Oracle recently held its FY26Q3 earnings call, addressing investor concerns about whether AI will replace SaaS software. The company stated that while AI is indeed disruptive, Oracle itself is the disruptor by embedding AI as complete functionalities directly into its applications at no extra cost. These features are included as part of quarterly updates within the application suite.

Oracle expressed strong satisfaction with its position in this field and is actively embracing AI. As a result, the company has already deployed 1,000 AI agents within its Fusion platform, with the banking suite alone containing hundreds of AI agents. Oracle emphasized it is building an entire ecosystem: automated healthcare, automated financial services, and automated retail. AI enables this expansion of vision and broadens the scope of SaaS software suite development, allowing automation of complete ecosystems.

Both multi-cloud database and AI infrastructure businesses are experiencing rapid growth. Multi-cloud database revenue increased 531% year-over-year, while AI infrastructure revenue grew 243% year-over-year. Both businesses face supply constraints, and Oracle has clear execution plans to rapidly convert this demand into high-margin recurring revenue.

The company continues to innovate its business model. Following previous discussions about funding AI infrastructure growth without additional debt or equity issuance, Oracle has signed over $29 billion in contracts using this new approach. This model combining "bring your own hardware" with customer prepayments enables expansion without consuming Oracle's cash flow, with the $29 billion representing additional orders beyond other deals signed this quarter.

During the Q&A session, analysts explored several themes. Regarding the "halo effect" of AI infrastructure on other businesses, Oracle executives detailed how proximity to AI models enables high-quality AI services embedded directly into applications. The company's infrastructure also serves as a "budget creator" for clients through more efficient workload migration.

On data center location strategy for AI inference workloads, Oracle explained that latency concerns are relative to use cases. The primary constraint isn't geographic location but rather hardware architecture, with innovations in AI accelerators being more critical than physical proximity.

Regarding AI database and data platform opportunities, Oracle noted strong demand for combining best-in-class models with private data rather than building custom LLMs. The company's multi-cloud database growth reflects customers accelerating migration of critical data to cloud environments to leverage advanced AI capabilities.

When asked about AI data center business profitability, Oracle confirmed 30-40% gross margins for accelerator business with adjacent services contributing to higher overall profitability. The constraint on margins comes from simultaneous construction of multiple data centers rather than delivered capacity.

On sovereign cloud capabilities, Oracle highlighted its unique position offering full OCI stack in sovereign configurations with flexibility in defining sovereign boundaries and delivering Oracle's complete capability set.

Addressing concerns about AI replacing SaaS, Oracle executives emphasized that mission-critical systems containing decades of industry expertise cannot be easily replaced. Instead, customers seek to consume built-in AI functionalities. Oracle positions itself as the disruptor by embedding AI capabilities at no additional charge as part of regular updates.

The company's AI Agent Studio within Fusion leverages data gravity from mission-critical systems, allowing creation of AI agents across Oracle and third-party applications while maintaining standard upgrade cycles. Oracle provides both pre-built agents and a development environment for customers and partners to expand the agent ecosystem.

Oracle Chairman Larry Ellison elaborated on the vision of automating entire ecosystems, citing healthcare as an example where Oracle automates not just hospitals but clinics, labs, payers, training systems, and regulatory processes. This comprehensive approach positions Oracle as uniquely capable of ecosystem-wide automation through AI.