Larry Ellison wants the U.S. to 'unify all the national data and then feed to AI (fortune.com)

At the World Governments Summit, Oracle cofounder Larry Ellison urged nations to consolidate fragmented citizen data into unified, AI‑ready databases so models can improve services, cut fraud and save money. He argued that governments today hold “3,000 databases” worth of separate records—electronic health records, diagnostics, genomics, welfare and other administrative data—that are unusable unless standardized and aggregated. Ellison used healthcare and fraud detection as concrete examples where integrated datasets plus AI could enable earlier diagnoses, better therapeutics, and automated identification of misallocated funds. Technically and politically, Ellison’s prescription implies major investments in domestic data centers, national interoperability standards, and modernized IT stacks to host sensitive data “onshore” for privacy and sovereignty reasons. That centralization raises trade‑offs: easier AI access and analytics versus a higher‑value attack surface for state and criminal hackers (he noted recent high‑profile U.S. breaches). Realizing his vision would require strong governance—consent frameworks, encryption, access controls, logging, and privacy techniques (e.g., anonymization, differential privacy or federated learning)—plus policy decisions about who controls and vets models. The proposal reframes government AI readiness as an infrastructure and cybersecurity challenge as much as an algorithmic one.