasing levels. So, that's the kind of the big impact because bond market investors returns start with the real interest rate, especially when we think about the returns after inflation. So that's the macro piece.

The micro piece is the AI story started with financing those capital requirements out of free cash flow. And the big shift over the last year has been, this is now a debt financed exercise. And so the movement of AI into the debt markets to finance that expansion is bringing both opportunities and risks. The opportunities are, you've got more debt issuance across both the hyperscalers, the environment around that, the infrastructure build out. The risk side is, you own some of that risk more in your bond portfolio. This was a bigger concern a few months ago. The concern has been overwhelmed by a another risk, which is the disruption risk. And the disruption risk best encapsulated by this tagline, AI eats software is a technological shock to the established business models of software as a service which has been big issuers in the debt markets. And so that's creating sort of a repricing as we try anticipate what is the impact of this transformational technology on the valuation and terminal value of many of these business models that are being disrupted. So you're seeing both sides of that in terms of the what side of the bond market.

Oscar Pulido: So, what you're saying, Jeff, is that the first impact that AI is having on the bond markets is you have companies that are at the center of the AI build out that are now issuing more debt. This journey of capital expenditures that they were on initially was funded from just cash on the balance sheet, but now they're looking to the debt markets to finance that. And so that's one of the impacts that it's having on the bond markets. It's more supply of fixed income. But maybe talk a little bit about the how does this impact how bond investors like yourself approach the market?

Jeff Rosenberg:

But there's another story as well. That's part of this transformative aspects of the modern bond market, and that is the impact of modernization- particularly within the credit markets. So, the credit markets as a sub component of the broad bond markets. And this maybe, Oscar is a whole other topic for another Bid, which is really the role that bond market ETFs have played in transforming how price discovery happens within the bond market. It's a very interesting story, but the impact in terms of the combination of tools the upgrading of tools that AI is delivering to investors, particularly systematic investors and melding that with the changes that we've seen in how transactions and price discovery happens within the credit markets is creating what I call a Reese's Peanut Butter Cup moment for systematic investing.

What does that mean? It means two great tastes that go great together. Chocolate and peanut butter. The chocolate is systematic investing is about the real time processing, using tools like AI and big data, updating optimal portfolios in small increments, on nearly a real time basis. That melds really nicely with the peanut butter of the modernization of credit market intermediation, where we trade less on individual large positions on big benchmark bonds and more on a portfolio wide basis.

That intersection is, unlocking more alpha opportunities for investors. Approaching bond market and credit market management, portfolio management from a systematic perspective. So that's a way in which, technological transformation we're seeing across a number of features, both the AI component in how we invest systematically, but also in terms of the technological advancements and the changes that the ETF revolution has brought about in terms of price discovery and how we do intermediation in the credit markets.

Oscar Pulido: It sounds like technology is making investing in the bond market perhaps more convenient or for you as an investor, giving you access to more opportunities and ways to generate return.

And Jeff, just to go back to something you said which is how AI is now and generative AI is giving you more insight into the market. I suppose as a bond investor, you care a lot about what central banks are saying and the press releases and the statements from the heads of those central banks. So it sounds like not so long ago you could read the transcripts from central banks and do maybe a word count how many times they said a positive word versus a negative word, and that seemed pretty insightful at the time. But you're saying it's evolved even from there, where you now have a better way to gauge sentiment. Is that a good example of how AI is impacting your space?

Jeff Rosenberg: It's a good example, it allows us to systematize what we've always done from a fundamental perspective. Now the example of the Fed is a bad one because that is the most widely followed Central Bank in the world. There's a lot of depth. It's in the price. You're not going to get a lot of alpha and edge on that. where you see it is doing that not just for the Fed, but doing it for all central banks and doing it across large markets and small markets where you can get some more alpha in the macro space.

And then when it comes to this kind of sentiment analysis, it's really about doing it in five, 10,000 individual companies where you're taking in not only information from the company. The earnings releases, the press conferences, but also from analysts, analyst reports, media coverage. It's, it's really about the transformation of systematic investing from what has historically been a breadth game where you're doing a little bit of an edge across a lot of individual companies to adding, and this is really the change in what AI is bringing to systematic investing is adding some of the depth that has historically been the purview of deep value fundamental investors, we can now systematize some of that depth approach with these new AI tools. And that's really the kind of transformative thing that's happening on the horizon.

Oscar Pulido: So you've definitely highlighted a lot of transformations in the bond market, and I'm thinking there are investors, who still remember buying a bond over the counter and holding it to maturity and you've definitely painted a picture of a much more modern bond market and a much more modern approach that you're taking.

If you look forward, you've already painted a picture of a very futuristic scenario that we're living in today, but where's the bond market evolving from here? What do you see going forward?

Jeff Rosenberg: We've touched on it a little bit and it's really, the combination of those two points. the tools allow greater depth in the analysis in a systematic way. So, systematizing the depth of fundamental analysis that historically has been hard for systematic investors to penetrate that. That's kind of one point. And then the second point back to this modernization of bond markets, it's really about, encoding that capability into our real-time portfolio optimization. So, we've always had kind of transaction cost aware optimizations, but now you can make those optimizations liquidity aware. So, you bring into your investment process the two sides of the equation, the real time analysis of the large data across your portfolio, updating in small increments every single day, in this kind of near real time optimization, but then incorporating at the same time, what is the liquidity environment look like? But you're able to do that systematically because you have portfolio trading, you have greater electronification. of Credit trading and moving away from your earlier kind of description of getting on the phone and trading that big benchmark issue, evaporating, liquidity very quickly, having to work orders. That's the old style. New style is finding ways to expand the amount of alpha extraction that we're able to generate, by minimizing the transactions costs through these new ways of transacting.

