Hunter Point’s CEO Sees a Data Center Overbuilding Risk in AI Boom

The artificial intelligence boom is driving an unprecedented buildout of data centers, but investors may be getting ahead of themselves, according to Hunter Point Capital CEO Avi Kalichstein.

Kalichstein is not concerned that the surge in AI infrastructure spending poses a systemic risk to financial markets. But he expects some investors will eventually discover they put too much money into data centers that fail to generate attractive returns, he said during an interview with CNBC’s Alts Investing.

"It feels to me like somebody somewhere is overinvesting in data centers that will turn out not to be great investments," Kalichstein said.

The warning comes as AI companies and their infrastructure partners commit hundreds of billions of dollars to computing capacity. Global AI investment is expected to approach $1 trillion this year, fueling demand for data centers, power and other infrastructure needed to run increasingly compute-intensive models, a report from Goldman Sachs stated.

For private-market investors, however, the rapid expansion creates a difficult underwriting question: How much of that capacity will ultimately be needed?

Kalichstein said Hunter Point has been cautious about investments where it cannot fully understand the underlying economics or determine which assets are likely to succeed.

"If we can’t really understand and we can’t see the future, we do think" that warrants caution, he said, contrasting data centers with assets such as airports, where investors have a clearer view of long-term demand.

The uncertainty is particularly relevant for private credit, where lenders are increasingly exposed to companies and infrastructure tied to the AI investment cycle.

AI Changes the Credit Equation

Kalichstein said private credit remains on solid footing because many of the underlying businesses managers finance continue to perform well. But AI is changing how investors assess those borrowers.

He said managers are broadly separating their portfolios into three groups: businesses that are largely immune to AI, companies whose products or margins could be significantly disrupted and businesses that could benefit from AI while also facing new competitive threats.

That assessment is affecting pricing and decisions about which companies are durable enough to finance, Kalichstein said.

Software is one area where the shift could be particularly significant. Some businesses that previously looked like durable private credit borrowers may face a more uncertain future if AI reduces demand for their products or puts pressure on margins.

The data-center question is different. Rather than worrying about whether AI will create demand, investors are betting on how much demand will exist — and where it will ultimately land.

Private Credit Isn’t Out of the Woods

On private credit, Kalichstein said the broader market is still working through redemption pressure from individual investors, even as institutional demand remains strong. 

He expects it will take several more quarters of performance before that pressure fully settles.

"I think we need another few quarters of performance to kind of let all of that pass until we get to some kind of stasis," he said. "So we’re not done yet."

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