Meta’s spending spree was already testing investor patience before it asked them for more money. Last week, the company reported quarterly revenue growth of 26% to about $65 billion, but operating income fell 37% to $13 billion as costs climbed sharply. It also lifted the low end of its annual capital-expenditure forecast to $135 billion, leaving investors focused on negative free cash flow rather than the headline sales beat.¹

On Monday, Meta set out its answer: raise as much as $95 billion through stock sales to finance AI infrastructure and its pursuit of “personal superintelligence.” The first stage is roughly $35 billion in underwritten equity offerings—$22.5 billion in Class A stock and $12.5 billion in depositary shares tied to preferred stock.²

The company intends to follow with a $60 billion at-the-market offering after its Class C shares begin trading in the first quarter of 2027. That approach would let Meta sell stock gradually at prevailing prices rather than in one large fixed-price transaction.²

Meta’s case is that the expense is an investment in opportunities across its apps, AI products, agent Muse and data-center business. “AI is creating significant opportunities for Meta across its core business and new products and services,” the company said, adding that it needs more infrastructure and compute to bring its vision to consumers and businesses.²

But the financing plan also shifts more of the AI arms race’s burden onto shareholders. Nvidia, AMD and Broadcom have each indicated interest in buying up to $5 billion of the common stock, though those expressions are non-binding.² Meta says it will balance the build-out with operating cash flow, investment-grade debt, partnerships and equity; it had about $82 billion in cash and liquid assets at the end of September.²

The broader industry offers little comfort for thrift. Goldman Sachs estimates AI-related spending on compute, data centers and power could reach $7.6 trillion between 2026 and 2031. As CCS Insight’s Ben Wood put it, Meta’s move reflects the “eye-watering levels of investment required to keep up in the AI arms race.”¹