Oscar Pulido: I think when we think about the markets, we think about stocks and there's literally thousands of stocks, right? But I think in the bond market, the number of unique issuers and bonds, is actually an order of magnitude bigger. So, it sounds like you need to use technology and some of the techniques that you're talking about too really find the opportunity. Is that a good way to think about it?

Jeff Rosenberg: Yeah, it's a great way of thinking about it. And it's also a great way in which the combination of the transformative technologies and the change in bond market intermediation unlock more opportunity for alpha extraction but you need to be able to minimize your transactions, costs. So all that alpha isn't basically eaten up by your transactions costs.

Oscar Pulido: Jeff, you've taken us on quite a tour here. We talked about bond ETFs, we talked about AI, the companies that are issuing debt, but also how you're using AI and technology to invest in the bond market. This sounds like a space that is evolving quick, thank you for shedding some light on this topic and thank you for doing it here on The Bid.

Jeff Rosenberg: Great to be here.

Oscar Pulido: Thanks for listening to this episode of The Bid. Next week we'll turn from bonds to stocks as we speak to Ibrahim Kanan about looking outside of the magnificent seven stocks that have been driving the biggest returns in indexes.

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. In the UK and Non-European Economic Area countries, this is authorized and regulated by the Financial Conduct Authority. In the European Economic Area, this is authorized and regulated by the Netherlands Authority for the Financial Markets. For full disclosures, visit blackrock.com/corporate/compliance/bid-disclosures

MKTG0326-5319757-EXP0327

The Bid Episode 250: Powering AI 2.0: Why the AI Boom Is Becoming an Energy Story

Episode Description:

Powering AI 2.0 is no longer just a technology story — it’s an energy and infrastructure story reshaping capital markets and the global economy. As artificial intelligence scales from training to real-world inference, electricity demand is accelerating at a pace few anticipated.

In this episode of The Bid, host Oscar Pulido is joined by Will Su from BlackRock’s Fundamental Equities Group to examine how Powering AI 2.0 is transforming utilities, natural gas markets, renewables, and nuclear power. With data centers expanding rapidly and gigawatt-scale facilities coming online, the AI build-out is driving a structural shift in U.S. electricity demand after more than a decade of stagnation.

Will explains why the energy sector sits at the center of AI investing. From the rise of bring your own power models to the growing role of natural gas as a dispatchable, scalable fuel source, the infrastructure required to support AI represents one of the largest capital investment cycles in modern history. The conversation also explores renewables, battery storage, and nuclear power — including the limits of restarts and the long timeline for new reactor construction.

Key insights from this episode:

Why natural gas has emerged as a key here and now fuel for AI infrastructure

How renewables and battery storage fit into the AI electricity mix

The long-term outlook for nuclear power and reactor construction

What bring your own power means for hyperscalers and utilities

How electrification and reshoring intersect with AI investing

Why the relationship between compute and energy is reshaping stock market trends

Keywords: Powering AI 2.0, AI investing, infrastructure, capital markets, energy transition, utilities, stock market trends, megaforces

Sources: From CES 2026 to Yottaflops: Why the AMD Keynote Highlights a Turning Point for AI Compute, AMD 2026; The Industrial Revolution, coal mining, and the Felling Colliery Disaster, Lancaster University, 2026; Bureau of Economic Analysis data 2026; Stargate's First Data Center Site is Size of Central Park, With At Least 57 Jobs, Bloomberg 2026; Energy Demand from AI, IEA 2026; Scaling bigger, faster, cheaper data centers with smarter designs, McKinsey 2025; EEI 2024 Review; Data Centers Ditching the Power Grid, Mark Carney's Viral Speech, and Some Joy, Clearview Energy; 2024 North American Energy Inventory, IER;

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. In the UK and non-European Economic Area countries, this is authorized and regulated by the Financial Conduct Authority. In the European Economic Area, this is authorized and regulated by the Netherlands Authority for the Financial Markets. For full disclosures, visit blackrock.com/corporate/compliance/bid-disclosures

<<TRANSCRIPT>>

Oscar Pulido: AI has been growing exponentially since Chat GPT burst onto the scene in November of 2022. The backdrop for the energy supporting AI today looks very different from two years ago. Models are growing larger data centers are scaling faster, and the demand for electricity is rising at a pace few expected. The story now goes beyond innovation in silicon. It's about the strain on global power grids, the race to build new generation, and the emerging divide between countries rich in energy and those constrained by it. AI becomes more deeply embedded in the global economy. The question isn't just what this technology can do, it's what amount of energy will it require to run?

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 we're joined by Will Su from BlackRock's Fundamental Equities Group. Will has been closely tracking the surge in electricity demand. Driven by AI and the implications for natural gas renewables, and nuclear power. We'll discuss how the energy landscape has shifted over the last 18 months, whether the world can build fast enough to meet AI's needs, and how investors might expect to see the energy landscape evolve.

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

Will Su: Thanks for having me back, Oscar.

Oscar Pulido: It has been almost two years since you were here. You and I spoke in May of 2024, and I actually remember that conversation because, Will, I think you were one of the first people that at least, drew some attention in my mind to the fact that the AI story is also an energy story. In fact, AI consumes a lot of energy, and you put a lot of numbers around that. AI has obviously become an even more dominant part of the conversation and ever more important part of the economy. So, can you talk to us about what changes you've seen in the energy landscape as it relates to this AI industrial revolution?

