NTT DATA has released new research showing that enterprise AI adoption is increasingly being constrained by data privacy, sovereignty, and jurisdiction requirements, forcing organizations to rethink the architecture and infrastructure supporting their AI strategies.
The findings, published in the 2026 Global AI Report: A Playbook for Private and Sovereign AI, highlight a growing divide between enterprises redesigning systems for secure, localized AI operations and those still relying on traditional architectures built around centralized and borderless data flows.
“The organizations that are succeeding are going beyond regulatory compliance and risk mitigation. They are building the operating foundation for AI that can perform across markets, jurisdictions and business environments,” said Abhijit Dubey, CEO and Chief AI Officer, NTT DATA, Inc.
According to the report, more than 95% of organizations recognize the importance of private and sovereign AI, yet only 29% are taking concrete near-term steps toward implementing sovereign AI strategies. Nearly 60% of AI leaders cited cross-border data restrictions as a major challenge, while only 38% expressed strong confidence in their cloud security posture.
The study suggests that as enterprises scale AI deployments, jurisdictional controls over where data resides and how it is processed are becoming core architectural requirements rather than compliance afterthoughts.
Abhijit Dubey, CEO and Chief AI Officer at NTT DATA, said organizations leading in AI adoption are treating governance, infrastructure, and security as strategic business priorities.
“As AI evolves, private and sovereign approaches are testing enterprise readiness. The companies moving fastest are redesigning their operating foundations early, enabling them to scale AI more effectively across regulated and distributed environments,” Dubey said.
The report identified five major trends shaping the next phase of enterprise AI adoption, including the growing importance of data locality, increasing complexity of AI ecosystem integration, and the emergence of competitive advantages for organizations redesigning infrastructure early.
NTT DATA noted that private AI focuses on protecting enterprise data and limiting exposure, while sovereign AI addresses regulatory and jurisdictional requirements governing where AI systems and workloads operate.
The research draws on insights from nearly 5,000 senior decision-makers across more than 30 markets and multiple industries worldwide. According to the company, organizations that fail to redesign infrastructure for secure and localized AI deployment may struggle to convert AI investments into long-term operational value.
