The AI Buildout Is Just Getting Started
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What significant growth did token consumption experience last year?
token consumption last year grew 17 times. Not 17%, which I think most people would view as a pretty good growth company, 17 times growth of token consumption. Essentially, as much money as the major large language model providers are plowing into capital expenditures, they can't keep up with AI demand. So even just in the last several months, I think the narrative has shifted in the market from that of Are we worried companies are over-investing in capex, to what if companies are actually under-investing in capex?
That was BlackRock's U.S. head of equity ETFs, Jay Jacobs, breaking down what the data actually says about AI's growth trajectory. I'm Motley Fool analyst Rachel Warren. I sat down with Jay to dig into BlackRock's newly released 2026 thematic outlook, covering everything from the AI infrastructure build-out to tokenization to what retail investors should be doing with their portfolios right now. Enjoy. Hello, everyone, and welcome back to Motley Fool Conversations. I'm Motley Fool analyst Rachel Warren, and today I'm excited to welcome Jay Jacobs, the U.S. head of equity ETFs at BlackRock, to the show. Jay oversees the overall product strategy, thought leadership, and client engagement for the firm's index and active equity ETF business.
Prior to his current role, Jay founded and led GlobalX ETF's research and strategy team and previously served as a business analyst at the New York Stock Exchange, where he helped launch hundreds of ETFs on the NYSE ARCA trading platform. Today, we're going to be diving deep into the massive structural shifts shaping the global economy. with BlackRock's newly released 2026 Thematic Outlook, which details how the next leg of AI compute is colliding with physical power grid bottlenecks, surging sovereign defense spending, and a massive wave of real-world asset tokenization. Jay, welcome to the show.
Thanks for having me on.
So as U.S. head of equity ETFs, from your standpoint, I would love to hear your thoughts on how the view of a traditional portfolio has changed now that thematic funds have grown over 11x just in the past decade.
Well, I think it's important to recognize portfolio management techniques have always been evolving as the world has evolved, as data and software has evolved to make portfolios be able to be managed in different ways and assess risk and opportunities in different ways. So you go back to some of the factor research in the 1970s, the introduction of the style box in the early 90s, the GIC sector classifications that divvied up the world into different sectors in the late 90s. There's been a constant evolution of portfolio management. And what we're seeing is one of the latest evolutions is really increasingly investors are looking at the world through a thematic lens. They see the rise of artificial intelligence, the changing demographics, the changing energy needs, the future of finance, as well as geopolitical fragmentation all being major forces that are reshaping how they can think about risks and opportunities in their portfolio.
And as they assess those risks, they increasingly see how valuable thematic ETFs can be for fine-tuning their exposure to these themes in their portfolios.
Well, one of the things I wanted to talk about, your internal model portfolios hit a 7.5% allocation, but the average moderate U.S. advisor model sits at just 3.6% thematic exposure. And your data actually shows that about 12% of analyzed U.S. advisor portfolios currently hold any thematic ETFs at all. So I wonder if you could talk through maybe what's causing this gap. And does this mean that, you know, sometimes we're seeing an under allocation to structural growth?
I would say there is an under allocation or the way that people are getting exposure to these growth opportunities is through not always the most precise tools. I do think a lot of people out there think they're getting exposure to AI by allocating to the technology sector. And in some ways you are. Yes, the technology sector has exposure to names that are building large language models or building some of the important hardware that goes into data centers.
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