Will Su: So, a lot has changed over the last two years, and I think the biggest change has really been this deepening recognition of the critical role that energy plays, not just to power artificial intelligence, but in some ways being artificial intelligence. So, if you recall from our last conversation, the way you get these AI models to become smarter is to basically train them with more tokens and parameters. And that's just a fancy way of saying you're feeding in more data and you're building models with more and more variables, so they become increasingly intelligent.

The more tokens you put in, the more parameters you run, and the more pre and post training that you do, the smarter the models become, the closer they start to approach to human level general intelligence, and could one day surpass it. These improvements are coming with an exponential increase in power demand.

So even with some of the efficiency gains that we have made on the semiconductor side, the reality is today's AI models are more power hungry than ever to create. On our last episode, we talked about the concept of zeta flops. So let me introduce a new term. Today, we are firmly marching into the world of yottaflop compute. That's 1 trillion, trillion calculations per second. Again, just mind-bending numbers. And of course, each calculation just involves the movement of electrons between the semiconductor chips. So over time that power demand really starts to add up and grow exponentially. I like to think of it this way, since the beginning of human history, knowledge is power, but for the first time ever, power is knowledge. So, by some estimates, we are investing more than $1 trillion per year in the United States alone to enable everything around the AI build outs. Like our tech guru Tony Kim said on his episode of The Bid, this is the largest investment in human history.

Now, there has been some legitimate concerns in the markets recently that we could be overbuilding this AI capacity and the power infrastructure that's associated with it. The skeptics tend to point to a lack of clarity around AI use cases in the real world to justify the massive amounts of investment, and my pushback to that more pessimistic view is really grounded on two points.

Number one, we're still in the very early innings of powering AI, where training dominates electricity consumption. But over time, as AI goes from being a science experiment to a part of everyday life, you're going to start to see that power demand increasingly shift towards what's called inference. And inference is basically when you take the AI models that were perfected during training, put them into the real world and have them answer questions and solve problems, and do things for us in real time. And that inference demand is going to continue to ramp up over time as adoption increases, and we're already seeing real time signs of adoption increase.

And the second point really is as the technology of AI improves and as the unit cost of compute decreases, you are likely to see this long tail of inference demand really pick up over time. And this is actually a phenomenon that we have seen in the energy markets two centuries ago around coal demand during the Industrial Revolution So just like coal demand in England where the introduction of the combustion engine has made efficiencies, that much higher coal demand eventually increased by tenfold. In England, we have a blueprint for how AI demand is really poised to see exponential growth. As that technology gets better and the cost becomes cheaper. And so as more and more consumers and businesses start to adapt and embed AI into their daily activities, as the things that AI can do for us become more complex and thus more power intensive, there is a long, long runway for more power demand that will be absolutely necessary to enable this AI future of ours.

Oscar Pulido: I feel like we've already seen an inflection point in power demand, and I think you started to touch on that. Yet, despite the fact that we're still in the early innings, we have been seeing and hearing a lot about the exponential growth of data centers, which are needed to, to power this demand for AI and its development. How big of an impact is AI having on electricity demand in the world?

Will Su: Great question I think there's no mystery at this point to anyone that there's a lot of investment going into building these AI factories of the future. It's almost a cliche at this point, but we really are all living and investing in an AI driven economy today. If you look around the world today, there are about 12,000 operating data centers each with an average power capacity of 11 megawatts. That's enough to supply about 10,000 households. So, it's by no means a trivial number. But just compare that with the Stargate Project being built in Abilene, Texas. When the first phase of that project comes online later this year and energizes it will bring with it 1.2 gigawatts of compute capacity. So, for reference one gigawatt is roughly the average power capacity of the city of San Francisco. There are just going to be so many more of these things being built. And by the way, they're just impressive campuses from a physical standpoint. So, Stargate is going to be roughly the same footprint as Central Park in New York City. And not only are they the size of cities, but some of these data centers also literally consume more power than some of the biggest cities in the world. And we're currently building more than a dozen of these gigawatts scale data centers around the US and around the world.

 So, the question really becomes, if you add all of these together what percent of total electricity demand do they represent? the International Energy Agency estimated that in 2024 data centers worldwide consumed about 415 terawatt hours of electricity. That's about 1.5% of the world's total power demand. And here in the US we're clearly leading the world in this AI build out that market share is higher. Data centers today represent about 5% of American electricity demand.

The growth ahead is just about to get so much bigger. Since 2023 with the introduction of ChatGPT 4, which is really like this watershed moment for the rapid expansion of AI Buildouts, we have seen a whopping 200 gigawatts of new data center capacity proposed in the United States alone. But we think at least a quarter of that, or more than 50 gigawatts, could come online by the end of this decade. And that would take market share of data centers up to as much as 12% of American power production by then. And all of this is just going to drive a step change in America's power needs.

We are coming out of a 15-year period where power demand in this country has barely grown, but the forward estimates now expect up to 3% to annual growth all the way through 2040.

And what that really just means is we're going to make a lot of more investments into the overall power infrastructure within this country and around the world. Everything from generation to transmission, to distribution to last mile logistics. And I think our friend Balfe Morrison said a best on his episode of The Bid a few months ago. If you're bullish on AI and AI adoption, you have to be bullish on power and utilities. They really are one and the same.

Oscar Pulido: Yeah. And you mentioned knowledge is power, and now for the first time, power is knowledge. we really do need a lot of power to help this industrial revolution that is going on actually continue. You, you mentioned a number of statistics. I think you said that the, to power San Francisco, that's one gigawatt. and that there are plans for, as much as 200 gigawatts of data centers in the us but even if only a quarter of those pan out, that's 50 San Franciscos in terms of power demand.

