Why some of the world’s biggest enterprises are pivoting to Sovereign AI

It's not just about compute power or GPUs

by · TechRadar

Opinion By Paul Speciale published 28 April 2026

(Image credit: Getty Images)

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It is no longer a secret that enterprises are quickly evolving their AI tools and planning to the next stages, after the initial pilot projects and experimentation. AI is advancing at light-speed, with advancements in capabilities being announced weekly.

This means organizations are now looking beyond LLM usage, focusing instead on leveraging agentic AI for real business outcomes. This has serious implications on control over data quality and security, which in turn implies control over their infrastructure.

Private AI provides a path for organizations to deploy AI and the data it consumes in secure sovereign environments, on-prem or in a private cloud, keeping sensitive assets protected and away from third parties or public models.

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Paul Speciale

Chief Marketing Officer at Scality.

The findings of our recent report support a more data-centric view of AI operations as inference becomes increasingly prevalent in day-to-day use. It also highlights the demand for control and predictability in environments where data sensitivity and regulatory oversight shape deployment decisions.

Determining that the data defines the problem, and the platform determines who scales underscores the growing recognition that mastery over AI is not just about compute horsepower or GPUs. Orchestrating data effectively, securely, and consistently is of key importance.

As private and sovereign AI gain adoption, governance, compliance, and data locality have claimed center stage. Private AI ensures organizational control of data, and sovereign AI extends oversight to meet national or jurisdictional requirements.

A sovereign infrastructure provides the very foundation, while sovereign AI is the application layer that operates atop it with full regulatory alignment. This reflects a growing understanding: AI is fundamentally a complex data challenge, requiring precise orchestration and secure, reusable data throughout its entire lifecycle.

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