Data sovereignty and regulatory conformity are usually treated as internal governance obligations — get them right and your data strategy holds up under audit. That framing misses what's happening at the infrastructure layer right now. The US reportedly told OpenAI and Anthropic to withhold new frontier models from the UK's AI Security Institute pending its own review — a jurisdictional access dispute between two of the most closely aligned AI regulators in the world. Labs are separately building "high-priority defender" access programs for cyber-defense AI, framed around government, health and telecom sectors, with no stated path for organizations outside that framing. Meanwhile, 78% of AI governance frameworks in the Global South remain non-binding, against 42% in the Global North — a gap that shapes not just what a jurisdiction can require of AI deployments, but what leverage it has to negotiate access to the systems at all.

The pattern across all three: regulatory posture no longer just determines your compliance exposure. It's becoming what determines whether you get access to frontier AI capability, at what tier, and on whose terms. This session works through what that means for organizations building data and AI strategy outside the US/EU regulatory core — what data sovereignty needs to accomplish now, and how to build resilient AI infrastructure without a seat at the table that sets the terms of access.