Nvidia (NVDA) has been one of the greatest investments of my lifetime.

It went from a relatively obscure semiconductor company to the face of the artificial intelligence revolution, creating trillions of dollars in market value along the way. Microsoft (MSFT), Alphabet (GOOG), Amazon (AMZN), and Meta (META) have also become some of the largest companies on Earth as investors bet on their roles in the AI boom.

I still believe many of these companies have bright futures. But there’s a simple mathematical problem that investors need to understand.

The bigger a company gets, the harder it becomes to double.

Think about a company worth $3 trillion. For its stock to double, investors need to create another $3 trillion of market value.

Now consider a $10 billion company. It only needs to add another $10 billion to double.

That doesn’t mean the $10 billion company is automatically the better investment. Smaller companies come with greater risks, and plenty of them will fail. But the math helps explain why some of the biggest percentage gains during the next stage of the AI boom could come from companies that are much smaller than today’s technology giants.

Moving Down the Food Chain

This fits perfectly with what I’ve been writing about this week.

On Monday, I explained why I believe AI is entering its second act. Yesterday, we looked at another unusual opportunity developing around some of the world’s largest private AI companies.

Today, I want to move farther down the food chain.

As AI spreads throughout the economy, trillions of dollars will be spent on more than GPUs and giant language models. AI needs data centers, networking equipment, power, cooling, and storage. It needs sensors that allow machines to interact with the physical world. And it needs software that can take all that intelligence and turn it into something businesses and consumers will actually pay for.

That’s where smaller companies can get interesting.

Take Applied Digital (APLD). It’s building large-scale data centers designed for AI and high-performance computing. The company generated $611 million in revenue in its latest fiscal year, up 167%, as its first major HPC facility began contributing to the business.

Then there’s Lumentum (LITE). It makes optical technologies that help move enormous amounts of data around AI data centers. Its fiscal 2026 revenue jumped 83% to more than $3 billion, and management says increasing AI workloads are pushing data centers toward faster optical connections.

But the opportunities aren’t limited to data centers.

Ouster (OUST) makes lidar and perception technology that gives robots, autonomous vehicles, and industrial machines the ability to understand their surroundings. Its second-quarter revenue jumped 56% from a year ago, while shipments topped 17,000 lidar and camera sensors. Its technology is already being used in warehouse automation, transportation, and other physical-AI applications.

And there’s another company in my newest report that shows how AI can create opportunities far away from traditional technology companies. This fintech uses its proprietary underwriting engine to help determine how much money customers can safely borrow. Revenue increased 30% in the latest quarter, while adjusted EBITDA jumped 48%.

That new report is only available to members of The McCall Innovation Report… If you’re not yet one, watching my new presentation on the biggest IPO in history could seriously benefit you. Click here to check it out.

Four very different companies. Four very different ways to participate in AI.

And that’s the point.

You Don’t Need the Next Nvidia

Investors love asking me, “What’s the next Nvidia?”

I think that’s the wrong question.

Nvidia became Nvidia because it was positioned at exactly the right place as a massive technological shift took off. The next huge AI winner may not manufacture GPUs at all. It could build data centers, connect servers, give robots vision, discover drugs, automate factories, or use AI to completely reinvent an old industry.

That’s what happened during the internet boom. The first wave created enormous winners in networking equipment and computers. But the internet eventually spread into advertising, retail, entertainment, payments, software, and almost every other corner of the economy.

AI is beginning that same journey.

And this is where market capitalization becomes so important. A $3 trillion company can still be a fantastic investment. But the law of large numbers is working against it. A smaller company that finds itself at the center of a rapidly expanding AI market has a much longer runway in front of it.

Of course, that works both ways. Smaller stocks can fall much faster, too, which is why I don’t buy something simply because it’s small and has “AI” somewhere in its investor presentation. I want real revenue growth, a real business, and exposure to a trend that could become substantially larger over the next several years.

That’s where I’ll increasingly be looking as this AI boom matures.

The first stage of AI created several trillion-dollar giants. The second stage could be about finding the companies that have the potential to grow into the next generation of market leaders.

P.S. Today I talked about finding companies before they grow into giants. The frustrating part is that some of the biggest growth stories of this era have done most of their growing in the private market, where everyday investors can’t get in.

That may be about to change in a big way. I just put together a new presentation on what could be the biggest IPO in history… and how you can get in on it before the crowd piles in. If you watched the first stage of the AI boom from the sidelines, this is one you’ll want to see.

Click here to watch it now.