Last Thursday, OpenAI Chief Executive Officer Sam Altman, dropped a few bombs:

You should expect OpenAI to spend trillions of dollars on data center construction in the not very distant future. And you should expect a bunch of economists to wring their hands and say, “This is so crazy, it’s so reckless,” and whatever. And we’ll just be like, “You know what? Let us do our thing.”

But a few minutes later in the same interview, Altman had words of warning for investors. From Bloomberg:

[Altman] sees parallels between the current investment frenzy in artificial intelligence and the dot‑com bubble in the late 1990s. In both cases, Altman said, “smart people” became “overexcited” by a new technology. “Are we in a phase where investors as a whole are overexcited by AI? In my opinion, yes.”

Altman said, “society as a whole” is unlikely to regret the massive investment in AI, but also admitted he thinks some current startup valuations are “insane” and “irrational behavior.” He added: “Someone’s gonna get burned there.”

So, which is it? Are AI stocks about to roar higher as trillions flood the sector, making investors rich? Or are they set to implode once investors realize that today’s nosebleed valuations aren’t supported by real profits? Let’s tackle this from two perspectives…

The Bull AI Case Today

Technology expert Luke Lango’s argument can be summed up in one sentence: “Most money in the modern economy is going to AI.” He points to what he calls the AI Bazooka – the concentrated financial firepower of the world’s richest companies aimed directly at AI dominance. From Luke:

These aren’t little R&D projects. We’re talking about trillion‑dollar corporations going all‑in. Nvidia, Microsoft, Apple, Alphabet, Amazon, Meta, Broadcom, Taiwan Semiconductor, Tesla — their balance sheets make most nations look like lemonade stands. And they’re opening the floodgates…

Microsoft’s annual capex is on track to jump from less than $15 billion before COVID to about $90 billion. Meta’s going from $20 billion in 2022 to nearly $90 billion now. Alphabet? From $20 billion to $95 billion. And Amazon is leading the charge at more than $120 billion. (Disclaimer: I own MSFT, GOOG, and AMZN.) Put it all together, and Luke says the top five U.S. hyperscalers are set to spend over $400 billion in the next year alone – compared to less than $150 billion just before ChatGPT went public in late 2022. And he expects that number to hit $1 trillion annually by 2030. Back to Luke:

Every new AI model demands more compute, more storage, more bandwidth, more power. The more they spend, the more AI integrates into daily life, which drives even more spending. This is a compounding growth flywheel – and as long as the AI Bazooka is firing, AI infrastructure stocks will keep ripping higher. Now, Luke acknowledges that booms eventually bust. He fully expects an eventual “AI Bust” once rate cuts overshoot and inflation returns. But he doesn’t think we’re there yet:

We’ve got another 12 to 24 months of blockbuster runway ahead for AI stocks.

The Bear Case: Valuation Risk

Macro Investing Expert Eric Fry doesn’t disagree that the spending wave is massive. His concern isn’t the spending. It’s the price investors are paying for the companies doing the spending:

Nvidia’s market cap is $4.23 trillion — the largest in the world. It trades at 56 times earnings, about double the market average. Eric believes that many of these AI companies are great businesses – but a great business isn’t a great investment if the price tag is too high.

I’m saying that right now, the valuations are overshot. You don’t want to stock up on overvalued or faulty companies. You want to invest in the right stocks at the right time. What that means, in Eric’s playbook, is avoiding the mega‑cap names that everyone is crowding into. Instead, look for fundamentally strong companies trading at attractive valuations.

How Luke and Eric could both be right

Luke and Eric’s perspectives aren’t really at odds – they’re complementary. Luke is right that the AI spending boom is real, massive, and still gathering steam. Eric is correct that many of the companies funding this boom are priced for perfection, and perfection rarely lasts forever. The smart approach? Take both to heart. Own the companies on the receiving end of all those billions… while steering clear of (or at least, being cautious about) the overvalued AI mega‑caps that are shelling them out. That way, you’re positioned to ride the upside of the AI Bazooka – without standing directly in front of it.

