Pershing Square's Meta stake draws focus after earnings and AI spending debate

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Pershing Square Meta earnings focus

Highlights

Pershing Square increased its Meta stake in February 2026, making it a core holding, with the position initially at 10% of capital in late 2025.
Bill Ackman asserts Meta's AI-driven long-term growth potential justifies current discounted valuation and supports upfront investment in compute infrastructure and talent.
Despite Meta beating third-quarter revenue estimates and issuing strong guidance, shares fell as investors questioned whether elevated AI spending will drive sustainable earnings growth.

Pershing Square's Meta investment thesis

As reported by CNBC, Ackman has made Meta a core part of Pershing Square's portfolio after the hedge fund first established a position in late 2025, when the stake accounted for 10% of the firm's capital at the end of that year.

He increased the position to a sizable stake in February. In an investor presentation at the time, Ackman said Meta's long-term upside potential from AI represented a deeply discounted valuation for what he described as one of the world's greatest businesses.

Pershing Square also believes Meta's investments in compute infrastructure are necessary and could eventually produce attractive returns. The firm has said the company is well positioned for long-term earnings growth because the potential upside from AI supports front-loading infrastructure and talent investments.

Market reaction and sector implications

Meta's role in Pershing Square's portfolio is drawing added attention as the Facebook and Instagram parent posts stronger-than-expected third-quarter revenue on Wednesday and issues solid guidance for the current period.

Even so, the shares are lower as investors weigh the scale of the company's AI spending. That tension highlights a broader market debate over whether heavy near-term investment in AI infrastructure will translate into sustained earnings growth for major technology companies.

In our earlier coverage of the U.S. AI data center boom, we explained how soaring financing costs, construction delays, and power constraints are starting to challenge the rapid buildout of computing capacity. We noted that only a minority of planned projects appear realistically deliverable, while cost overruns and local pushback are adding pressure on developers to prove they can turn massive capex into sustainable returns.

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