The next wave could come from companies that the biggest AI players eventually decide they should own…
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Editor’s note: In 2012, Mark Zuckerberg paid $1 billion for a photo app for 13 people, had no revenue, and by most accounts, no real business model. Wall Street called it the worst deal of the year.
A decade later, Instagram alone generated tens of billions of dollars in revenue, and the people who made the most profits never bought a share of Meta stock. They owned part of Instagram long before Zuckerberg arrived.
my colleague Luke Langoa technology and growth specialist at InvestorPlace, believes the same pattern is repeating itself across the AI boom — but on a much larger scale.
So, for today Smart moneyI invited Luke to track where Silicon Valley’s biggest AI labs are pouring their money, and he shows that the fortunes to come won’t go to companies building AI, but to smaller players that the giants can’t afford to compete with. Luke will go over the full framework — as well as a specific company he thinks fits the style — along the way Free online event this Thursday, July 30 at 1pm EST. Reserve your seat here.
In May 2023, Spark Capital It made the largest investment in its history.
The venture capital firm wrote a seed check for $75 million to help with the financing Anthropica little-known AI startup with no stock symbol, almost no revenue, and no way for ordinary investors to buy.
There was no Wall Street research report telling investors what this deal was worth. There were no earnings estimates.
After three years, the value of the Spark stake appreciates 7 billion dollars On paper.
One investment. Almost 100 times the return.
Spark Capital needed only one human figure. History suggests that investors often don’t need much, either.
I keep coming back to that story because I believe it marks the beginning of the current AI investment cycle. Investors like Spark have provided capital that has helped companies like Anthropic grow into some of the most valuable companies in the world.
But this cycle is already changing.
And companies that were startups just a few years ago are quickly becoming giants: Anthropic, OpenAI, and others. along with Microsoft Corporation (MSFT), Alphabet Company (Google), Amazon.com Inc. (Amzn), Meta Platforms Inc. (dead)and Nvidia company (NVDA)They are raising—and spending—enormous sums of money, racing to build what they believe will become the next great computing platform.
However, sooner or later, they will find that they cannot invent everything themselves. No company — not even nearly trillion-dollar AI labs — can hire every brilliant engineer or invent every breakthrough first.
In short, I believe we are entering the next phase of the AI boom.
The first phase rewarded investors who realized that AI infrastructure—chips, memory, networks, power, and data centers—would become essential. I still think many of these companies have room to run.
But the next stage may look very different.
Instead of asking, “Which companies are going to build AI?” Investors may soon need to ask, “Which companies will the big AI players decide to own?”
If I’m right, the answer to this question could make the difference between simply participating in the AI revolution… and getting there before the rest of Wall Street catches up.
This is what I want to show you today.
First, I’ll explain why I believe the AI arms race is entering a new phase.
Then I’ll show you how Silicon Valley’s biggest companies are flipping their hands long before they announce the next blockbuster acquisition.
Finally, I’ll explain the framework I’ve begun to use to identify the types of companies I think could become the biggest winners in the future, whether they eventually go public or are bought out first.
Let’s start tracking the money…
Follow the money
One of the first rules I learned as an investor is that money leaves clues. When hundreds of billions of dollars start flowing in the same direction, I take notice.
Right now, it’s not just money flowing to Nvidia.
It flows into the entire AI ecosystem.
Follow the money.
Amazon alone expects strong inflow 200 billion dollars in capital projects this year. Both Microsoft and Alphabet are planning 190 billion dollars. Meta could spend another $135 billion.
This is almost 700 billion dollars In one year, or about $2 billion every day.
This is an arms race.
Meanwhile, Anthropic’s recent funding valued the company at nearly 100%. $965 billion. OpenAI is said to be worth approx 852 billion dollars.
But even when companies have that much money, they can’t invent everything themselves. Call it Silicon Valley’s dirty little secret: It’s often faster to buy innovation than to build it yourself.
Think about what these companies are trying to achieve.
Leading AI companies believe they are building the next computing platform. When the risks get that high, companies stop asking: “Can we build this?” And start asking, “Who already has it?”
We’ve seen this movie before.
