We’re witnessing a global awakening around data control, with Sovereign AI emerging as the centerpiece.
Spurred by national security, economic stability, and growing distrust of centralized control, governments are demanding assurances that their data — and their citizens’ data — remains within borders, under local jurisdiction, and away from foreign influence.
Sovereign AI is their answer: a commitment to building and running artificial intelligence within a country’s own borders and on infrastructure that can be directly managed under its own laws. It’s also about keeping a nation’s data, decisions, and digital future in its own hands, regardless of how the geopolitical winds blow.
And like any strategic shift, it raises questions for enterprise and government leaders: Can your existing cloud partners deliver local control with credible independence? Can you trust their AI infrastructure if their business interests don’t align with your regulatory environment? Can your data and how that data is used in an AI environment remain sovereign?
Beyond Data Residency: True Sovereignty
When most people think about data sovereignty, they focus on where their data physically resides. But real sovereignty goes beyond where the data sits. Can the rules that protect data where it’s stored stay with the data if it’s accessed or authenticated outside its local jurisdiction? Consider this scenario: your data sits in a European data center, but the authentication systems, encryption key management, and administrative access all flow through servers in another jurisdiction. Will your data remain private if that foreign government issues a subpoena, passes a law, or signs an executive order that impacts your data?
This level of concern has moved from the fringe to mainstream boardrooms. I recently spoke with a CIO in the United Kingdom who put it bluntly: "I need full physical control and full physical isolation of my data and my encryption keys. No external cloud provider can have access to that."
Limits of Centralized AI
The early cloud era brought huge gains in flexibility, scalability, and innovation speed. But it also ushered in a new kind of concentration risk. In many regions, AI infrastructure is heavily reliant on a few hyperscale platforms. That’s not just a technical or procurement issue—it’s a sovereignty issue.
For instance, if a model is trained or hosted in a country with conflicting laws, how do you stay compliant? When updates to foundation models are opaque, how do you verify outcomes or avoid systemic bias? When a single provider can throttle compute availability or reprioritize workloads based on global demand, how do you ensure national priorities aren’t left behind?
In this environment, countries — and the enterprises that operate within them — are re-evaluating control. They want AI that’s close to the ground: physically, legally, and operationally.
Permanent Shift, Not Passing Phase
The signposts point in one direction: In three to five years, sovereign AI will become a permanent fixture in the technology landscape, but not in an all-or-nothing manner. Significant demand for hyperscale AI services for general-purpose applications will remain — you don't need a sovereign solution to write better emails. However, for sensitive data processing, the trend toward sovereignty is irreversible.
Consider healthcare. AI can identify patterns in blood tests far more quickly than human analysis, but this requires handling the most sensitive personal data imaginable. The 23andMe bankruptcy illustrates how an individual’s genetic data could be treated as a corporate asset and sold to the highest bidder. Sovereign control isn’t a luxury; it’s the last line of defense.
What’s making this possible is air-gapped AI — full separation from external clouds. We've built mechanisms that allow organizations to disconnect entirely from external clouds, allowing IT teams to download, scan, and approve commercial and open source models on their timeline, not when a vendor pushes updates.
The Economics of Independence
Sovereign AI isn’t just a security issue. It’s an economic one. If your services depend on platforms outside your jurisdiction, an overnight policy change — like a new tariff, law, or regulation — can upend your cost model. Currency fluctuations, trade restrictions, or a sudden vendor policy change could break your business plan.
This isn’t a niche concern anymore. At Broadcom, we’re working with providers across Asia, Europe, the Middle East and Latin America to help them deliver sovereign AI using trusted infrastructure that doesn’t depend on U.S. or Chinese hyperscalers.
Why does that matter? Because real sovereignty isn’t just where your data sits. It’s also about who controls or has access to it. Can you deploy models locally? Can you fine-tune and audit them?
One common fear: Will sovereign AI trap us in isolated silos? That’s where standards matter. Organizations need flexibility and interoperability — to switch hardware accelerators, test new models, and scale apps without rewriting everything from scratch.
That’s why open-source frameworks and standard APIs are essential.
We’ve built our platform with those features in mind. You can change hardware or models without locking yourself in. You can even take services developed on the OpenAI cloud and run them in your sovereign AI cloud without refactoring thanks to our OpenAI-compatible API. Unlike the hyperscalers, we do not build and sell our own foundation models. That has made it far easier for us to partner across the ecosystem without conflict, resulting in far greater flexibility and choice with our offering. Mistral AI and others are proving that sovereign-first doesn’t mean second-best.
The Strategic Choice
The questions are shifting: Not just “What can AI do for us?” but also “What happens when regulations change overnight?” In an unpredictable world, the surest bet is control. If your business depends on data you don’t fully govern, you’re exposed. Sovereign AI isn’t about fear. It’s about resiliency. It’s about designing systems with change in mind — and being ready before it comes.
The organizations that act now won’t just stay ahead of compliance. They’ll lead. In the next phase of AI, independence isn’t a limitation. It’s a strategic advantage.