Let’s get granular – how? Enough theory – let’s get down to brass tacks. Luke has specific “buy” recommendations:

The beneficiaries are spread across the entire AI supply chain.

Raw Materials

- MP Materials (MP) – Rare earths supplier up nearly 600% in the past year.
- Commodity producers feeding chip and component manufacturers are seeing their order books fill years in advance.

Chip Foundries & Compute Engines

- Taiwan Semiconductor (TSM) – Up 250% since ChatGPT’s launch.
- Nvidia (NVDA) – The poster child of the AI boom, up over 1,500% in five years.

Memory & Storage

- Micron (MU), Western Digital (WDC), Seagate (STX) – All screaming to 52‑week highs.

Semiconductor Equipment

- ASML (ASML), Lam Research (LRCX), Applied Materials (AMAT) – Selling the pickaxes in this gold rush.

Interconnect & Networking

- Astera Labs (ALAB) – Up nearly 4x since April.
- Marvell (MRVL), Rambus (RMBS) – Essential for the high‑speed data movement AI demands.

Datacenter Networking & Optics

- Arista Networks (ANET) – Red‑hot networking leader.
- Lumentum (LITE), Coherent (COHR) – Optics stocks hitting all‑time highs.

Power Generation & Energy Grid

- Constellation (CEG) – Up 50% this year.
- Vistra (VST) – Up 170% in the past year.
- Quanta Services (PWR), Eaton (ETN) – Building the AI‑powered grid.

Cooling & Infrastructure

- Vertiv (VRT) – Cooling solutions darling.
- Dell (DELL) – Server rack integrator on a tear.
- Digital Realty (DLR), Equinix (EQIX) – Datacenter developers cashing in.

This is the blast radius of the AI Bazooka. These stocks have been winning, and so long as the bazooka keeps firing, they’ll keep winning. (Disclaimer: I own ASML, VRT, LITE, COHR, DLR.) For more of Luke’s AI research and his specific AI recommendations, you can learn about joining him in Innovation Investor here.

Eric’s “sell” recommendations

Eric recently put out a “Sell This, Buy That” research package that urges investors to sell four market darlings. I got his permission to reveal three of them: Amazon, Tesla, and Nvidia. In Eric’s report, he reveals what he’s buying instead. There are AI picks – especially related to robotics. Here’s more from Eric:

I’ve compiled a list of three companies that I believe are “Buys.” These are under‑the‑radar, early opportunities that can help you protect and multiply your money during make‑or‑break markets. You can find the details of these companies – ticker symbols and all – in my special broadcast, free of charge.

Circling back to Altman… In a way, he already gave us the roadmap… Yes, “trillions” will be spent on AI in the not‑too‑distant future – and yes, we’re in a phase of “overexcitement” with some “insane” valuations. That’s essentially Luke and Eric’s combined message… The spending tsunami is real. The opportunities for the companies on the receiving end of it are enormous. But some of today’s biggest, most beloved AI names are priced as if they’ve already won the next decade – and that’s when investors are at risk of getting burned. Here’s our bottom line: Follow both Altman’s money – and his warning. History shows that valuation matters… eventually. So, be smart about where you place your bets today. Own the reasonably‑valued beneficiaries of the AI boom, while being careful about the valuations of the ones writing the biggest checks. Have a good evening,

Jeff Remsburg

The AI Stocks to Sell (and Buy) Now

Sam Altman warned that AI spending will reach trillions but investors may be over‑excited, echoing a dot‑com bubble comparison. Technology analyst Luke Lango argues that the AI boom will drive massive capital outlays from the top U.S. hyperscalers and identifies a wide array of beneficiary companies across the AI supply chain. Macro investor Eric Fry cautions that many AI mega‑caps are overvalued and recommends selling names like Amazon, Tesla and Nvidia while seeking fundamentally strong, attractively priced alternatives. The article blends Altman’s optimism with Fry’s caution, urging investors to capture upside from AI beneficiaries while avoiding over‑priced AI leaders.