Unless you’ve been living under a rock, you’ve at least heard about generative artificial intelligence (AI) products such as ChatGPT.
These programs have a lot of uses. They can serve as brainstorming partners or catalysts for the discussion of new ideas… generate first drafts for writing projects… process and summarize documents… repurpose content so it can be used for different audiences… accelerate your learning in areas you’re not familiar with… guide business processes… accelerate coding… and develop conversational support bots… to name just a few.
Looking at those examples, you can see that the uses of generative AI are far wider – and much more beneficial – than just having ChatGPT finish a school paper or write your friends funny emails in the voice of a famous author.
To give you an idea of how widespread AI already is and how much room it still has to expand, consider that while 9 out of 10 leading businesses are already invested in AI technologies, only 14.6% have deployed AI capabilities in their operations.
That means there is still an enormous adoption rate on the horizon – and that’s creating a huge opportunity.
But here’s the problem…
Nearly every company in the S&P 500 is talking about AI.
And not all of them will hit the bull’s-eye.
There are specific plays that will pay off… if you know where to look.
I like to think of AI as being similar to the California gold rush. Most prospectors never struck it rich, but they did spend a lot of money on tools, supplies and clothing – and that generated huge profits for companies like Levi Strauss.
What are the pick-and-shovel companies of AI?
Your first guess would likely be the semiconductor chip manufacturers that provide the processing power for generating results. You can’t have AI without them. I’m talking about names like Nvidia, Advanced Micro Devices and Intel.
But there’s an even better pick-and-shovel play…
Semiconductor chips are of no use until they are deployed in a machine that can put them to work.
The most basic “tools” of the whole AI revolution are the large-scale data centers that are the physical epicenters of the AI ecosystem.
Purpose-built AI data centers are facilities composed of networked computers, storage systems and computing infrastructure that leverage AI chips. They can run multiple computations at once as AI applications sift through enormous stores of data.
These AI-specific data centers require massive investments in terms of capital and time. So the companies that have already begun transitioning their infrastructure to meet the demands of AI have a huge first-mover advantage over their competitors – and a large moat.
Because of the growing demand, spending in the global AI infrastructure market (which includes data centers) is expected to reach $422.55 billion by 2029, growing at a compound annual rate of 44% over the next six years, according to research firm Data Bridge Market Research.
My favorite way to play data centers is Equinix (Nasdaq: EQIX), one of the largest data center operators in the world. It has 251 data centers… across 70 metro areas… in 32 countries… on six continents.
Its portfolio of data center assets includes…
- Network dense: 2,000-plus networks; 100% of Tier 1 network routes
- Cloud dense: 3,000-plus cloud and IT service providers
- Interconnected ecosystems: 460,000-plus total interconnections.
That’s an impressive portfolio… and it’s boosting the company’s financials.
Going back to 2000, the company has increased annual revenue every single year. It went from just $13.02 million in 2000 to $7.26 billion in 2022. And over the trailing 12 months, revenue has increased once again, coming in at $7.95 billion.
Most recently, the company reported third quarter results that included revenue of $2.06 billion, of which $1.96 billion was reoccurring revenue.
On the bottom line, net income for the third quarter was $276 million, which represented a year-over-year increase of 30%.
And here’s the best part…
Equinix not only is tied to one of the fastest-growing industries in the world and generates consistently increasing revenue… but it has also posted eight years of cash dividend growth since converting to a real estate investment trust in 2015.
Speaking of the dividend, the company recently increased its fourth quarter dividend to $4.26 per share, a 25% bump from the third quarter.
On an annual basis, the company will pay out $14.49 per share in 2023, a 19% year-over-year increase.
I like Equinix’s prospects as a solid AI pick-and-shovel play with plenty of growth and income ahead of it.
It’s a surefire way to profit from the AI boom as adoption takes off.