The Next AI Millionaire Makers: 3 Stocks Set to Become Tomorrow‘s Tech Giants

In 1996, I bought Apple in my own account. Four years later, the dot-com bubble burst. The Nasdaq went on to lose more than 75% of its value. 

I didn‘t sell. Not because I was stubborn… 

By 2000, 52% of American adults were online. The internet had gone mainstream, and that changed where the money would be made. 

The problem was, the companies that built the internet had been priced as if their breakneck growth could last forever. It couldn‘t. Lucent’s stock lost 99% of its value. Cisco fell 89% from its peak, and investors who bought at the top waited more than 20 years just to get back to even. 

Apple went the other way. 

All those new internet users created a giant new market for iTunes, the iPod, and later the iPhone. Since 2001, the stock has soared more than 150,000%, with dividends reinvested. 

I call this the Pioneer’s Paradox. When a breakthrough technology goes mainstream, the technology keeps spreading. But the pioneers can’t grow fast enough to meet Wall Street’s expectations. The biggest gains move to a new group of companies whose opportunity gets bigger as adoption spreads. 

We saw it with radio around 1930, television in the mid-1950s, personal computers in 2000, and smartphones after 2012. 

Now we’re seeing it with AI. 

AI Just Crossed the Threshold 

Economists at the Federal Reserve Bank of St. Louis, Harvard, and Vanderbilt have been tracking how many working-age Americans use generative AI. In May 2026, the figure hit 61.8%. Yet ChatGPT didn’t launch until November 2022. 

That means AI has gone mainstream faster than the personal computer, the internet, or the smartphone. 

And just as the Pioneer’s Paradox predicts, Wall Street has started sorting the winners from the losers. In June alone, the Magnificent Seven lost about $2.3 trillion in market value. On July 31, J.P. Morgan described money rotating away from crowded AI trades while the broader bull market stayed intact. 

I believe AI will be the most transformational technology of our lifetime. But I want my money in companies whose biggest growth is still ahead of them. 

That’s why I ran all AI stocks through the five tests I’ve used to find my biggest winners in the past. 

Each company must be a leader in cutting-edge technology. It must sell breakthrough products used on a massive scale. Its technology must be protected by patents, trademarks, or brand names. It must show massive sales growth. And it must have blockbuster catalysts ahead that can drive the stock higher. 

Very few companies pass all five. The three in this report do. 

Can they become millionaire makers? No one can promise that. But each one sits today where an earlier giant sat before its biggest run. 

AI’s Missing Link 

Powerful AI models require thousands of chips to function – sometimes hundreds of thousands – working together like one giant brain. Every chip has to talk to the others at blinding speed. One bad connection, and thousands of chips can sit idle, burning through expensive computing time. 

Credo Technology Group Holding Ltd. (Nasdaq: CRDO) has built the technology that makes this possible. 

Its flagship product is the active electrical cable, or AEC. Think of it as a copper cable with a brain. Ordinary copper cables lose signal strength after a few feet. Credo builds its own signal-processing chips – tiny processors that clean up and boost the data – right into the connectors. The result moves data at enormous speed, uses far less power than fiber optics, and is much more reliable. 

Credo’s cables are bright purple – and the company has registered the color as a trademark. That brand recognition pays off… 

The cables showed up in Elon Musk’s photos from inside Colossus 2, his AI supercomputer in Memphis. They showed up in Amazon Web Services CEO Matt Garman’s photo of Amazon’s AI chip racks. Meta displayed them on an Nvidia rack at a major industry show. 

Nvidia makes the brains of AI. Credo connects them. 

Credo doesn’t name its customers. But analysts at BNP Paribas believe they likely include Amazon, Microsoft, Meta, Oracle, and xAI. 

Seven Straight Quarters of Doubling 

In the first quarter of fiscal 2027, which ended August 1, sales hit a record $479 million. That’s up 115% from a year earlier. It was the seventh straight quarter that sales more than doubled year over year. Adjusted net income soared 140% to $236 million. 

Management guided to $525 million to $535 million in sales for the current quarter – nearly double the $268 million Credo brought in a year ago. For the full fiscal year, it expects growth of more than 85%. 

Every time a data center adds chips, it needs more connections. As AI clusters get bigger, Credo’s market gets bigger right along with them. Last December, management said its market would top $10 billion in the coming years – more than triple its estimate 18 months earlier. Credo brought in $1.34 billion in fiscal 2026. It has barely scratched the surface. 

The next engine is optics. Management expects more than $600 million in optical sales this fiscal year, spread across three product lines that should each top $100 million. 

We’ve seen a company in exactly this spot before. In 2014, the cloud giants needed a faster way to move data between servers. Arista Networks solved it. By 2016, two years after going public, Arista was bringing in about $1.1 billion a year – close to where Credo was last year. A $10,000 investment in Arista at the start of 2016 would be worth more than $350,000 today. 

