Editor's note: As the AI revolution rages on, companies around the world are aiming to keep up with this transformative technology's ravenous appetite for data.
That's why Luke Lango – senior analyst for our corporate affiliate InvestorPlace – stresses that investors must look beyond flashy AI stocks to focus on the companies powering this trend.
In today's Masters Series, Luke details how you can maximize gains throughout this AI revolution by keying in on the "infrastructure behind the infrastructure"...
AI Can't Run Without This
Every major tech revolution follows the same rhythm. And when you know that rhythm, you know where to look to build your wealth.
The headlines focus on the innovators – Apple (AAPL), Tesla (TSLA), OpenAI, and the like.
But the biggest fortunes often end up in the hands of the suppliers – the companies that provide the foundation that makes everything work.
During the rise of PCs, Intel (INTC) and Microsoft (MSFT) became giants supplying chips and software.
During the electric-vehicle ("EV") boom, battery makers and lithium suppliers saw their stocks soar.
And now, as AI enters its infrastructure phase, the same pattern is repeating itself.
By mid-2024, investors had fixated on the flashy AI names. But the deeper I looked, the clearer it became...
The real money isn't only in who builds AI. It's in what AI runs on. So, we focused on pick-and-shovel plays – the infrastructure behind the infrastructure.
This year alone, America's five largest cloud operators – Alphabet (GOOGL), Amazon (AMZN), Apple, Meta Platforms (META), and Microsoft – are on track to spend over $400 billion building AI infrastructure. That's more than double what they spent just two years ago.
They're not dabbling. They're building the data centers, compute clusters, and storage systems that will power AI for decades to come.
The pattern is clear: When industries transform, foundational suppliers often capture the outsized gains.
Right now, one of AI's fastest-growing foundational layers is data storage. Every model, neural network, and inference engine needs capacity. As demand for high-capacity drives explodes, that bottleneck becomes a profit generator.
And that led us to one stock.
This quiet enabler of the AI revolution has become one of the sector's biggest beneficiaries.
Since our initial recommendation in August 2024, it's up about 150%... one of the top-performing stocks this year.
Today, we'll identify the stock, why the storage supercycle is real, and how to potentially amplify those gains with a unique short-term strategy we're set to debut...
AI runs on chips, but it feeds on data. All that data has to be stored. Our featured company wins because it sells the high-capacity storage hyperscalers need. It isn't on consumer labels, but it's inside the build-out.
As generative AI scaled, hyperscalers rushed to store training data, model checkpoints, embeddings, logs, and newly generated content. The compute arms race created a new bottleneck: bulk storage.
Zooming out to Seagate Technology (STX)...
- Big Tech has launched an unprecedented AI capex spree to stand up supercomputers and data centers.
- Modern AI data centers operate at exabyte ("EB") scale – with 1 EB equating to 1,000 petabytes ("PB"). OpenAI reportedly scoped multi-EB deployments, and Meta operates EB-scale infrastructure.
- Industry voices are calling it a "data storage supercycle."
Yet, the supply side of storage is essentially a duopoly: Seagate and its chief rival, Western Digital (WDC), produce nearly 90% of the world's hard drive storage capacity combined.
With AI's appetite for data growing faster every quarter, these two companies find themselves with enormous pricing power.
Modern AI training routinely operates at hundreds of terabytes ("TB") to petabytes of data. Nvidia (NVDA) notes that computer-vision training datasets can easily exceed 30 terabytes.
Open large language model ("LLM") datasets such as RedPajama require around 260 TB. The Common Crawl corpus used in many LLMs spans multiple PBs. And Meta stores AI training data on EB infrastructure.
Every new AI model – from ChatGPT to the next-generation image generators now popping up – requires an unprecedented surge in storage capacity. This is the unseen backbone of the AI economy, and it's being built right now.
So, why Seagate?
The truth is, when it comes to high-capacity storage, Seagate is it.
The company has a decadeslong track record in hard disk drive ("HDD") innovation and holds a 40%-plus share of the global HDD market.
More importantly, hard drives remain indispensable for AI infrastructure. Despite the rise of flash memory, about 90% of the EBs stored in the world's largest data centers reside on hard drives. That's due to the cost advantage for bulk storage that HDDs offer.
For AI workloads that involve huge datasets where top speed isn't the primary need (think storing training data, archives, backups, etc.), HDDs are the only economically feasible choice. In fact, roughly 90% of enterprise "EB scale" tasks – like AI data retention and analytics – rely on hard drives.
We have a scenario where demand is skyrocketing, and the supply (hard drives) is controlled by just a few players who are already running near full tilt.
It's Economics 101: surging demand combined with constrained supply equals improving fundamentals for the suppliers.
That makes adding Seagate to your buy list a no-brainer.
However, identifying a stock in a great multiyear trend is just one way to win. There's another approach that can take a stock like Seagate and boost its returns exponentially in the short term.
For that part of the story, let me introduce my colleague who specializes in squeezing the maximum profit from exactly these kinds of situations...
Jonathan Rose is a veteran Wall Street trader with a remarkable track record of navigating these same megatrends – but in a completely different way.
While I focus on long-term exponential growth stories – companies like Seagate that can multiply over the next decade – Jonathan has developed a trading approach designed to amplify gains in those same trends in a matter of weeks.
He's proven it time and again. This year alone, using this trading strategy, Jonathan has identified trades like 959% on Albemarle (ALB), 534% on MP Materials (MP), and 233% on Rigetti Computing (RGTI) – all tied to the same themes driving AI infrastructure and next-generation technology.
In short, we see the same opportunities. But where I spot the rockets, Jonathan sets up the boosters.
It's not often that a stock shows up on both my radar and Jonathan's at the same time. Typically, my focus is on the multiyear horizon – the fundamental trend – while Jonathan zeroes in on short-term momentum and money flows (he calls it "unusual Wall Street activity"). But when those two approaches converge on the same stock, it's a special situation.
That's why I'm so excited about Seagate – not just as a long-term AI infrastructure play, but as a setup that Jonathan's system could amplify.
I'm holding Seagate for the AI data supercycle: the multiyear wave of growth that will reshape how digital infrastructure is built. Meanwhile, Jonathan is trading the waves inside that cycle and leveraging his system to capture shorter bursts of opportunity within the same trend.
Same story. Different time frames.
If Seagate's 150% climb got your attention, imagine learning how to turn that into a 750% gain.
That's the power of combining my megatrend picks with Jonathan's timely trade execution...
Sincerely,
Luke Lango
Editor's note: To help investors execute this dual playbook, Jonathan and Luke are teaming up for an online presentation on November 10 to show you a smarter way to trade picks like these for potentially far bigger gains.
During this event, Jonathan will pull back the curtain on his trading system and show how he finds this unusual Wall Street activity early. And he'll walk through how his strategy could amplify the returns on stocks like Seagate by 500% or more.
And just for attending, you'll get access to three exclusive stock picks – top recommendations from Luke, legendary growth investor Louis Navellier, and global macro expert Eric Fry. Click here to get the full details...