NTT DATA Research Reveals Growing Privacy & Sovereignty Barriers

NTT DATA’s new research 2026 Global AI Report: A Playbook for Private and Sovereign AI, revealing that enterprise AI is outgrowing the architecture and infrastructure beneath it as data privacy and sovereignty requirements tighten.

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.

The research finds a widening split between enterprises that are redesigning AI for control, locality and security, and organizations still layering AI into environments that were not built to support these requirements.

“As AI evolves, private and sovereign approaches are testing enterprise readiness,” said Abhijit Dubey, CEO and Chief AI Officer, NTT DATA, Inc. “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. Our research shows AI leaders are pulling ahead by treating architecture, infrastructure and governance as strategic requirements.”

The report identifies 5 shifts defining the next phase of enterprise AI:

1. 1. AI is running into a wall – and it’s not the model. The constraint is no longer model performance alone. AI now requires greater control over compute, data access, security and locality—exposing the limits of infrastructure built for centralized, borderless data flows.
2. 2. Data jurisdiction is now an architectural constraint. Data can still move, just not the way AI needs. Because AI depends on continuous access and movement of data, jurisdiction is shaping where data lives, where models run and how systems are designed and governed.
   3. Everyone sees the shift—few are acting on it.More than 95% of organizations recognize the importance of private and sovereign AI, but only around one-third are prioritizing sovereign AI in a concrete, near-term way.
   4. Leaders are redesigning early and moving decisively—creating competitive divergence.Leaders are moving decisively, aligning infrastructure, governance and operating models early. This is enabling them to move faster from pilots to scaled deployments, while others struggle to adapt.
   5. Private and sovereign AI sounds like independence—in practice, they rely on tightly orchestrated ecosystems. More than half of organizations cite integration complexity as their top challenge. As organizations push for greater control, they are also increasing the complexity and interdependence of their AI ecosystem partners coordinating across the stack
   
3. The report draws on two studies engaging a total of nearly 5,000 senior decision-makers across more than a dozen industries, more than 30 markets and five regions

//Staff Writer