And the last time you came on here, will, as part of how we generate this power, you talked about natural gas as one of the ways that, we are going to find the power to enable this AI, industrial revolution. Can you bring us up to speed on how the sector has done and what are the current trends for gas power generation?

Will Su: So, gas has really moved front and center in this whole AI data center build out, and I think it's important to just take a step back and set the scene for what gas really brings to the table here.

If you wanted to bring, bring a new data center online today, there are basically three ways you can power that data center. You can request an interconnection into your regional grid. You can build your own power plant and feed that electricity directly into your data center. Or you can do a combination of both.

So, on the grid side, the American utilities are really doing everything that they can to help us meet this future demand growth. They're investing more than a trillion dollars over the next five years to modernize every aspect of the grid. So again, generation, transmission, distribution. And that is a 30% increase from the last five-year period. So, a significant step up. But despite their best efforts, it is becoming increasingly clear that the grid alone is going to struggle to enable this AI revolution. You now have to wait more than four years to plug a new project into the grid. That is a delay that the hyperscalers can't really afford to wait for in this very competitive AI arms race.

Another very important issue is affordability for the American consumer. So, retail power prices in America were basically flat for the decade going into COVID, but after that they have grown by more than 30% in the last five years, and the trend is for additional increases in the coming years.

So, the very loud and clear message is this: to enable our AI build out and this AI future, we can no longer rely on connecting into the grid. Increasingly, we're going to have to invest in and construct new power generating assets that are dedicated to the data centers that they serve.

And this is what the industry calls BYOP or bring your own power. The power source sits behind the meter as a separate part from the overall grid to supply that data center.

This is where natural gas enjoys some really deep structural advantages that has positioned it as the here and now fuel source for the AI revolution. Natural gas is already the largest input into power generation in America, responsible for more than 40% of our generation. They're highly efficient and they release less than half the emissions when compared with coal power. We have abundant natural gas resources in this country that will meet our current demand for the next century. And gas can be deployed relatively quickly. So, when you put all that together, gas is very uniquely advantaged in this AI build out.

The next question obviously becomes, what is the investment opportunity in energy equities?

The top six natural gas producers in the country produce one fifth of all gas Su supply. That is a level of consolidation in a commodity business that we simply haven't seen since the start of the shale revolution 20 years ago. And there are other really bullish factors happening for natural gas. the most front and center one is going to be liquified natural gas or LNG. This is basically when you take natural gas and you super cool it down to about minus 260 degrees Fahrenheit, or minus 162 degrees Celsius so that it condenses into a liquid. LNG Demand has a long future to grow because the world requires this amount of electricity for their own power and their own electrification, including the build out of their own AI infrastructure.

So, if you take a look at US natural gas balances There are about 110 billion cubic feet per day, or BCFS per day, flowing through the US every day. Just to visualize that's enough gas to fill 3000 Empire State buildings. each and every day. I think between data centers and other electrification sources like the reshoring of industrials, we will add at least five BCS per day to that demand number on the power side by the end of this decade.

So, this should raise the floor price for natural gas prices and enable the lo low-cost producers to deliver better earnings and better returns for their shareholders as we go through this AI scale up in the coming years.

Oscar Pulido: You and I work down the street from the Empire State Building, and I walk by it almost every day. So, I'm trying to picture what 3,000 of those buildings looks like and then think about the volume of natural gas that is going to fill those buildings. But you're saying that's where we are now, that doesn't even take into account what the demand for natural gas could be going forward as again, we keep moving in this direction of this AI economy.

Will, we haven't talked about renewables, we talked about natural gas, but I think you've made the point that there needed to be, or needs to be, a partnership between gas and renewables to, to fuel the growth in the AI economy. How have renewable energy companies navigated the demand for power and how are they navigating the regulatory landscape as well?

Will Su: So, I think we should really be very proud of the progress that we have made in low emission power generation in this country. at the turn of the century, less than 30% of our power generation came from low emission resources, and the vast bulk of that was really nuclear and hydroelectricity is fast forward to today and more than 40% of our power now comes from low carbon emitting resources, and that's of course driven by the fast growth in both solar and wind. Solar is now almost 8% of our power generation, and wind is about 10%, both having grown from almost nothing 25 years ago.

Now that being said, the forward path between solar and wind is really starting to diverge here. While solar still has a lot of very strong momentum and the annual installation of capacity is tracking at around 30 gigawatts per year for when that number has really taken a step back and is tracking at just about a quarter of the pace of solar. And if you think about the future with data center demand front and center, I think solar enjoys some really nice structural advantages within renewables.

We're also seeing a lot more solar being built today with what's called battery energy storage systems, or BESS. What this does is it enables you to store some of the excess solar that you generate in the middle of the day and discharge it to meet demand even after the sunsets. So even though this doesn't quite replace the truly dispatchable resources like nuclear and natural gas, it does I think, make solar a more relevant and durable part of this future of power when you have data centers added into the demand profile.

Now, on the other hand for wind, we do think that wind generation will continue to grow in the coming years. Wind does face some more unique challenges versus solar. They face more issues with permitting, with zoning, with regulatory, federal regulatory pushback, along with a host of other issues.

So, I think the bottom line on renewables is this, there is going to be more renewables in our future power generation. We think more of it is going to come from solar than from wind. We think battery backed solar has an increasingly big role to play in powering data center projects as we go forward and just as it always has been, renewables will continue to work in this really close partnership. Dispatchable resources like natural gas to ensure that we have the scalability, reliability, and affordability that we have today as we expand our overall power infrastructure.