Arista solved the bottleneck for the cloud. Credo is solving it for AI. And I believe AI data centers will prove far hungrier for connections than anything the cloud ever built. 

On my checklist, Credo goes five for five. It pioneered the AEC. Its customers are the biggest AI builders on Earth. Its AEC patents have teeth: Amphenol and Volex settled infringement claims, and 3M and Siemon now license them. Sales are up 115%. And its fast-growing optical business, plus next-generation 1.6-terabit products, can provide fresh catalysts for future growth. 

Of course, Credo won’t have this market to itself forever. On a recent analyst call, MaxLinear CEO Kishore Seendripu estimated that Credo holds 93% to 99% of it today. But he argued that the market is starting to diversify as the technology gets more complex. 

Not to mention the stock has had a volatile year. And customer concentration could prove to be a problem. The largest customer accounted for 33% of sales last quarter, and the second-largest for 28%. 

A company that owns nearly all of its market should expect rivals. The question is whether Credo wins the next generation. Optical sales in Credo’s next quarterly report, expected around the start of December, are the first test. 

What I’d Pay – and What Would Make Me Sell 

Say Credo reaches $4 billion in sales by fiscal 2029 – roughly 40% of that $10 billion market – and keeps 45 cents of every sales dollar as adjusted profit. (It kept 49 cents last quarter.) I estimate that works out to about $9 a share in earnings. At 35 times earnings, the stock would trade near $315, roughly double today’s price. 

I’d change my mind if Credo lost a top-two customer’s next-generation build to a rival, or if sales growth slowed below 30% before the optical business took off. But in the meantime, it’s in a solid position to blast higher. 

Recommendation: Buy Credo Technology Group Holding Ltd. (Nasdaq: CRDO) at market. While this should be considered a long-term position, some Members may prefer to use a 25% trailing stop to protect their principal and profits. 

The Oracle of the AI Age 

As AI gains traction, every business is asking the same question: How do we put it to work to enhance our own operations? 

It starts with data. To be effective, AI must know about a company’s customers, sales, and inventory. 

Snowflake Inc. (NYSE: SNOW) stores that data for many of the world’s largest companies. And a growing number now use Snowflake to put AI to work. More than 14,500 companies use Snowflake, including Capital One, AT&T, and Pfizer. So do 829 of the 2,000 largest companies on Earth. 

The leading AI labs are on board. In December 2025, Anthropic signed a $200 million partnership to put its Claude models directly inside Snowflake’s platform. Two months later, OpenAI signed a $200 million partnership of its own. OpenAI also uses Snowflake to run its own analytics and testing. 

Customers pay for what they use, much like a utility. And Snowflake put AI on the same meter. So every time a company points AI at its data, Snowflake earns more. 

Momentum Is Building 

In the second quarter of fiscal 2027, which ended July 31, product revenue jumped 37% to $1.49 billion. That’s the third straight quarter of faster growth. 

Snowflake added more new product revenue in those three months than in any quarter in its history – $158 million – and it was the second straight record. CEO Sridhar Ramaswamy said roughly half of the acceleration in sales came from AI products. The other half came from those AI products pulling more of the core business along with them. 

Existing customers spent 26% more than they did a year earlier. And management raised its full-year forecast to $6.07 billion, up from $5.84 billion just one quarter before. 

The runway is long. Snowflake’s CFO puts its market at $225 billion today, more than doubling to over $460 billion within five years. With this year’s sales on track for about $6 billion, Snowflake has tapped less than 3% of the total addressable market. And 1,171 of the world’s 2,000 largest companies still aren’t customers. 

Oracle sat in this same spot in 1997, with about $5.7 billion in sales. A $10,000 investment at the start of that year would be worth more than $250,000 today. 

On my checklist, it’s five for five: a leader in AI-ready data, more than 14,500 customers, more than 1,050 U.S. patents, 37% growth and accelerating, and AI partnerships just starting to pay off. 

Snowflake isn’t profitable yet under standard accounting rules. Last quarter, it posted a $263 million operating loss, largely because stock-based pay and related costs ate up 29% of revenue. Management is targeting a profit in the fourth quarter of fiscal 2028. 

It faces a fast-growing rival too. As SaaStr founder Jason Lemkin pointed out, Databricks recently announced $7 billion in annual revenue, representing growth of more than 80%. 

But Snowflake’s record quarter was fueled mostly by big customers spending more – not what you see when customers are leaving. 

Now, Snowflake did lower its full-year product gross margin forecast to 74% because AI workloads cost more to deliver. But it raised its full-year adjusted operating margin forecast at the same time. In other words, it’s covering the extra AI costs by running the rest of the business more efficiently. 

