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2 ways to play the AI energy crisis

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You already know AI is changing everything—from how we work and communicate to how we invest. But there’s one crucial piece that’s not getting enough attention.

The truth is, none of this AI growth is possible without a massive surge in electricity. According to consulting firm ICF, global power demand is expected to rise by 25% by 2030… and 78% by 2050.

And here’s the kicker: We’re not ready.

Within 3–5 years, blackouts and soaring utility bills could become the norm.

But where there’s crisis, there’s opportunity… 

Let’s delve into the numbers that reveal just how severe the looming AI crisis could be… and two sectors savvy investors are buying to capitalize on the situation.

AI’s massive energy problem

New AI data centers are popping up at an astounding rate… Data centers in the U.S. have doubled since 2021. And they’re getting bigger. Tech giants like Meta (META) are building massive eight-story data centers spanning 60 football fields, consuming more electricity than entire cities. 

Goldman Sachs predicts the world will need 47 gigawatts of new power generation by 2030 just to support data center growth. To put that number into perspective, it’s equivalent to powering over 32 million homes—a 21% increase in America’s total housing supply.

Even wilder: That’s a conservative estimate—and it doesn’t even take into account the massive amounts of land, water, and other infrastructure that data centers require.

It’s also worth noting that as AI becomes more advanced, its energy needs rise. Liquid-cooled chips like Nvidia’s latest generation require nearly double the power of previous models.

The infrastructure to support this is years behind where it needs to be. Utilities are already warning they can’t guarantee long-term capacity.

Hyperscalers like Microsoft and Amazon are scrambling to lock in power deals 20-plus years out. Microsoft even signed a deal to reopen the infamous Three Mile Island nuclear plant—a project that won’t produce electricity until 2028.

Let that sink in: The biggest tech companies in the world are so concerned about future electricity access, they’re tying up supply decades in advance. If that doesn’t scream investment opportunity, we don’t know what does.

Put simply, AI is driving explosive growth in power demand… And the current energy infrastructure isn’t enough to keep up.

Energy infrastructure investments are projected to reach $150 billion by 2029 to build out capacity for these new power demands.

The situation creates an incredible opportunity for two sectors…

Utilities—no longer just your grandfather’s dividend stock

Forget everything you thought you knew about utilities. Power companies are no longer just slow, steady performers—they’re rapidly becoming the backbone of AI infrastructure.

You can already see this trend playing out in regions with the most data center growth.

For instance, Virginia has the most data centers in the country—more than the next five largest markets combined—thanks to low energy costs and state tax incentives. Meanwhile, regions seeing significant data center growth include Texas, California, Arizona, and Oregon.

Utility companies in these areas are evolving from stable, predictable investments to dynamic growth opportunities. Dominion Energy, Duke Energy, and American Electric Power are just a few examples of companies trading near their 52-week highs. And many of them are cheap at current levels given their growth potential.

The situation is similar to telecommunications companies during the internet and smartphone booms. AT&T (T) and Verizon (VZ) used to be boring dividend stocks… until the internet revolution turned them into major growth stories.

The bottom line: Utilities—once considered slow-growing dividend stocks—are now poised to become the backbone of the AI revolution… and become major growth players in the process. 

Uranium: The fuel of the future

Nuclear energy is finally getting the recognition it deserves. It’s clean. It’s scalable. And it’s the only realistic solution to the AI power crunch over the long term.

And the government sees it, too.

Back in May, President Trump issued a series of sweeping executive orders to dramatically ramp up nuclear energy production in the U.S. And the uranium sector is already reaping the rewards…

After a brief selloff earlier this year, the Global X Uranium ETF (URA) has bounced from $20 in April to $42—an 11-year high. 

Individual names like Cameco, UEC, Denison Mines, and NexGen Energy are ripping higher, too.

What to do now

We’re still in the early innings of the AI revolution. Yes, AI stocks have run up, and you might feel like you missed the boat. But the truth is that the real opportunity is just getting started.

If you want long-term exposure to AI, start building a position in the companies that make it all possible: utilities and uranium. Because when the world realizes we can’t keep up with AI’s electricity needs, these are the stocks that could surge.

And make sure to join Frank and Daniel for their FREE live event, AI’s Power Crisis: How to Profit Before the Lights Go Out, on September 25 at 7 p.m. ET.

The guys will deep-dive into the AI energy crisis… share the under-the-radar stocks poised to skyrocket… and answer your most pressing questions during a live Q&A.

