Slower growth and hotter inflation … where AI goes next … the dirty secret of AI … the best picks and shovels approach … two stocks to consider today
The big news this morning was the weak U.S. gross domestic product report.
The Bureau of Economic Analysis reported that the U.S. economy expanded at just 1.6% in the first quarter, well below the Dow Jones forecast of 2.4%.
Beyond the underwhelming growth rate, the report showed that consumer prices rose at 3.4%. This crushed Q4’s price increase of 1.8%.
This is yet another nail in the coffin for the “multiple interest rate cut” narrative that has helped prop up the markets this year. And in fact, the CME Group’s FedWatch Tool is now putting majority odds on just one rate cut in 2024.
It wasn’t that long ago that traders were confident we’d have seven quarter-point interest rate cuts!
As you’d expect, the markets are a sea of red in the wake of the news as I write mid-afternoon. At least they’re off their lows of the session.
The second issue roiling stocks this morning is the 10-year Treasury yield. It’s jumped to 4.70% (it was at 4.73% earlier this morning). This is the highest level since November 2 of last year.
We’ll dive into this treasury yield in greater detail tomorrow. But for now, let’s use today’s selloff as an opportunity to put some potential investments on your radar.
After all, if this morning’s disappointing economic data tips the market into a significant correction, it would likely present some great buying opportunity for long-term investors.
Let’s get prepared.
We’ll begin with peek at what’s right around the corner with Artificial Intelligence
Let’s go straight to the April issue of AI Revolution (for newer Digest readers, this is a service featuring the top AI picks from our three experts, Louis Navellier, Eric Fry, and Luke Lango):
The next big thing in AI is coming this year… and they’re called AI agents.
AI agents are “smart” AI applications that can perceive their environment and act accordingly…
In short, AI agents extend what AI chatbots can do. They have the potential to be personal assistants… travel agents… educators… DJs… and will play thousands of other roles we haven’t yet dreamed of.
To get a sense for what this really looks like practically speaking, let’s turn to none other than Bill Gates, creator of Microsoft.
From Gates’ online blog, GatesNotes:
Imagine that you want to plan a trip.
A travel bot will identify hotels that fit your budget. An agent will know what time of year you’ll be traveling and, based on its knowledge about whether you always try a new destination or like to return to the same place repeatedly, it will be able to suggest locations.
When asked, it will recommend things to do based on your interests and propensity for adventure, and it will book reservations at the types of restaurants you would enjoy…
Agents won’t simply make recommendations; they’ll help you act on them.
If you want to buy a camera, you’ll have your agent read all the reviews for you, summarize them, make a recommendation, and place an order for it once you’ve made a decision.
If you tell your agent that you want to watch Star Wars, it will know whether you’re subscribed to the right streaming service, and if you aren’t, it will offer to sign you up.
And if you don’t know what you’re in the mood for, it will make customized suggestions and then figure out how to play the movie or show you choose.
Now, whether you read this and feel a warm rush of utopian excitement or an icy blast of dystopian dread, the question for us is the same…
How can we benefit from an investment perspective?
To answer that, let’s begin more broadly…
Artificial Intelligence has a dirty little secret
It’s not profitable.
Behind all the excitement about how AI will change our world and simplify our day-to-day lives, at the moment, it’s a money pit.
From The Wall Street Journal last fall:
Tech companies are touting new AI technology that can spit out business memos or computer code. They are still figuring out how those products will generate a profit.
Generative artificial-intelligence tools are unproven and expensive to operate, requiring muscular servers with expensive chips that consume lots of power. Microsoft, Google, Adobe and other tech companies investing in AI are experimenting with an array of tactics to make, market and charge for it.
Microsoft has lost money on one of its first generative AI products, said a person with knowledge of the figures.
Part of the problem with the economics of AI is that it’s not as scalable as traditional software.
Unlike, say, Microsoft Excel, AI software often requires intense calculations for each new query. This adds to the ongoing cost of maintaining AI software programs.
So, as more customers use AI products, the more expensive the infrastructure costs become for the company behind that AI offering.
The problem doesn’t just relate to the cost of developing and running these programs. We’re so early in the AI adoption curve that consumer demand isn’t there yet.
As just one illustration, about a year ago, Pew Research found that only 14% of U.S. adults had tried ChatGPT. Though that number has certainly climbed since then, it surely isn’t yet reflecting use by most Americans.
Here’s Forbes with some numbers on customer use and how it impacts ROI, specifically with AI’s enterprise initiatives:
Only 32% of data scientists said their models are usually deployed, according to one survey. That’s a massive waste of time and resources.
That waste is reflected in the average ROI on enterprise AI initiatives, which recent IBM research revealed to be an unimpressive 5.9%. That’s well below the typical 10% cost of capital. It’s no wonder that many businesses find AI implementation frustrating and unrewarding.
Now, Big Tech will eventually find a way to bring these costs down. But as we stand today, picking tomorrow’s most profitable AI product (and by extension, stock) is little more than a gamble.