Oscar Pulido: it really sounds like you have to look in a lot of different directions for these power sources. We've talked about natural gas, you've, you've compared solar and wind, but it sounds like both are going to be part of the equation.

We haven't talked about nuclear. Last time we spoke, you had mentioned that. There were nuclear power plants that had been closed that were starting to reopen as, as we saw this sort of underlying change in the economy causing power demand to pick up. So, what's the story on nuclear now? More recently?

Will Su: Yeah. So, Oscar nuclear restarts have been a favorite among Hyperscaler customers for meeting their data centers since the last time that we spoke.

The hyperscalers prefer nuclear power for two clear reasons. Number one, they bring a reliable power load that sits behind the meter and is available 24/ 7 /365. Number two, they're an emission free power source. So really the best of both worlds. That's the good news. The bad news is on a go forward basis, we have sold out of these low hanging fruits of nuclear restarts. So, the new the nuclear story going forward is really going to have to deal around investing in and building new greenfield nuclear generating plants, and it's not going to be a walk in the park here in America today.

 as of today, there is not a single utility scale nuclear reactor being constructed in the United States. I do think there are some green shoots here. Some utilities have started to move nuclear projects back into its resource space, which is a very early phase before you decide to invest in a project.

But I think the harsh truth is we don't expect to see a new utility scale reactor being built in the states for the next decade. But there's many, there's a lot of reasons to be optimistic here.

 The Department of Energy has set a very ambitious goal to triple America's nuclear capacity by 2050.

So, all of this makes me really optimistic that nuclear is going to have this key long-term role to play and expanding our power infrastructure to power AI in a way that is also carbon free and also fully dispatchable to ensure reliability.

Oscar Pulido: So, Will, we've covered a lot of ground here. We've talked about the demand for energy that is going to be created as AI becomes more pervasive across our day-to-day. You mentioned natural gas. We talked about nuclear, solar, and wind, but I just want to come back to you for a second. You're a fundamental analyst. You come to work and you're looking at companies and you're trying to determine where to invest, what companies, what sectors, what industries, how has ai impacted the way you go about doing your role and the way you go about doing fundamental investing.

Will Su: Oscar, I think AI for me has really become an increasing part of my daily life. But as an investor, like you said, I think one of the key questions that I've always had is, look, we accept at this point that AI is increasingly intelligent and highly efficient. The real question and the million-dollar question really is it any good at investing and trading in the real world?

we're in luck because there's data for this. So, there is a live-stock trading competition hosted on LLM Stats. In that competition, only one out of 16 AI models is actually currently making money, 15 out of 16 unprofitable. On a separate trading competition that's hosted on Alpha Arena, again, only one out of eight AI models being tested has made money on average. So not the most impressive results so far.

And my hypothesis for this really is AI as a standalone model is not nearly as powerful or profitable as an experienced investor who can leverage that AI to improve their investment and research and risk management processes. And this combination of man and machine is really, in my view, what's going to define investment talent in the years to come.

When you combine the scale efficiency and speed of AI with the deeply knowledgeable investors that bring decades of experience, deep industry knowledge through the different economic cycles and their irreplaceable human connections in the real world. That is a secret to delivering better investment outcomes and more value to our clients and investors in the future as we march into this world of AI ahead of us.

Oscar Pulido: Will, you've done it again. You've given us a lot of great things to think about. You talked about power is knowledge, which I thought was, really memorable. You mentioned BYOP, bring your own power, which is something that builders of data centers have to think about. And you also gave us a lot of terminology that we'll have to go back and look at around the sheer quantities of power demand that are being created. But we appreciate you sharing an update on where we are with the AI and energy story, and we appreciate you doing it here on The Bid.

Will Su: Thanks for having me, Oscar. Look forward to part three of our conversation in the future.

Oscar Pulido: Thanks for listening to this episode of the Bid. Next week I'm joined by Lisa Yang to talk about the K-shaped economy. What behavior investors can expect from the US consumer.

<<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. In the UK and Non-European Economic Area countries, this is authorized and regulated by the Financial Conduct Authority. In the European Economic Area, this is authorized and regulated by the Netherlands Authority for the Financial Markets. For full disclosures, visit blackrock.com/corporate/compliance/bid-disclosures.

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230. AI At The Frontier – A Stock Picker’s Take on Tech and AI investing

Episode Description:

The world of artificial intelligence continues to profoundly impact the stock markets and create investment opportunities. Despite a brief setback earlier this year, AI continues to push the boundaries of human ingenuity and drive market dynamics.

Oscar Pulido welcomes Tony Kim, head of the BlackRock Fundamental Equities Global Technology Team, and Michael Gates, lead portfolio manager of BlackRock's target allocation models. Fresh from their interactions with technology leaders in San Francisco and Silicon Valley, Tony and Michael share their insights on the rapid advancements in AI, the efficiencies it brings to the economy, and the promising investment opportunities it unveils across various sectors.

AI, AI Investing, Tech Investing, Technology Investing, Silicon Valley, Tech,

Sources: AI Scaling Laws and Market Structure, Anton Korinek, Professor of Economics, University of Virginia; Bloomberg data as of June 31^st 2025; The Complex Truth About AI Computing and Value, Wall Street Journal, March 2^nd 2025; Analysis based on BlackRock Global Technology evaluations and calculations; BlackRock and World Bank Group Data, World Bank estimates GDP around $111 trillion, Capital expenditure on AI infrastructure is estimated at around $400 bn.

