How 2 Wellington Investors Are Picking Winners And Losers As The Ai Boom Evolves

• It's getting more expensive to build data centers, which could totally change the AI trade.
• Hyperscalers could thrive, but infrastructure names could see pain, two Wellington investors said.
• Here's how to think about who might win and lose in the next phase of the AI bet.

The AI boom is minting billionaires and attracting historic amounts of investment, but it's also becoming harder for startups to cash in on the frenzy.

On Monday, Anthropic filed for a historic IPO, which could reportedly raise up to $100 billion. The very same day, SpaceX and Apollo announced a $40 billion chip financing deal.

These historic capital outlays may seem like a bullish sign for AI, but rising borrowing costs are creating a divide between companies that can easily attract capital and those that may struggle to survive.

SpaceX CEO Elon Musk said in an X post that the company was able to borrow because of its investment-grade credit rating and non-AI revenue streams, such as Starlink. Others won't be so lucky, he said.

"As of the past few weeks, debt markets have almost entirely shut off access to money for any company that doesn't have substantial revenue independent of AI data centers," Musk said, threatening "guppy-level death and consolidation" for neoclouds.

Interest rates, inflation, and the cost of compute are all rising. It's no longer a bull market for anything and everything that calls itself AI. Two investors at asset manager Wellington Management say this new era will see differentiated results for businesses.

It's not that the high cost of capital is "damning for the AI industry," Matthew Witheiler, head of late-stage growth at Wellington Management, said at an event Tuesday; it may be "damning for a specific type of business in the AI industry that used a lot of debt to fund their product bill."

"In today's world, there are a lot of haves and have-nots," he later added. Here's how it might shake out.

Loser: Infrastructure companies loaded with debt

The most obvious companies that will be hit hard by elevated borrowing costs are infrastructure investors with large debt loads.

The businesses that make up the AI "infrastructure stack" will be "ones that will be more directly impacted if the marginal amount of capacity doesn't get built because of financing costs," said Jeff Courey, a global industry analyst at Wellington covering tech firms in the public market.

Until borrowing costs go down, these companies may have to "figure out what they can afford," he said.

Witheiler agreed that it "could be true" that some of the neoclouds and other infrastructure investors have "the wrong capital structure to fulfill a lot of the demand, and they may be more challenged."

Winner: Frontier labs and hyperscalers

Those with all of the compute demand on the other side of the deal are in a much better place. Their massive size and an increased cost of borrowing mean they have quite a moat.

"It's hard to imagine a new player showing up," Courey said, noting the amount of money it would take to catch up. At the same time, these companies are seeing their revenue start to pour in, as highlighted by Anthropic's $16.3 billion in revenue in the first half of 2026, up from $1.2 billion a year earlier.

Even data points that seem negative for AI adoption, such as a recent finding from Apollo economist Torsten Slok that only the Mag Seven saw increased profitability from AI, could be seen as bullish for these companies if you look at it the right way.

"Of course, the early adopters of technology are technology companies, the Mag Seven," Witheiler said, as the other major S&P companies adopt the tech. All that means is that there's "so much more of the economy to impact," he said, driving more demand for these companies.

Winner: Fast-growing AI startups

If you need to borrow money, having an AI-focused business with prolific growth is key. AI companies that are growing 150% — or even better 1000% — year over year, at "real revenue scales," are the "haves" in this market, Witheiler said.

"Those businesses easily get financed in the private market," Witheiler said.

Even if you're cash flow negative, if you're spending on research and development that should soon pay off, or paying for salespeople who will sell your products, you won't have any worries finding cash, said Courey.

"Those kinds of cash flows are very understandable to the market," he said.

And for the "vast majority" of use cases, the actual factor holding companies back is their ability to sell their products, not the cost of tokens, Courey said. That cost is not going up nearly as fast as tokens could.

Loser: Companies that don't make a profit

If you're growing more slowly, call it "10% to 25% revenue growth," and you're breaking even or losing some money and need to raise more money or debt, "that's a really tough place to be in."

These companies have "no way" to get money because they're "competing" for dollars against companies growing 500% instead of 20%, Witheiler said.

"If you are losing money and not growing, you're worth nothing," Witheiler said.

Losers: "Wrappers" or flash-in-the-pan companies

Just because a startup uses AI doesn't mean they're going to have an easy time fundraising. If you have "rapid, rapid growth," but no defense or durability for that growth, you could have a hard time fundraising.

Companies that merely create a wrapper, or a graphical and operational interface over another company's large language model, are "not super defensible" and therefore not worth leaning into, Witheiler said. There are important questions to ask before believing the hype.

"Is it a flash in the pan and it's going to be really cool for two quarters and tons of people are going to use it and then it's going to fall off because it's a fun experiment that people got burnt out on, or is it something that in four years from now can be a stand-alone public company?" Witheiler said.