What I’d Pay – and What Would Make Me Sell 

Say growth cools to 30% a year. Product revenue would top $17 billion by fiscal 2031. At 12 times sales – roughly half today’s multiple – I estimate Snowflake would be worth about $200 billion, or about $565 a share. That’s about 70% above today’s price. 

I’d change my mind if existing customers’ spending growth fell below 15% a year, or if management pushed back its profit target. 

Recommendation: Buy Snowflake Inc. (NYSE: SNOW) at market. While this should be considered a long-term position, some Members may prefer to use a 25% trailing stop to protect their principal and profits. 

AI’s Hidden Monopoly 

Every AI chip starts as a blank disc of silicon called a wafer. To turn it into chips, you have to print billions of tiny circuits onto it. 

For the most advanced chips, only one kind of machine can do it. It’s called an extreme ultraviolet, or EUV, lithography system. It prints circuits using light with an extremely short wavelength. Each system is about the size of a school bus. Standard models cost around $250 million, and the newest High-NA version runs about $380 million. 

Only one company in the world can build it: ASML Holding NV (Nasdaq: ASML). 

Nvidia, Apple, Google, and Amazon are racing to design the best AI chips. Those chips are made by Taiwan Semiconductor, Samsung, and Intel – on ASML’s machines. So every one of those giants depends on this Dutch company. 

ASML began serious EUV development in 2001. It took nearly 20 years and billions of dollars to reach full production. Nikon and Canon abandoned their own EUV efforts years ago. China has reportedly built a prototype using parts from older ASML machines and former ASML engineers, but it hasn’t produced working chips. 

And ASML doesn’t get paid just once. Its machines run around the clock, and chipmakers pay ASML to service and upgrade them for years. That business brought in €3.3 billion in the third quarter alone. 

Business Is Booming 

Back in January, ASML expected 2026 sales of €34 billion to €39 billion. It raised that forecast in April, then again in July. On October 14, it narrowed the range to €44 billion to €45 billion, or roughly $50 billion. 

The third quarter was a record. Sales hit €11.7 billion, and net income reached €5.0 billion, or about $5.6 billion. That figure includes a gain of about €0.5 billion from a higher valuation of its stake in AI startup Mistral. 

CEO Christophe Fouquet said ASML now expects that its planned supply for both 2027 and 2028 will not fully meet customer demand. ASML plans to add 30% to EUV capacity in 2027. 

In November 2024, ASML told investors it expected €44 billion to €60 billion in sales by 2030. Based on its current forecast, it’s on track to hit the low end this year – four years early. And Bernstein, one of Wall Street’s top research firms, projects ASML could reach €80 billion, or about $90 billion, by 2030. That’s nearly double this year’s forecast. 

To see what that growth can do, look at Applied Materials. It makes many of the other machines inside a chip factory. By 2016, it was already the world’s biggest chip-equipment maker, with more than $10 billion in annual sales. Yet every time the world needed a better chip, chipmakers came back for new machines. An investment of $10,000 in Applied Materials at the start of 2016 would be worth more than $200,000 today, with dividends reinvested. 

ASML gets paid the same way. Only this time, nobody else can build the machines. 

And just like the other two stocks in this report, ASML is five for five on my checklist. It’s the only company that builds EUV machines. Nearly every advanced chip relies on it. Its patent portfolio runs to tens of thousands of patents and applications. It has raised its forecast twice this year. And price increases arriving in 2027, with the full effect hitting in 2028, should provide a boost in revenue. 

On the downside, ASML isn’t cheap. It trades at about 40 times earnings, and the stock fell after its record third quarter. 

And while management expects system purchases from memory chipmakers to jump about 75% in 2026, it’s forecasting only a 10% increase for logic chipmakers. Memory spending has always run in booms and busts. And China is expected to account for about 20% of ASML’s sales this year, which leaves it exposed to export restrictions. 

What I’d Pay – and What Would Make Me Sell 

Bernstein projects that ASML will earn €97 a share in 2030. If it gets there and the stock trades at 35 times earnings – below today’s multiple – it would be worth about €3,400, or roughly $3,800 a share. That’s more than twice today’s price. 

I’d change my mind if a rival began producing advanced chips at scale on a competing EUV machine, or if ASML cut its outlook because customers pulled back on spending. 

Recommendation: Buy ASML Holding NV (Nasdaq: ASML) at market. While this should be considered a long-term position, some Members may prefer to use a 25% trailing stop to protect their principal and profits. 

On the Right Side of the Sorting 

These three companies share one trait. The bigger AI gets, the bigger their opportunity becomes. Credo connects more chips. Snowflake meters more AI work. ASML prints more advanced circuits. 

None of them will rise in a straight line. So build your positions over time, and never invest more than you can afford to lose. 

But I’ve seen this pattern before. In 2000, the internet didn’t stop growing. The opportunity simply shifted. The investors who moved with it did very well. 

The same sorting is underway with AI right now – with these three companies all capable of leading its next phase.