Written disclosures in each podcast platform and each 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 the names of each company mentioned in this communication is merely for explaining the investment strategy and should not be construed as investment advice or investment recommendation of those companies.

For full disclosures go to Blackrock.com/corporate/compliance/bid-disclosures

<<THEME MUSIC>>

<<TRANSCRIPT>>

Oscar Pulido: Artificial intelligence continues to claim the spotlight and test the limits of human ingenuity. And even after a brief setback early in the year, it continues to drive stock markets. As the technology evolves, so do the investment opportunities. So, where do the greatest prospects reside now and what are the risks?

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 Tony Kim, head of the BlackRock Fundamental Equities Global Technology Team, and Michael Gates, lead portfolio manager of BlackRock's target allocation models. Tony and Michael recently spent time with technology leaders across San Francisco and Silicon Valley, and today they reflect on the rapid pace of progress, the efficiencies AI is creating across the economy and the investment opportunities it is revealing across various sectors of the market.

Tony and Michael, thank you much for joining us on The Bid.

Tony Kim: Thank you. It's a pleasure to be here.

Michael Gates: Thanks, Oscar.

Oscar Pulido: Tony, this is one of our favorite episodes to do over the course of a year because this is where we talk about that tech tour where you take more than 30 BlackRock colleagues around Silicon Valley and San Francisco. In fact, I think you travel more than 300 miles over the course of five days to meet with the leaders of approximately 25 technology companies. So, it sounds like a busy week, and this is the 12th annual tech tour that you've hosted. When we talked about this tour last year, you mentioned that AI was really not much of a topic of discussion for the first nine years of that tour, but that that had started to change and that it became a very prominent topic of the tour. There's obviously been a lot of development in the AI space since we last spoke. So, tell us about those conversations that you had with industry leaders. How has it changed over the past year?

Tony Kim: Yeah, last year it was all about AI, but it was chatbots, the origins of agents. And this year, it was all about AI, but it was AI, what I would call at the frontier, at the edge of what is possible. Really, it's around super intelligence. So, we keep ratcheting up the capabilities of what these AI systems can do and we were looking at AI companies in the full stack, from everything from the infrastructure and the compute to the models, to the applications and now the extensions of AI into the physical world. It's still all about AI, but the scope has expanded materially.

Oscar Pulido: And that term ‘AI at the frontier’ does make it sound like a lot has changed in the past year and that it is more pervasive across different applications and the use case. One of the things that we did this year, again, Tony, is that The Bid team joined you on your tech tour and we were able to get some clips from some of the industry leaders that you met with. And so, on that topic of the rapid pace of change that we're seeing in AI, we want to hear from Jitendra Mohan, CEO and co-founder of Astera Labs.

Jitendra Mohan: The rate of change for AI is insane. It is the fastest pace of innovation that I've seen in my lifetime, arguably in anybody's lifetime. If you look at a couple of years ago, we had the ChatGPT movement and ChatGPT was impressive and magical, but it was still a novelty at the time. And look at where we are today: AI is writing code, AI is finding bugs, these models are able to do reasoning. And I'm pretty sure that there is a virtual AI agent or a physical AI robot in our near future.

Oscar Pulido: Tony, last year when we spoke we also talked about this concept of the technology stack. This is how you described sort of the investment opportunity set and you talked about these as three different layers of investment opportunities. At the bottom you said are the chips and the infrastructure, the middle stack is the AI intelligence layer, and then the top stack are the AI models, the software applications themselves. There's been a lot of, again, attention and focus on the infrastructure — that bottom foundational layer. So, things like semiconductors and data centers is what comes to mind. Is this still the primary investment opportunity or are the investment opportunities now branching out to some other stacks within that, in that foundation?

Tony Kim: This is a great question. I think this is the best way to interrogate AI. If we just look at these three layers: the compute and infrastructure, the intelligence and the models, and then the applications and services.

And so at the bottom of this stack, just the top spenders of physical CapEx is nearly half a trillion dollars this year. It will grow to trillion or more in the coming years. Just to put in context, the global GDP is $100 trillion, so just AI infrastructure is already 0.5%. This is just pure chip and data center investment, is already at half a percent of global GDP. This is the largest investment in human history. We're just in the early stages at that layer, and this continues. And the reason this continues, these are AI factories effectively, they then birth the intelligence. It is created based on how much compute you have. And this intelligence layer they are growing at exponential capabilities - 10 x or more of improvements per year tied to how much compute investment. The world has realized that if you have more compute, we get more intelligence. And so, this is this inexorable linkage between the compute layer and the intelligence layer, and that is giving birth to ever increasingly capable AI systems.

And so, those two are getting the lion's share of the investment, and we're seeing growth that we've never seen before. Companies like OpenAI and Anthropic are growing multiples faster than even Google at the dawn of the internet age. So, we are seeing, as Jitendra mentioned, growth that we've never seen before and the rate of change.

And then at the top layer is what I call the applications layer. And before I was really thinking about the software applications, and I think this is going to change dramatically because the AI will be writing the applications. But I would add one more piece. These AI systems will not just be software applications, but it will be merging software and labor and services together. And so, what we thought were these distinct industries, the capabilities of these AI systems will subsume into the application layer and the service layer. And the service layer is over roughly half or more of the global GDP. And so now you're starting to see the scope and scale of what is potentially coming with these advanced AI systems — it is expanding to bigger and bigger parts of the global GDP.

