MNTN CEO Mark Douglas warns US AI data centers won't age well in 2 years

Meta’s stock jumped more than 7% Tuesday after a Bloomberg report said the company is building a new business to sell excess AI computing capacity to outside customers, putting it in competition with AWS, Microsoft Azure, and Google Cloud. But Mark Douglas, president and CEO of connected-TV ad platform MNTN, says the more consequential story is not whether Meta should do this. It’s whether US-based AI infrastructure economics will hold up at all.

Douglas told Fortune: “I think data center capacity in the United States is not going to age well.” Then he attached a hard timeline. “I think literally two years from now, those data centers are not going to be very attractive.” His logic is blunt: it’s one of the most expensive places to build that kind of capacity, and many communities don’t want the facilities. In other words, he’s pointing to a squeeze that could show up quickly for anyone betting on the US as the default location for hyperscale AI.

If that thesis is even directionally right, Meta’s reported compute pivot has an extra layer of risk. Selling cloud-style services is a different ballgame than shipping social media apps or even running AI internally. Douglas is skeptical of the specific plan Bloomberg described because he sees it as competing in a market dominated by incumbents that already offer compute as a service. “It doesn’t make a lot of sense unless you really want to put your name in the back of the AI space - just basically get attention,” he said. And he points out that the stock reaction itself may be miscalibrating difficulty: markets often reward a famous company entering a new area as if capability automatically transfers.

In Douglas’s view, the harder part is less strategy and more execution reality. “It doesn’t matter what size you’re at - it’s really, really hard to build a new company from scratch, or a new product line, or new revenue, even when there’s proven product-market fit.” He also argues that talent dynamics make pivots even tougher for large companies: “the talent that knows how to build something from scratch usually doesn't work for a big company like Meta. They're usually building their own startups.” That’s a subtle second-order point for boards and investors: you can have the money and the brand, but still lose on the specific skill set needed to sell and operate infrastructure at hyperscale.

Douglas’s alternative competitive pressure is not domestic zoning wars or US cost curves alone. He highlights the Gulf, and Saudi Arabia in particular, as an underappreciated source of capacity. “The Kingdom of Saudi Arabia is coming online with massive data center capacity, hosted out of Saudi Arabia, at significantly lower prices - because why pump oil out of the ground and ship it overseas in tankers when you can use it here to power massive data centers?” he said, citing Saudi Arabia's Public Investment Fund, one of the world's largest sovereign wealth funds. He’s essentially describing a supply-side advantage created by energy and industrial policy, not just by clever engineering.

There’s another detail that matters to multinational customers with compliance constraints. Douglas said some Gulf data centers are structured as legal extraterritorial zones, effectively functioning as data “embassies.” The point is to let multinational clients with strict data-residency rules use the infrastructure “without technically moving data outside their home country.” Translation: even when US capacity is available, regulatory and residency needs can push spend elsewhere. This could alter demand patterns for cloud and AI compute in ways that don’t show up until procurement cycles turn and contracts renew.

Douglas then questions whether selling compute fits Meta’s core trajectory. The company went from three or four billion social media users to selling data center capacity to “10 customers” (as he described the setup of that business model) sounds, to him, like a mismatch in incentives and customer logic: “Going from three or four billion social media app users to 10 customers buying data center capacity from them - that just doesn't seem like a good fit.” He’s also warning against confusing headline optics with durable business fit: “But again, we're sitting here talking about it, which maybe is the point.”

So does he think Meta’s AI strategy is misguided overall? Not exactly. Douglas remains bullish on Meta long-term, especially its open-source models and what they could do for advertising. He argues Meta has the capital, recruitment ability, and data scale to train models and make them available at attractive prices. “That's going to benefit their ads business, and it's going to benefit the ads business generally.” He even said MNTN is in conversations with AI companies about partnering on advertising-specific models for targeting, and he pushed back on the idea that better ad-targeting AI harms consumers. “Consumers pay for everything - companies pay for nothing unless they're not profitable. The better these models can predict who wants to buy what, the lower the cost of the products are. If you make marketing more efficient, that goes back to the consumer in lower prices.”

For executives trying to interpret all of this, the meta lesson is about framing. Douglas said worries that Meta is becoming more like Amazon or Microsoft miss the point. “Taking a detour toward AI infrastructure - I think it is a detour. It's not a major strategic move. It's a tactical move. And all tactical moves have a beginning and an end. I think this one probably would too, if it comes to fruition.” Whether or not you buy the two-year US timeline, the competitive and operational pressure he describes is real: cloud compute procurement is increasingly a question of where capacity is cheapest, most compliant, and most reliable. For boards and investors evaluating pivots, the takeaway is simple. It’s not enough for an incumbent to announce it. You have to underwrite whether infrastructure economics and go-to-market realities will actually support a new revenue line before the hype fades.