In 2012, Facebook Paid $1 billion for Instagram. At the time, it seemed ridiculous.
Instagram only had 13 employees. It wasn’t making money. Most people thought Mark Zuckerberg overpaid for a photo-sharing app that allowed people to put vintage-looking filters on photos of their lunch.
It turns out that Zuckerberg got the deal of the century. Instagram has since become one of the most valuable companies in Meta. Last year, Meta estimated Instagram’s brand value at more than $70 billion, and said it generates annual revenue of about $67 billion.
But that’s not what I find most interesting.
The biggest winners weren’t the people who bought Meta shares after the Instagram deal was announced. They were the people who actually owned part of Instagram before Zuckerberg came along.
This pattern has continued throughout the past few technical breakthroughs:
Google bought Android before smartphones were ubiquitous and acquired YouTube before online video dominated the media.
Facebook bought Instagram and WhatsApp before those companies reached their full potential.
Microsoft acquired GitHub as software development becomes increasingly collaborative and cloud-based.
Notice the pattern. None of these companies were acquired because the buyers were running out of money. They were acquired because buyers were running out of time.
I think AI is creating a similar dynamic, but on a much larger scale.
The indicator is no longer the starting line
For decades, most investors have assumed that the stock market is where great companies start.
Increasingly, it is the place where they end the first chapter.
Think about it Space Exploration Technologies Company (Spex).
Millions of investors finally had the opportunity to buy shares after the IPO. But by then, SpaceX had spent years building rockets, launching satellites, signing government contracts, and creating enormous value.
Within weeks of its IPO, its shares had fallen well below its high of $202.50 — on top of its original offering price of $135.
If you participated on day one, you were part of the largest IPO in history. But the momentous occasion did not prevent you from falling into a painful withdrawal.
Investors who entered years ago were playing a completely different game. They bought at private valuations well below those received by public investors on IPO day. So a modest change in the overall stock price means something completely different for these two groups.
Two people can believe in the same company equally and come out with radically different results.
That’s why I recently started asking: Which companies will become so important that an AI giant decides it can’t compete against them?
Some of these companies will become the next generation of AI leaders. Others may receive buy offers long before the opening bell rings on Wall Street.
Either path can create tremendous value.
The challenge is to identify these companies early.
Over the past year, I’ve built a completely different framework for finding those opportunities.
It’s not about chasing any trending stock on social media. It is not based on guessing tomorrow’s headlines. Instead, it is based on following the money.
I examine where Silicon Valley is investing, what capabilities the largest AI companies still lack, and what small companies are working on problems that the giants may eventually decide they need to have.
It’s a different research process and a completely different way of looking at the AI boom.
And honestly, I think it’s one of the most exciting parts of this entire course.
History tells us that during technological revolutions, headlines always focus on the giants.
But the greatest fortunes are often a layer or two below them.
Back in 2023, Spark Capital saw something in Anthropy that most of the world couldn’t see. This decision may become one of the defining investments of the age of artificial intelligence.
I believe the next chapter of AI could produce similar opportunities — because every technology revolution creates a new generation of companies that solve problems that giants can’t solve alone.
My goal is not to find another Anthropist. It’s finding Anthropic companies and the rest decide they can’t ignore it.
This is what I will show you Thursday, July 30 at 1pm EST. On that day, I’ll walk you through this framework during a free online event I’ll be hosting 2026 AI Megadeal Event. (You can reserve your place here.)
I’ll cover a few things during this event.
- Why I think the AI investment cycle is entering a completely new phase.
- The framework I use to identify companies that can become tomorrow’s AI leaders—or tomorrow’s acquisition targets.
- I think one particular opportunity shows exactly how this next phase could unfold.
The first phase of the AI boom rewarded companies working to build the future. I think the second phase could reward the companies that these contractors decide they need to own.
I will show you how to find them. The event is free. All you have to do is Reserve your seat here In order to get an invite (plus my bonus report: “AI Collector’s Portfolio: 7 Stocks to Buy for the Biggest Tech Spending Surge Ever.”)
I hope you’ll join me.
sincerely,
Luke Lango
Senior investment analyst, Investor location