Oscar Pulido: That was the word that was going through my mind is the scale you mentioned $500 billion in terms of the investment, what it represents as a percentage of global GDP. You touched on some of the companies these days that are growing very fast and how that compares to technology companies of a few decades ago, and just the rate of change being so quick.

We want to hear from another one of the executives that you encountered on this tech tour. This is Sasan Goodarzi, the CEO of Intuit, who sees AI as a tool that could allow customers more time to focus on their real passions.

Sasan Goodarzi: Are there big hard problems that we can solve in ways where a customer never has to lift a finger in running their business, but do all of their finger lifting in what they're passionate about. And that's why I'm so excited about what's possible with AI. I believe it will ignite global innovation in ways that we could never imagine possible, and I can't wait for it to power prosperity in ways that we could never imagine.

Oscar Pulido: So Michael, I want to bring you into the discussion. You were on this tech tour. You're also an active manager. You're managing portfolios and having to make decisions about what to own and what not to own. As someone who invests so broadly across asset classes and sectors, why is it important for you to have a view on technology?

Michael Gates: Well, let's level set a little bit about what's been happening fundamentally for the kinds of companies that are in the public indexes. US Tech over the last 15 years, sales growth rate has been 8% per year compound annual growth rate for the last 15 years, since 2010. If you look at the US market overall, the sales growth rate has been 5%. If you look outside the US, you see growth rates between positive 0.5% and negative 0.5%. Within the US, the IT sector has delivered 50% better earnings growth over the last 15 years at a compound annual rate.

So the ability to beat and raise is something we look for, and where we're finding it is in tech. And within tech where we're finding it is in those companies that are exposed to the AI theme.

Oscar Pulido: Tony, I'd like to come back to you on this topic of AI at the frontier and how much it's evolving. There's a lot of discussion around how AI may supplement human labor in the future, from large language models to all the way to things like humanoids. And so what is your view on this, are we going to see humanoids play a role in our lives anytime soon?

Tony Kim: AI at the frontier, I love this terminology. What we're seeing is this rate of change, an unprecedented rate of change. And humans we're used to linear kinds of change. Growth at 5%, 10%. And what's happening here with AI, we are seeing change at the chip level 2x a year, and we're seeing change at the model intelligence layer 10x a year. So that's like a 20x potential improvement in capabilities, if you take the chip and the model improvements — could be 10x, 20x — but we're seeing this exponential scaling of capability.

So, if we see this kind of non-linear exponential change, and then you compound that one year, two years, three years, four years, you are soon in the thousands of X improvement in just a few years. So, if this rate of change continues between now and let's say 2030, which is just four to five years away, we could see thousands of X capability improvement. So, if we believe that to be the case, and this is AI at the frontier, it is hard to imagine what that means for society. And because the capabilities are improving at this kind of rate, absolutely, yes, you could take the embodiment of this capability and put it into a physical form of a humanoid robot.

Today, I would characterize humanoid robot as the capabilities of a three- or four-year-old child. In two years, it could be a teenager, but in five years we could have very capable, functioning humanoid systems. So, I would say if this is the question on humanoid a little bit, there are the two forms. It's the brain, which is that intelligence capability. And then the physical system of the robot, the mechanical parts. You'll see dramatic improvements on both sides. And so, I think you could get to a point where you could really see that happen before the end of this decade.

Oscar Pulido: And I think the point you mentioned about we're used to linear change and AI really is an example of non-linear change. It's exponential change and it's probably why we spend so much time talking about it as a mega force and a structural driver of returns in the future.

Michael, to come back to you in terms of then the investment opportunity there, there's so much nuance to this space. There's a lot of different winners and losers potentially to come out of the AI revolution. We've seen the dominance of the Magnificent 7 in the US market in particular. But again, how do you think about the role of active management when it comes to this AI theme?

Michael Gates: I keep my eye on the ball in terms of what, is, are the most important indications of financial and economic health. And one of the things we've learned, is that looking at the process of earnings and sales estimate revisions is a really good way to figure out how's it going.

You often get this comment of, oh gosh, the US market's so concentrated, the big companies are such a big part of the index. And that's true, they are a big part. But you might ask the question, is this market concentrated enough? Turn it on its head. And I'll tell you what, if you look at the estimate revisions for the broad index or sectors, what you often find is that there's a subset of companies that are generating really great positive surprises on earnings and sales, and then getting the subsequent positive revisions to their earnings expectations. And that tends to be the largest companies.

Tony Kim: If I were to add to Michael's comments, he is expressing one of my core tenets and observations that I've noticed about the tech sector, what I call a power law. It's not a law, it's an observation. The big get bigger, the winners win, as long as there is tailwind behind these companies. And so, you do see underestimation of the winners just continue to win and win big unless there is some sort of structural change into their competitive position.

And that's what's also fueling these big winners in AI is because there's another element here of AI, which is very unusual, it requires so much capital to play the game.

Oscar Pulido: It's also fair to say, I think we're talking about the concentration of a few companies that have really dominated, but AI as a theme can also then bleed into sectors outside of technology.

And speaking of some of these other industries, Tony, last year when we spoke to you about your tech tour, you you brought up the topic of quantum computing, which maybe was not on the tip of everybody's tongue the way AI seems to be in the last couple of years. And in July, you actually spoke on an investor panel at the Global Quantum Forum in Chicago where they dubbed 2025 as the year of quantum. So you've been an early champion of this technology. What do people need to know about quantum computing, its relationship to AI, and where are we in this journey?