Get 3 stock picks FREE when you register.





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Researchers ‘polarised’ over use of AI in peer review

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Researchers appear to be becoming more divided over whether generative artificial intelligence should be used in peer review, with a survey showing entrenched views on either side.

A poll by IOP Publishing found that there has been a big increase in the number of scholars who are positive about the potential impact of new technologies on the process, which is often criticised for being slow and overly burdensome for those involved.

A total of 41 per cent of respondents now see the benefits of AI, up from 12 per cent from a similar survey carried out last year. But this is almost equal to the proportion with negative opinions which stands at 37 per cent after a 2 per cent year-on-year increase.

This leaves only 22 per cent of researchers neutral or unsure about the issue, down from 36 per cent, which IOP said indicates a “growing polarisation in views” as AI use becomes more commonplace.

Women tended to have more negative views about the impact of AI compared with men while junior researchers tended to have a more positive view than their more senior colleagues.

Nearly a third (32 per cent) of those surveyed say they already used AI tools to support them with peer reviews in some form.

Half of these say they apply it in more than one way with the most common use being to assist with editing grammar and improving the flow of text.

A minority used it in more questionable ways such as the 13 per cent who asked the AI to summarise an article they were reviewing – despite confidentiality and data privacy concerns – and the 2 per cent who admitted to uploading an entire manuscript into a chatbot so it could generate a review on their behalf.

IOP – which currently does not allow AI use in peer reviews – said the survey showed a growing recognition that the technology has the potential to “support, rather than replace, the peer review process”.

But publishers must fund ways to “reconcile” the two opposing viewpoints, the publisher added.

A solution could be developing tools that can operate within peer review software, it said, which could support reviewers without positing security or integrity risks.

Publishers should also be more explicit and transparent about why chatbots “are not suitable tools for fully authoring peer review reports”, IOP said.

“These findings highlight the need for clearer community standards and transparency around the use of generative AI in scholarly publishing. As the technology continues to evolve, so too must the frameworks that support ethical and trustworthy peer review,” Laura Feetham-Walker, reviewer engagement manager at IOP and lead author of the study, said.

tom.williams@timeshighereducation.com



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Amazon Employing AI to Help Shoppers Comb Reviews

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Amazon earlier this year began rolling out artificial intelligence-voiced product descriptions for select customers and products.

Now, the company’s “Hear the Highlights” feature has extended to all users, CNBC reported Sunday (Sept. 14), arguing this could replace user-created reviews as the main source of product information.

Among the advantages here, the report added, is that artificial intelligence (AI) won’t suffer from cognitive overload from combing through thousands of reviews. 

“It’s important to recognize where AI is currently strong, such as in automation and pattern recognition, and where it still falls short, like in judgment-heavy tasks,” said Ankur Edkie, co-founder and CEO of Murf AI, which develops AI voiceovers. “A key question is whether there’s a way to factor in customer context as an input while generating these summaries.”

The value of AI, according to Edkie, is determining the right “problem-capability fit.” Without that, he added, a sense of “gimmickry” is likely to filter through thanks to AI fatigue, which he says consumers are likely feeling by now.

PYMNTS has contacted Amazon for comment but has not yet gotten a reply.

The CNBC report also noted that the tendency of AI to focus on common themes can water down responses even as it summarizes them, taking out the detailed personal experiences found in human reviews.

“AI might overlook unique insights or niche needs that don’t align with the majority of responses,” said Brian Numainville, principal at consumer research firm Feedback Group. “Additionally, the ability to critically interpret reviews — like spotting biases or trusting certain reviewers — is diminished with AI summaries.”

Nauman Dawalatabad, a research scientist at Zoom Communications, offered his opinion that the technology is on its way to improving customer experience.

“I take it as technology helping us to make informed decisions,” he said, pointing to the mental fatigue and wasted time that can result from working through customer reviews.

Meanwhile, recent research by PYMNTS Intelligence shows that AI shopping adoption has begun to gain traction with younger and middle-aged consumers. The research found that 32% of all consumers said they have used or would use generative AI for shopping.

“Bridge millennials — older millennials straddling Gen X — lead the way, with 38% reporting AI use for shopping,” PYMNTS wrote last month. “Zillennials are close behind at 36%, followed by millennials at 35%. Gen X is next, at 33%, while Gen Z comes in at 31%. Baby boomers show some traction as well, with 28% using gen AI for shopping.”



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China isn’t racing to artificial general intelligence — but U.S. companies are

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