Oracle has delivered another quarter of robust growth driven by the artificial intelligence boom, sparking anxiety in investors who focused less on rising revenues and more on the staggering amount of money the company plans to spend to stay competitive.
Shares of the software and cloud computing giant fell nearly 9% in after-hours trading on Wednesday after Oracle unveiled plans to spend as much as $95 billion on capital expenditures in fiscal 2027 and signaled it would raise almost $40 billion through a combination of debt and equity financing.
Oracle has been aiming to become one of the biggest challengers to cloud-computing leaders such as Amazon and Microsoft, leveraging major contracts with customers, including OpenAI and Meta Platforms.
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The strategy is centered on a massive expansion of data-center capacity. The company disclosed that the giant Texas-based Stargate project it is building alongside OpenAI and partners will be more than three-quarters complete within the next 90 days. OpenAI also announced that customers will soon be able to access some of its most advanced coding models through Oracle’s cloud infrastructure.
“Our pace of delivery continues to accelerate with our fiscal first quarter of 2027 delivery approaching one gigawatt, nearly the same capacity as we’ve delivered in the previous four quarters combined,” Oracle executive Clay Magouyrk said, highlighting the speed of the company’s buildout.
That figure is significant because a gigawatt-scale data center complex is comparable to the electricity consumption of a major city, which illustrates how AI is transforming cloud providers into some of the world’s largest consumers of power and capital.
Despite investor concerns over spending, Oracle’s operating metrics continue to point toward surging demand. The company reported remaining performance obligations, a measure of contracted future revenue, of $638 billion, significantly above analyst expectations of about $593 billion.
For the first time, Oracle also provided greater visibility into when that revenue is expected to arrive.
Chief Financial Officer Hilary Maxson said Oracle expects roughly $76.6 billion, or 12% of the backlog, to be recognized within the next 12 months. Another $216.9 billion, representing 34% of contracted revenue, is expected over the following two years. Those figures suggest Oracle has already secured a substantial portion of its future growth through long-term cloud and AI infrastructure agreements.
The backlog also shows that demand for AI computing capacity is outstripping supply, prompting companies to sign multiyear commitments to secure access to data centers and advanced computing resources.
Spending Like A Hyperscaler
The challenge for Oracle is that it must now spend like the hyperscale cloud giants it is trying to compete with. Oracle spent approximately $55.7 billion in fiscal 2026, already exceeding its previous target of $50 billion. For fiscal 2027, the company expects capital expenditures of up to $95 billion, although management noted that between $20 billion and $25 billion of that amount is expected to be reimbursed by customers.
Even after accounting for those repayments, Oracle’s own spending could reach around $70 billion, surpassing analyst expectations. The scale of the investment places the company among the industry’s biggest infrastructure spenders and reflects how AI has fundamentally changed economics in the cloud sector.
Unlike previous software cycles, where growth could be achieved through relatively modest investments, AI requires enormous expenditures on:
- Data centers
- Advanced processors
- Networking equipment
- Cooling systems
- Power infrastructure
The result is that cloud providers are now behaving like utilities and industrial companies, committing tens of billions of dollars annually to physical assets.
Debt Concerns Grow Louder
Wall Street’s biggest concern is no longer whether Oracle can generate demand. The question is whether it can finance expansion without placing excessive strain on its balance sheet.
Oracle said it plans to raise nearly $40 billion in fiscal 2027 through debt and equity issuance, including its previously announced $20 billion at-the-market stock offering. The financing plans come after Oracle had already indicated earlier this year that it could raise as much as $50 billion through a mix of debt and equity sales.
The growing reliance on external financing has intensified scrutiny of the company’s leverage and free cash flow profile.
“The demand is real with cloud infrastructure revenue and backlog growing fast. But the funding question is getting harder, not easier, with capex coming in well above estimates and free cash flow still negative,” Jacob Bourne, an analyst at eMarketer, said, summarizing the dilemma facing investors.
The concern extends beyond Oracle. Investors across the technology sector are now debating whether the AI boom can generate returns quickly enough to justify the unprecedented capital expenditures being undertaken by cloud providers.
Operationally, Oracle’s results were solid. The company reported fourth-quarter revenue of $19.18 billion, slightly above analyst expectations of $19.10 billion. Adjusted earnings came in at $2.03 per share, comfortably ahead of the consensus estimate of $1.96.
Yet those gains were largely overshadowed by concerns about future spending and profitability.
Maxson warned that gross margins would decline during fiscal 2027 as Oracle accelerates construction of the data-center project. That pressure lends credence to the view that profits may be squeezed in the near term as companies race to secure capacity before competitors do.
Overall, Oracle’s latest update is widely seen as one of the clearest illustrations yet of how the AI race is reshaping the technology industry. Just a few years ago, Oracle was often viewed as a mature software company with modest growth prospects. Today, it is committing nearly $100 billion annually to infrastructure projects in pursuit of AI-driven growth.
The company’s swelling backlog is believed to be an indication that customers are willing to sign enormous long-term contracts for AI computing resources. However, delivering on those commitments requires capital spending on a scale rarely seen outside energy, telecommunications, and industrial sectors.