Oracle is leveraging a bold financing strategy to fuel its ambitious five-year partnership with OpenAI, a deal valued at $300 billion in revenue. While Oracle does not own the physical datacenters powering the collaboration, it is responsible for supplying the AI hardware—specifically GPUs and related infrastructure—under a model that relies heavily on external financing. This approach allows Oracle to avoid the massive upfront capital costs of building and operating multi-gigawatt facilities, but it requires significant investment to keep pace with OpenAI’s rapid expansion. The company’s current financial position presents challenges. As of the second quarter of fiscal 2026, Oracle held $19.8 billion in cash and carried $124.4 billion in debt. With GenAI demand outpacing traditional cloud growth, Oracle needs to deploy vast amounts of capital to build the necessary AI infrastructure—estimated at $45 billion to $60 billion per gigawatt. To meet this need, Oracle plans to raise between $45 billion and $50 billion in calendar 2026 through a mix of equity and debt. This includes issuing $15 billion to $20 billion in new shares, which will dilute existing ownership by less than 5%, and selling $5 billion in mandatory convertible preferred securities. The remainder will come from investment-grade senior unsecured bonds. This financing is essential because OpenAI will not pay Oracle until the hardware is deployed and operational. The first payments will be delayed, meaning Oracle must fund the initial buildout from its own resources and newly raised capital. The company is relying on its strong enterprise software cash flow—still substantial despite share buybacks and dividends—to reinvest in the AI infrastructure. The goal is to gradually expand the Stargate datacenter network in Abilene, Texas, built by Crusoe, and scale the fleet over time, with peak capacity expected in years three or four. The economics hinge on the assumption that OpenAI’s rental payments will eventually cover future expansion. The $300 billion revenue stream is based on providing 4.5 gigawatts of AI capacity over five years. At roughly $60 billion per gigawatt, the total hardware cost is around $270 billion, with half allocated to equipment and the other half to power and facilities. Oracle expects to generate $300 billion in revenue, meaning it could see significant profits by year five, especially if it reuses the hardware for its own enterprise customers after the OpenAI contract ends. OpenAI is reportedly securing this hardware at a lower rate—around $10 per GPU-hour—compared to AWS, Azure, and Google, which charge $14 to $18 per hour for Blackwell GPUs, and neoclouds like CoreWeave, which offer prices as low as $5 to $8 per hour. This suggests Oracle is offering a competitive edge in pricing, likely to lock in OpenAI’s long-term commitment. Beyond the OpenAI deal, Oracle’s broader strategy is to position itself as a dominant AI infrastructure provider. With over 430,000 enterprise customers, the company can repurpose surplus AI capacity once OpenAI’s usage plateaus. This creates a long-term path to profitability and strengthens Oracle’s ability to integrate AI into its databases, middleware, and applications. The real question remains: how much more will Oracle need to borrow if construction delays or partner shortfalls arise? If the Stargate project stalls, Oracle may have to enter the datacenter facility business directly—a move requiring not just billions in capital but also access to land and reliable, low-cost power. Ultimately, Oracle’s gamble is not just about building hardware—it’s about transforming its entire business. If successful, it could shift from being a software and cloud provider to a full-stack AI infrastructure leader, potentially even challenging OpenAI itself in the future. With its massive fleet of tensor compute and deep enterprise reach, Larry Ellison may one day be in a position to build his own AI models—just as he once took on IBM in the database wars.