Oracle AI World to spotlight database modernization for repeatable AI

TheCUBE Research has found that the motivation for database modernization has traditionally been greater efficiency and cost savings, but a larger prize is at stake: AI projects built on a modernized foundation can generate significant value. “For Oracle customers, the strategic question is becoming: Are we simply reducing infrastructure cost, or are we creating a better platform for repeatable AI execution?” said Dave Vellante of theCUBE Research. He said the bigger opportunity is using that foundation to get onto the AI learning curve earlier, free skilled teams from routine administration, improve governance consistency and accelerate AI use cases over time. Database modernization remains an IT decision but is increasingly an AI readiness decision, he said.

Oracle plans to use the event to show product advancements in guardrails and trust. Juan Loaiza, executive vice president of mission-critical database technologies at Oracle, said AI-generated solutions need to be accurate, secure and reliable for enterprises to trust results as autonomous agents build applications and take actions. “Guardrails don’t cut it. You can’t simply drop AI on top of an architecture that was never designed for these challenges AI brings and expect it to work,” Loaiza said during a pre-event conversation with theCUBE. “What we’re doing is different. We’re ensuring trust across the entire technology stack. The only way we think is possible to build AI solutions that we can trust is to architect the whole thing together — AI, data and AppDev all in one whole.”

Earlier this year, Oracle outlined a three-pronged strategy to address security challenges from wider AI use. AI systems have created new paths to sensitive enterprise data, and Oracle has implemented tools for database security, patching, testing and lifecycle management. Arpan Shah, senior vice president of Oracle Database, said a key focus in Las Vegas will be showing what Oracle is doing in the product and how features are designed from the data layer to the app layer to help customers move from AI prototypes to trusted AI apps at scale.

Oracle will also detail intelligent data architecture. Nipun Agarwal, senior vice president of Oracle Autonomous AI Lakehouse, said Oracle will unveil new capabilities in Autonomous AI Lakehouse, which combines Autonomous Database capabilities with Apache Iceberg’s open table format to provide an interoperable analytics foundation across major clouds. “The lakehouse is transforming from being an analytic platform into a decision backbone for enterprise AI,” Agarwal told theCUBE. He said customers previously came to a lakehouse for analytic workloads, but it is now an appropriate platform for both analytic and AI workloads.

Oracle’s Autonomous AI Database provides a fully automated, cloud-based data platform that uses machine learning and AI to manage, tune, patch and secure itself. Its multicloud capabilities let enterprises run it in Oracle Cloud Infrastructure or on Oracle managed services in Amazon Web Services, Microsoft Azure and Google Cloud. The database supports multimodal data management, transactional and analytical processing, and efforts to standardize and automate database operations.

Editor's Summary

Oracle AI World on Oct. 28 will center on database modernization as a foundation for repeatable AI, with Oracle executives emphasizing trust, security and lakehouse capabilities. Oracle plans to detail new Autonomous AI Lakehouse features and multicloud database options as it seeks to move customers from AI prototypes to production.