Funding Plans - Oracle plans to secure between $45 billion and $50 billion in funding during 2026 to expand its cloud infrastructure capacity to meet demand from clients like AMD, Nvidia, Meta, OpenAI, TikTok, and xAI [1] - The funding will be raised through a combination of equity and debt financing, with an approximate split of 50% for each approach [1] Equity Financing - For the equity portion, Oracle will utilize a mix of equity-linked and common equity issuances, including an initial offering of mandatory convertible preferred securities and an at-the-market equity program authorized for up to $20 billion [2] - Shares will be issued under this program in line with market prices and capital requirements [2] Debt Financing - Oracle expects to complete a single issuance of investment-grade senior unsecured bonds early in 2026, with no additional bond offerings planned for the year beyond this transaction [3] - Goldman Sachs & Co. will lead the senior unsecured bond offering, while Citigroup will manage the at-the-market equity issuance and the convertible preferred equity offering [3] Strategic Goals - The funding approach aims to preserve Oracle's investment-grade rating and maintain balance sheet strength while expanding cloud services [4] - Oracle anticipates 2026 to be a pivotal year for advancing AI in the US, focusing on building AI infrastructure to support medical research, scientific breakthroughs, and economic growth [4] AI Infrastructure Development - Oracle is developing AI data center campuses in collaboration with OpenAI in Texas and other sites in New Mexico, Wisconsin, and Michigan, with a commitment to benefit local communities [5] - The company plans to fund on-site power generation or grid upgrades and implement closed-loop cooling systems to limit water use [5] AI Supercomputer Collaboration - In October 2025, Oracle and Nvidia collaborated to build an AI supercomputer named Solstice at Argonne National Laboratory for the US Department of Energy, achieving a combined output of 2,200 exaflops of AI performance [6]