Same model, better answer: Enterprise data is what turns generic AI into a business tool

Generic artificial intelligence can generate SQL queries, but lacks a company's specific order, customer, and revenue data. Oracle Database seeks to provide AI agents with that context to help resolve issues like stalled orders. This shift raises concerns about complexity, vendor lock-in, and security as AI agents start interacting with live transactions.

Oracle's solution is a unified platform that integrates vectors, graphs, documents, and transactions within a single engine, according to Hasan Rizvi, Oracle's executive vice president of product and research, database engineering. Rizvi explained to Dave Vellante of theCUBE, "If you ask a generic AI assistant, you get a generic answer.

But if you ask an AI assistant that knows your business, you get a much better answer." Oracle's platform allows for rapid application and data store development, addressing data sprawl concerns. Oracle's data engine has been refined over four decades, boasting high availability, security, scalability, and performance. Building a new data type within the same engine grants access to this accumulated investment.

Oracle offers flexibility, with the database operating on-premises, via Oracle Cloud@Customer, and across various public clouds. The company also expanded Iceberg support in its Autonomous AI Lakehouse during the event. Security is a growing concern with AI, as Oracle's Deep Data Security enables access policies to be embedded in the database, ensuring that user identities travel with every request from an AI agent or application.

This integration enhances security by making it more challenging for attackers to reverse engineer vulnerabilities.