Is there a better way to invest today?
Absolutely.
The low-hanging fruit of AI investing
During the great American Gold Rush of the late 1840s and early 1850s, approximately 300,000 people migrated to California in hopes of striking it rich.
A few got lucky and became overnight success stories. But the overwhelming majority of these individuals went broke.
Meanwhile, do you know who made the first million dollars during the Gold Rush?
It wasn’t a gold miner – it was Sam Brannan, the owner of a general store who sold the mining equipment that all the would-be millionaires needed as they sought their gold fortunes.
This anecdote is what gives rise to the investment phrase “a picks and shovels play.”
Why take the risky route of trying to strike gold when you get take the more conservative path, growing incrementally wealthier by supplying critical infrastructure to all the gamblers out there.
So, how do we do this with AI?
Well, there are a handful of ways, but let’s zero in on just one in today’s Digest…
Data centers.
The coming tsunami of AI products requires the same thing – data processing
We don’t know who will come out on top as the preeminent AI company, but we do know one thing…
Every AI company that’s in the running for that title will require huge volumes of processing power, data storage, and energy. So, why not invest there?
Here’s how our technology expert and the editor of Early Stage Investor, Luke Lango, put it earlier this year:
Data centers [are required] to expand cloud computing capacity to be sufficient to handle numerous advanced AI applications…
Of course, this data center construction boom will also benefit domestic engineering, construction, and building materials firms. But the bigger plays here will be found in the providers of critical data center components, like networking equipment, cooling equipment, virtualization software, and more.
These companies should benefit massively from a domestic data center construction boom.
And this comes from Globest.com:
The rapid expansion of U.S. data center capacity to support the demand for artificial intelligence will double the size of the industry by 2030, measured in gigawatts…
The surge in power consumption will be driven by an industry-wide upgrade to data center campuses that are being rebuilt or newly developed to meet the huge data processing demands of AI and its cousin, machine learning (ML), the report said.
So, how might you play it?
If you Google “top data center stocks,” you’ll get a number of names to begin your research, including:
- Equinix
- Nvidia
- Fortinet
- AMD
- Arista
But I’ll give you two options directly from our experts.
The first pick comes from Eric Fry, editor of Investment Report and The Speculator. He has been urging his readers to invest in IBM for many months now.
In fact, back in January, Speculator subscribers closed out a portion of their IBM trade for nearly 300% gains. Then about a week later, they took profits on a second IBM trade for 450% gains.
From Eric’s analysis from last fall:
IBM has been reinventing itself as a hybrid cloud and artificial intelligence company. To accelerate this transformation, the company has been pursuing an out-with-old-in-with-the-new growth strategy.
Since 2019, IBM has divested 17 legacy businesses, while also making more than 30 acquisitions…
Because IBM’s fast-growing AI and hybrid cloud businesses will power most of its future growth, I expect the company to become a dominant leader of the AI boom.
Though IBM has rewarded investors handsomely over the last year, its role as an AI data center leader should provide snowballing profits (and a climbing share price) for years to come.
I’ll add that IBM is down 8% as I write in the wake of the company’s earnings release this morning. While earnings topped estimates, revenues were slightly lower than expected
Based on today’s news, Eric is recommending his Speculator subscribers lock in gains of roughly 240% on their final portion of their IBM trade.
To be clear, the long-term case for IBM’s AI/data center leadership remains. Eric’s “close” recommendation is more a reflection of a market veteran deciding to protect big profits in a trade. We’ll let you know if Eric’s long-term analysis of IBM changes materially.
Our second play comes from Luke Lango in his Early Stage Investor service. It’s the data center company, Vertiv. This is a more targeted play than IBM.
It turns out Vertiv announced earnings yesterday that provide a fantastic illustration of the snowballing demand for data centers.
From Vertiv’s press release:
First quarter 2024 organic orders up 60% compared to first quarter 2023, book-to-bill ratio 1.5x in first quarter 2024 and record high $6.3 billion backlog at the end of first quarter 2024…
Vertiv’s stock spiked as much as 19% during yesterday’s session in the wake of the news. And as I write today, with the broad market tanking, Vertiv is up another 8%.
Luke’s Early Stage Investor subscribers got in roughly two months ago. They’re up 49%, but if Luke’s right, this is just a taste of the gains that Vertiv will produce over the coming years.
IBM’s path should be smoother than Vertiv’s, but the potential upside is likely greater in Vertiv than IBM (IBM’s market cap is more than 5X the size of Vertiv’s, so it’ll be harder to move the needle there).
Wrapping up, yes, AI is going to change everything…
But for most businesses, making money off AI right now isn’t clear or easy.
As investors, we can make it clearer and easier by focusing on where the growth is happening, and the money is flowing, right now. And that points us in one direction…
Data centers.
We’ll keep you updated.
Have a good evening,
Jeff Remsburg
