The Bull Case for AI Just Got Stronger
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There’s supply and demand for AI computing power and there’s supply and demand for AI itself. The two should be linked, but that hasn’t always appeared to be the case. In the past few weeks, however, the two sides of the AI equation have lined up nicely.
To put it another way, the long-term case for AI demand has strengthened, and that justifies much of the investment in AI data centers. This shift could unlock more funding for the infrastructure behind AI, helping developers meet the surging demand for computing power. It could also spur a wave of even more speculative projects.
The shift justifies the big fund raising at OpenAI, as well as increasing the likelihood that it and Anthropic will have epic initial public offerings in the next 12 months. It also should give investors confidence that higher spending on computing power by Meta Platforms and others is warranted.
The reason for my optimism comes from the emergence of big-money backers seeking to accelerate business adoption of AI. Last week, my colleagues Anissa Gardizy, Valida Pau and Stephanie Palazzolo scooped talks about a potential joint venture involving Anthropic and private equity firms Blackstone and Hellman & Friedman. OpenAI appears to be doing the same thing with private equity firms TPG, Brookfield Asset Management and Bain Capital.
Those reports were quickly followed by news that Jeff Bezos is raising $100 billion to buy up manufacturing companies and use AI to help them automate. If Bezos can raise the money, the fund would be one of the biggest ever.
All of this didn’t happen in a vacuum. AI models, especially Anthropic’s newest versions of Claude, coupled with OpenClaw—software for creating AI agents—have made AI’s capabilities clear. What’s also become clear is AI agents’ insane demand for computing power, which is not likely to slow down.
What ultimately matters here is the demand for AI. The possible private equity joint ventures aimed at speeding AI adoption should help supply that. The top 10 private equity firms own more than 2,000 companies that generate roughly $2 trillion in revenue spread across nearly every industry.
The boom in AI comes at a difficult time for those firms. Many are stuffed with software companies, seen as vulnerable to AI, and have been forced to hold investments for longer than in the past because of a lack of exit opportunities.
But private equity firms won’t give up without a fight: Their executives’ compensation depends on it. That means they will embrace AI and infuse it into the companies they own. “It’s all the buzz in the PE world,” said Neil Dhar, who leads IBM Consulting’s business in the Americas and advises private equity firms. He added that some firms are identifying technology that works for them and spreading it through their companies. “You didn’t see that much in the past,” he said.
The size and breadth of private equity’s holdings mean a large number of companies will see competitors quickly adopting AI. Private equity firms tend to buy midsize companies that typically can’t afford big investments in technology. Competitors will either have to make those investments or risk falling behind.
One of private equity’s most popular strategies in recent years has been the rollup. If there’s an industry with 10 main players, private equity firms will buy up two or three, then those companies will buy one or two more of the remaining competitors. Pretty soon the industry is dominated by private equity–owned and now AI-armed companies. The remaining independent companies scramble to keep up.
The AI build-out has always been a chase after cash. By potentially creating more demand, private equity firms and the Bezos fund will effectively be adding more money to the already huge AI stockpile.
None of this means building a data center is a direct path to huge gains. Data centers are hard to build, and the economics have gotten worse with the rise of fossil fuel prices and interest rates. If they fall behind, data center developers could still blow through their funding and never get to enjoy the windfall at the end.
Demand is also not infinite. Real estate firm JLL expects $3 trillion in spending on AI infrastructure through 2030. That doesn’t sound as bonkers as it did a few months ago. The risk is that the current euphoria will give lenders confidence to fund even more projects. If there wasn’t an AI bubble last year, there might be one this year.
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