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

SHARE Coverage from SiliconANGLE's livestreaming video studio UPDATED 11:25 EST / NOVEMBER 05 2026

Generic AI models can write SQL, but they don’t know a company’s orders, customers or revenue definitions. Now, Oracle Database aims to give AI agents the context to move a stalled order forward.

But that shift raises questions about complexity, lock-in and security as AI agents start acting on live transactions. Oracle Corp.’s answer is a converged platform that keeps vectors, graphs, documents and transactions in one engine, according to Hasan Rizvi (pictured), executive vice president of product and research, database engineering, at Oracle.

“If you ask a generic AI assistant, you get a generic answer,” Rizvi said. “If you ask an AI assistant that knows your business, you get a much better answer. Where is the stock? How can I fix the transaction? How can I expedite the delivery?”

Rizvi spoke with theCUBE’s Dave Vellante at Oracle AI World, during an exclusive broadcast on theCUBE, SiliconANGLE Media’s livestreaming studio. They discussed database convergence and the safeguards needed for AI agents. (* Disclosure below.)

AI lets teams spin up applications and data stores very quickly, making data sprawl everybody’s problem. Skeptics favor specialized databases for each workload, but new data types built inside Oracle’s engine inherit proven availability, security and scale, according to Rizvi.

“We’ve been working on this engine for 40 years, which is highly available, highly secure, highly scalable, highly performant,” Rizvi said. “If you build a new data type or a new workload in the same engine, you get all that benefit, multiple decades’ worth of investment.”

Choice is the other half of the pitch. The database runs on-premises, through Oracle Cloud@Customer and across multiple public clouds, and Oracle used the event to expand Iceberg support in its Autonomous AI Lakehouse, Rizvi noted. But security is where AI raises the stakes most, with Oracle’s Deep Data Security defining access policies in the database itself, so a user’s identity travels with every request from an agent or AI-generated app.

“Before, it took a lot of time and effort to find vulnerabilities to exploit them,” he said. “Now, with AI, it’s made it very easy to reverse engineer fixes for attackers to attack.”

Here’s the complete video interview, part of SiliconANGLE’s and theCUBE’s coverage of Oracle AI World:

(* Disclosure: TheCUBE is a paid media partner for the Oracle AI World 2026 event. Neither Oracle., the sponsor of theCUBE’s event coverage, nor other sponsors have editorial control over content on theCUBE or SiliconANGLE.)

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