with increasing speed and efficiency. AI is exposing the limits of that model. Sensitive data must be protected, workloads must run inside defined jurisdictions, and models must be governed under tighter controls. Data cannot always move with the speed and fluidity many AI systems expect, making jurisdiction a core architectural constraint. As a result, private and sovereign AI have become critical considerations.

NTT DATA’s 2026 Global AI Report: A Playbook for Private and Sovereign AI reveals a gap between what organizations know they need and what they are ready to build:


More than 95% of respondents say private and sovereign AI are important, but only 29% are prioritizing sovereign AI in a concrete, near-term way.

About 35% of CAIOs identify building, integrating and managing complex AI models in private or sovereign environments as their top barrier to adoption, and nearly 60% of AI leaders cite cross-border data restrictions as a majo
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