Oracle Stock: Is Strong AI Demand Enough?

Core Viewpoint - Oracle's shares dropped over 11% in after-hours trading following its Q2 fiscal 2026 report, despite a significant increase in AI demand and a large backlog of orders [2][3]. Group 1: Financial Performance - Oracle reported a slight revenue miss of $16.06 billion compared to the estimated $16.20 billion, but Remaining Performance Obligations (RPO) surged 438% year-over-year to $523 billion, indicating strong AI bookings [3][6]. - Capital expenditures reached $12 billion this quarter, with ongoing aggressive spending anticipated [11]. Group 2: Operational Challenges - The primary reason for the revenue shortfall is attributed to a lack of energized capacity rather than insufficient customer demand, highlighting concerns over the time and costs associated with developing AI infrastructure [6]. - The market is recalibrating its expectations, recognizing that Oracle's growth will depend on the speed of establishing new capacity rather than just demand [10][12]. Group 3: Strategic Positioning - Oracle is transitioning from a high-margin software company to a capital-intensive infrastructure builder, which may lead to increased depreciation expenses impacting earnings per share [7][11]. - The company is embedding its hardware within competitors' data centers, which could complicate the narrative for Oracle Cloud Infrastructure (OCI) [11]. Group 4: Market Dynamics - The competitive landscape is influenced by the physical limitations of data center construction and power availability, which are becoming bottlenecks in the AI cycle [10]. - Customers are incentivized to train AI models where their data is located, which is often within Oracle databases, providing a structural advantage against customer churn despite deployment delays [11]. Group 5: Future Outlook - The stock is perceived as "dead money" in the short term until management can demonstrate expedited physical deployment of AI clusters [13]. - Potential future improvements could arise from advancements in energy infrastructure, such as nuclear SMRs or grid upgrades, which may alleviate current capacity constraints [16].