AI Investing in 2026: The Next Phase of Artificial Intelligence
In a Nutshell
AI is shifting from a tech-sector story to a real-economy force, with enterprise adoption, robotics, and healthcare applications now driving investment returns. Physical bottlenecks—chips, refining capacity for copper/lithium/nickel, and electricity demand—are creating new supply constraints and opportunities in materials, power, and infrastructure. The decisive winners will be the companies that convert AI into measurable economic gains rather than those merely spending on the technology.
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When you hear AI, what do you picture? Chips, chatbots, Big Tech? That was part of the first chapter. But the next chapter of AI could look very different in our daily lives, from autonomous vehicles to how doctors screen for disease, maybe even data centers in space. Welcome to the AI economy. The AI is moving beyond the technology sector and deeper into the real economy. We think that that changes where investors should be looking.
For the last few years, much of the AI story has been about building the technology. Now we're starting to see another question matter. Who can actually put AI to work? Enterprise AI is gaining traction and not only where you might expect. Legal and medical administration, industries that have historically been slower to adopt new technology, are among the larger enterprise use cases outside of coding. That matters, because the next phase of AI may not reward every company equally. Simply spending on AI is one thing, turning it into better business outcomes is another.
But there's another side to this story. AI may feel digital, building it is extremely physical. Starting with chips, AI demand can accelerate quickly. Semiconductor supply cannot. Adding new memory chip capacity can take three to four years or more. And the broader buildout requires more than semiconductors. Data centers, power systems, energy storage, and the industrial infrastructure around them draw on a wide range of critical materials.
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