Oracle shares jumped as much as 10% in extended trading after the company reported quarterly results that exceeded analyst expectations and raised its fiscal 2027 revenue outlook, signaling sustained demand for AI-driven cloud infrastructure.
The company reported adjusted earnings per share of $1.79 for the fiscal third quarter ended February 28, beating the $1.70 consensus estimate, while revenue reached $17.19 billion, above analysts’ expectations of $16.91 billion, according to March 10 reporting by CNBC and Reuters. Total revenue increased 22% year over year, and net income rose to $3.72 billion from $2.94 billion a year earlier.
Cloud continues to drive the company’s growth. Oracle reported $8.9 billion in total cloud revenue during the quarter, up 44% year over year and slightly above analyst estimates of $8.85 billion. Within that segment, cloud infrastructure revenue reached $4.9 billion, rising 84% year over year and accelerating from 68% growth in the prior quarter.
The company also raised its fiscal 2027 revenue forecast to $90 billion, roughly $1 billion higher than its prior projection and well above the $86.6 billion consensus estimate cited by LSEG.
AI Infrastructure Demand Fuels Backlog Growth
Oracle’s remaining performance obligations (RPO), a measure of contracted future revenue, reached $553 billion in the quarter, more than quadrupling year over year and exceeding analyst expectations in the Reuters report. The surge reflects large-scale AI infrastructure agreements with customers building generative AI workloads.
The company said most of the RPO increase relates to large AI contracts in which infrastructure costs are offset by customer prepayments or customer-provided GPUs, reducing the need for additional financing.
Oracle has expanded its data center footprint to meet AI demand. During the quarter, the company announced plans to raise $45 billion to $50 billion to expand cloud infrastructure capacity. Oracle plans to bring more than 10 gigawatts of computing capacity online within the next three years, according to Clay Magouyrk, Oracle’s co-CEO.
The company has secured cloud infrastructure customers including Air France-KLM, Lockheed Martin, SoftBank Corp., and Activision Blizzard, a Microsoft subsidiary.
Analysis
What this means: AI infrastructure demand and data center expansion are reshaping cloud economics.
Oracle’s plan to raise up to $50 billion to expand cloud infrastructure and $553 billion RPO highlight the scale of enterprise demand for AI computing capacity. ERP platform vendors increasingly operate within a market where infrastructure investment and AI workloads are tightly linked, as well as be differentiated based on compute availability and long-term infrastructure capacity.
AI Software Strategy, Cost Restructuring
Oracle’s leadership framed AI as both a platform opportunity and a development accelerator. On the earnings call, co-founder and executive chairman Larry Ellison emphasized the role of AI-assisted coding in expanding the company’s application portfolio.
“We have these coding tools now that allow us to build a comprehensive set of software, agent-based software, to implement, to automate a complete ecosystem like healthcare or financial services,” Ellison said.
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The company said AI code generation is allowing Oracle to reorganize development teams into smaller groups while increasing software output. Reuters reported that Oracle is using these tools to build new software-as-a-service applications across multiple industries.
At the same time, Oracle’s strategy depends heavily on large capital investments in AI infrastructure. The company reported negative free cash flow of $13.18 billion over the past twelve months, reflecting the cost of its data center expansion.
Analysts view the latest results as an indicator of continued enterprise spending on AI infrastructure. As Jacob Bourne, an analyst at eMarketer, told Reuters, “Oracle’s quarter is a beat and a stress test result for the AI trade.”
Analysis
What this means: AI-assisted software development is changing application delivery models.
Oracle’s use of AI coding tools to restructure development teams suggests a shift toward smaller engineering teams producing more industry-specific SaaS applications. This approach could accelerate vertical application development across ERP ecosystems.
