Here’s the most interesting part of the strategy. Oracle’s databases hold most of the world’s highest-value private data—think health records, government data, and tax information.
The problem? Customers want the benefits of AI’s reasoning, but they do not want their private data to be used to train AI models.
Oracle’s solution is to separate the concepts. Their strategy is to use private data for reasoning, not for training.
How? Through technology like Retrieval-Augmented Generation (RAG) and AI vector search. Think of it this way: the AI can learn that “hot water burns your hand” (a reasoning-based conclusion) without ever needing to know the specific data point of “what temperature the water was” (the private data).
This allows Oracle to build smarter models by learning from the patterns in private data without ever seeing, sharing, or compromising the data itself.
