The One Unshakable Truth Behind AI

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Investors face constant, nearly irresistible temptations for promising investment stories that haven’t yet borne fruit.

Pie-in-the-sky promises that wind up less impactful than anticipated, or even just take a long time to reach mass-market appeal, are what bubbles in premature tech are made of. (See the past bubbles in blockchain, 3D printing, and the then-unproven internet of the late ’90s for evidence.)

I get the temptation. Because many of those narratives mint millionaires. Still, we must be wary of stories.

Now, I’m about to say something potentially controversial.

The elephant-in-the-room investment narrative, right now, is AI.

Many folks are convinced that AI is here to stay, and with good reason. Already, it’s seen a lot of useful applications, like digital twin testing. ChatGPT, having reached 180 million users in just over a year, speaks for itself.

Still, it’s uncertain just how much AI is set to disrupt. Can it really replace 2.4 million U.S. jobs by 2030, as research firm Forrester predicts? Will it really boost GDP by nearly 15% by the same time, as PwC estimates?

It might… but we should never invest on hopes and projections alone.

So what can we do?

Focus on the certainties.

If AI is here to stay — and it probably is — what can we count on happening?

Well, for one, we can count on AI consuming a tremendous amount of energy. Data centers, some of which house AI models, already consume an estimated 1% of the world’s energy.

And that’s just getting started. AI is forecast to grow its energy consumption alongside its adoption, with one report expecting it to consume more than some small countries by 2027.

So if AI is already consuming so much energy… And is set to consume more… It tracks that we should have exposure to energy technologies that are positioned to meet AI’s growing demand.

Today, we’ll look at the current energy situation with AI — and some possible solutions.

And I’ll share one critical energy technology that’s woefully underinvested but is clearly the trade to make.

What Powers AI?

To understand the AI energy picture, it’s helpful to zoom out and think about what AI really is.

The best analog for AI today is cloud computing, which is simply racks upon racks of powerful computers whose power we can access remotely through the internet.

AI is powered much the same way: in data centers full of computers running AI algorithms. That’s why semiconductor companies, like Nvidia and AMD, caught such a tremendous bid last year. Any company that makes market-leading computer chips is in a great position to take advantage of the AI trend.

Computer chips are one side of the equation… And there are plenty of trades to make there — especially in companies that flash one of the most important buy signals in the market. 

But energy is the other, equally important side that’s yet to see nearly as much interest. AI is set to demand more energy than any technology that came before, bar none. Even right now, it’s a more energy-intensive technology than what it’s working on replacing.

OpenAI found last year that a Google Search query consumes an estimated 0.0003 kWh (kilowatt hours) of electricity. A query with ChatGPT consumes anywhere from 0.001 to 0.01 kWh of electricity — or anywhere from 3 to 33 times more.

Granted, Google is still pulling many times more queries a day than ChatGPT, but the search giant is only growing at about 10% per year. AI is growing much faster. 

ChatGPT alone reached 100 million users in less than a year. It took YouTube, Facebook, and Twitter more than four years to do that. Netflix took more than 10 years to reach 100 million users. 

The point is, this is a big shift… and that’s just ChatGPT. There are dozens of other generative AI tools out there sucking up energy.

And even this isn’t counting the AI capacity set to come online. Consider that Nvidia plans to ship 1.5 million dedicated AI servers in 2025. 

And the fact that Alex de Vries, a researcher at the VU Amsterdam School of Business and Economics, estimated all the new servers would demand more than 85 terawatt hours of energy annually. That’s more than some small countries.

His research also estimated that on the whole, global data center energy demand could jump 50% by 2027.

These are projections, just like the projections about job losses and GDP boosts. But an unshakable truth about AI, regardless of how it’s used in the future, is that it consumes a ton of energy.

And with the push from world governments to shift away from fossil fuels and toward renewables, we can be sure that these AI data centers won’t be powered exclusively by coal-fired plants and oil pipelines.

We need to focus on the technologies that can provide clean energy at a global scale.

And if you’ve been following along with TradeSmith Daily, you’re already well ahead of the crowd.

The Nuclear, Green, AI Future

Add AI to the growing pile of reasons why you should invest in nuclear energy stocks:

1. They’re still woefully misunderstood, with a bad PR problem despite being cleaner and safer than coal, oil, natural gas, and even wind turbines…
2. They’re showing the first strong uptrend in decades…
3. Even though they’re up 47.9% year-to-date (versus 17.1% for the S&P 500), the sector is still comparatively cheap (19.3 vs. 29.4)… 

But don’t just take my word on this. The preeminent mind in AI, OpenAI CEO Sam Altman, is saying the same thing.

Here he is speaking at the World Economic Forum in Davos, Switzerland, in January:

“There’s no way to get there without a breakthrough,” he said. “It motivates us to go invest more in fusion.”

And Reuters noted:

In 2021, Altman personally provided $375 million to private U.S. nuclear fusion company Helion Energy, which since has signed a deal to provide energy to Microsoft in future years. Microsoft is OpenAI’s biggest financial backer and provides it computing resources for AI.

Altman said he wished the world would embrace nuclear fission as an energy source as well.

The guy who brought ChatGPT to the world is saying we need more nuclear energy capacity and is directly investing in nuclear energy himself.

It’s no wonder that uranium, the commodity underlying nuclear energy stocks, has been on an absolute tear.

I’ve been tracking this chart of uranium against oil, natural gas, and coal futures (below).

You can see that uranium continues to leave fossil fuels in its dust. Oil, coal, and natural gas have all barely treaded water in 2024; in fact, they’re down hard since 2022 – while uranium has nearly doubled.

Long story short, you need to have nuclear energy stocks in your AI investment plan, right alongside high-quality semiconductor companies.

As far as I know, there is no better speculation on the future of not just AI, but the global energy story, period.

The easiest way to do this is with the Global X Uranium ETF (URA), which holds a basket of energy companies. This ETF will give you broad exposure to the trend.

But if you want to find the best stocks, that’s where TradeSmith’s best-in-industry tools come in.

One of the easiest ways to find high-quality stocks in any trend, sector, or market is with Ratings by TradeSmith.

With a few taps of your keyboard, you can immediately see if a stock is worth your investment dollars… or one to avoid entirely.

For example, here’s the rating for Cameco (CCJ), the largest publicly traded uranium company. 

Cameco earns a Strong Bullish Rating at 83, making it a prime target for anyone looking to invest in the nuclear energy trend. And you can do this with any nuclear stock in the URA ETF, helping you find the best stocks to buy.

I also like to plug some of my own holdings into Ratings to see if I should keep holding, cash in my gains, or cut my losses. It uses several algorithmic tools, like our Business Quality Score, to give you an instant picture of a company’s overall quality.

Using Ratings can help save you from bad investments and guide you toward good ones. Uranium stocks like Cameco are just one example.

To your health and wealth,

Michael Salvatore
Editor, TradeSmith Daily