Tony Kim: Yeah, absolutely, great question. Classical computing, which is the Intel, Nvidia, this has been the hallmark of the technology industry for 50 plus years. It just so happens we are now at the dawn of a second computing platform, which was classical computing CPUs and GPUs for 50 years, and that continues. And all of this AI is still based on, as we know, the Nvidia GPU kind of architecture. But these are classical computing architectures for the digital world. I have the opportunity in my career to potentially invest in the second computing platform that will sit adjacent to classical computing, which is quantum computing. Like AI, like fusion, like many other things, these are long, long in development, but we are now at the potential dawn of a utility scale quantum computer.

And what does this do? To just put it simply, it is a completely different computing system that basically computes nature. Nature is based on quantum mechanics at a subatomic level. This is a different kind of computer that can compute the natural world at the subatomic level, which is very different than the digital AI, AGI, classical systems that were driving us to AGI. But this new computing system will sit adjacent to AI systems and it will solve different kinds of problems that we could never solve before with a classical computer. And the output of this new computer is profoundly different and insights to nature, chemistry, biology, drugs, materials, encryption that we've never been able to calculate before, will create new kinds of data.

And then that not only unlocks new discoveries, but it also creates data to help train the AGI system to become even more intelligent. So there is this symbiotic relationship; they don't compete with each other. It just, it's a very different kind of computer. A computer for nature versus the computer of the digital world. And we are at the dawn of this. You mentioned earlier to me about humanoids by 2030, which I think will happen. I think we'll also have quantum computing come onto the scene in a major way also between now and 2030. So again, these next four to five years, it is going to be an epic time of innovation and breakthrough.

Oscar Pulido: It reinforces the point of, this is not linear change, but something unlike what we've seen in the past. We should touch on that, the fact that AI does come with some concerns and we talked about labor and things like humanoids and what that could disrupt in terms of what we know today, but there's also the issue of privacy and security. So I want to go back to our executives that we met throughout the tech tour. We're going to hear from Michael Sentonas, the President of CrowdStrike, which is on the front lines of the effort to provide security, protect privacy as AI grows increasingly sophisticated, and here's what he had to say.

Mike Sentonas: We now live in a world where we are using more and more AI technology in our everyday lives. We're also seeing the attackers get the same sorts of benefits. So we're in this race effectively to build technology, to defend against attacks, to defend and prevent attackers compromising organizations, and attackers that are motivated for financial gain. And we're using this technology to build better systems, better models to prevent these attacks.

Oscar Pulido: So Tony, how are governments and enterprises addressing this and, where's the investment opportunity in this?

Tony Kim: So, cyber is forever here to stay. Before we were addressing human-derived actors using classical techniques to, to try to attack and breach. So now we introduce a super intelligence or a very advanced intelligence. They can write, the AIs can write code, and you will have, let's say millions and billions of AIs that can then create an inexorable rise of attack vectors. And so not only before were we just combating human bad actors, we are now, they can then weaponize themselves using AI-generated cyber vectors. Again, it's a non-linear exponential increase in attack surfaces.

Yet, on the other hand, we could use the AI to help defend against the AI attacking us, and they will be far in excess of what human attackers will be. And so there will be this constant cat and mouse battle of one upmanship of using AI to attack and using AI to defend. This will never go away. In fact, if anything, it becomes even more of an imperative. And so, therefore, the question about governments and companies and I think they're all grappling with this issue — this arms race of weaponizing these AI systems for attack and for defense. And I think that is the direction of travel for the cyber industry.

Oscar Pulido: Michael, this was your first time joining the tech tour. What was your top observation from this marathon week?

Michael Gates: I was really impressed with some of the companies. What was evident to me was was with respect to a couple very important companies in the AI space, they've been anticipating where we are today for years. And they saw that we would be where we are today, which I think many of us find very surprising. They saw this a couple years ago and they are looking to two years ahead. And what they are seeing for two years ahead is really mind blowing.

If you just take it as a fact that they saw what is today a couple years ago and planned accordingly to profit from that development, then you listen to them talk about what is coming in the next couple years and then listen to the indications of what their plans are and the kinds of investments that are happening to make those plans come to being.

Oscar Pulido: And thinking about fast forwarding and what's coming, Tony, if we're having, or I should say, when we have this conversation in September 2026 and we're talking about at that point your 13^th annual tech tour, what will we be talking about then in terms of AI and the developments that we've seen at that point?

Tony Kim: I would say we'll have much more conversations, I believe, around this idea of the super intelligence. Are we closer to physical intelligence as an embodiment in physical systems? That will become more of a topic. And then thirdly, I think you mentioned it, societal impact. What is the societal impact and how the face of work changes, how will it change how we work and these ideas, while they're talking about a little bit, I don't know if the mainstream realizes the potential axiom of change that is potentially coming to that part, the societal impact on how we are doing work, and these questions will be, I think, more at the forefront next year.

Oscar Pulido: I already know that's going to be a fascinating episode to listen to as hopefully this one has been as well, just to hear what's going on in the center of the tech world and what's going on with AI. Just listening to the two of you, it feels like so much has changed in the last couple years, but it's also evident there's so much more change coming and we'll look forward to hearing from both of you what that change looks like.

Tony and Michael, thank you so much for sharing your views on AI and the tech tour and thank you for doing it here on The Bid.

Tony Kim: Thanks, Oscar. It's been great to be here.

Michael Gates: Thanks for having me.

Oscar Pulido: If you enjoyed this episode, check out The Intersection of AI and Geopolitics From An Investing Lens where we discuss how rapid advances in AI are influencing global power dynamics. And don't forget to subscribe to The Bid wherever you get your podcasts.

<<THEME MUSIC>>

Spoken disclosures at end of each episode:

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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