WorkThe story, in brief
Establishing AI and data sovereignty in the age of autonomous systems
Enterprises made a bargain: 'Capability now, control later.' That contract is expiring.
The KeyNews take
Why it matters
As autonomous AI systems proliferate, data sovereignty and governance are becoming competitive imperatives and regulatory flashpoints. Companies built on third-party models face existential risks around data control, compliance, and strategic independence.
The key facts
4 to knowEnterprise AI adoption model: proprietary data fed to third-party models with external governance
Core tension: capability gains vs. loss of data control and sovereignty
Timing: shift from research phase to autonomous systems deployment raising governance stakes
Audience: board-level risk and strategy discussion around AI dependency
Go to the source
MIT Technology Review AItechnologyreview.com
Publisher excerpt: When generative AI first moved from research labs into real-world business applications, enterprises made a tacit bargain: “Capability now, control later.” Feed your proprietary data into third-party AI models, and you will get powerful results. But your data passes through systems you do not own,…