The plan comprises approximately $35 billion in underwritten offerings, including common stock and mandatory convertible preferred stock, alongside a proposed at-the-market share sale programme of up to $60 billion. The latter is expected to begin after Meta’s new Class C shares start trading, potentially in the first quarter of 2027. The full amount is not guaranteed to be raised, and the future programme’s final terms have yet to be determined.
The fundraising comes as Meta increases spending on data centres, computing capacity and other infrastructure intended to support its AI products and services. The company expects capital expenditure of between $135 billion and $145 billion in 2026, reflecting the scale of investment required to build and operate advanced AI systems.
Meta reported third-quarter revenue of $64.6 billion, up 26% year on year, and net income of $9.9 billion. It also reported approximately $82 billion in cash, cash equivalents and marketable securities at the end of September. However, the company recorded negative free cash flow of $2.12 billion in the third quarter, underlining the pressure that substantial investment can place on cash generation.
The financing strategy reflects a wider challenge for major technology companies. AI infrastructure requires substantial capital before the full commercial value of new systems and services becomes clear. While investment may strengthen product development, advertising performance and future revenue opportunities, it can also increase exposure to financing costs and shareholder dilution.
Meta says it intends to fund investment through a combination of operating cash flow, debt, strategic partnerships and equity. Nvidia, AMD and Broadcom have indicated interest in purchasing up to $5 billion of Meta’s Class A shares, although those indications are not binding commitments.
The immediate test will be whether Meta can translate its expanding infrastructure into durable earnings and cash generation. Investors will also assess the final terms of the offerings, the pace of capital expenditure, and whether returns from AI products justify the scale of funding required. The outcome could influence how markets value the broader technology sector’s investment race.
