AI is reshaping the sovereignty debate for telecom operators, turning it from a regulatory concern into a core infrastructure decision. As intelligence moves beyond centralized cloud environments and embeds into sectors like healthcare, energy, finance and government systems, reliance on external platforms is becoming harder to justify without clear safeguards. Control over data, operational continuity and technology supply chains is emerging as a strategic priority.
That shift challenges an industry built on centralized architectures optimized for global scale and efficiency. Greater sovereignty often requires more distributed approaches, along with tighter control over where data resides and how it moves. At the same time, hyperscalers continue to define the pace of AI innovation, creating a persistent tradeoff between independence and competitiveness that few operators can ignore.
As a result, a middle ground is taking shape. Rather than pursuing full independence or accepting total dependence, carriers are adopting more selective models to retain control over sensitive data and critical functions while leveraging external AI capabilities where necessary. In that balance, sovereignty becomes less about isolation and more about governance, resilience and long-term strategic flexibility.
Shazia Sobani:
The networks were optimized around global efficiency, and sovereignty sometimes challenges all those three pillars. You'll have to probably move from centralized to more of a distributed architecture.
Logan Wolfe:
Now you might be sovereign, but are you losing out to competition on some of the innovative aspects?
Blair Levin:
The most important thing we're going to do is solve problems before other people realize they're problems.
Steve Saunders MBE:
Until now, the digital economy has largely been built around centralized architectures, bigger clouds, bigger platforms, bigger concentrations of compute and power all concentrated in and around the core. Telecom operators helped build that world by connecting nations and enterprises to hyperscalers and cloud platforms, the most powerful privately owned infrastructure systems ever constructed. But that raises a difficult question. Should a corporation's most valuable data travel across infrastructure owned by another corporation, one ultimately controlled by people like Jeff Bezos? And should governments, utilities, and critical national systems become dependent on those same platforms, there is no simple answer, but increasingly evolving definitions of sovereignty are being viewed as the way forward. Welcome to Carrier 2.0.
AI has changed what's at stake for companies, governments, and carriers. Intelligence is no longer confined to the cloud core. It is now moving directly into the physical economy, healthcare, manufacturing, finance, logistics, energy, government infrastructure. And the more that intelligence becomes woven into those systems, the more uncomfortable centralized dependency begins to feel. Telecom operators helped build the networks underpinning the AI economy. But what happens when the hyperscale platforms running on top of those networks become too powerful and too deeply embedded for them to leave them?
Logan Wolfe:
We tend to look at it across sort of three major domains and that's data, it just underpins everything. And the second domain is operations, that's the ability to conduct and continue operations independently of foreign undue influence. And the third aspect is technology and supply chains. And it's basically being able to use technology, whether that's software or hardware, impervious to a reasonable extent to, let's say, undue surveillance or other disruptions from potentially unpalatable parties.
Steve Saunders MBE:
Historically, the concept of data sovereignty was largely tied to national borders. Data was expected to remain inside secure compliant infrastructure within a single country. If organizations expanded into another jurisdiction, they typically built another sovereign cloud environment. But modern AI systems increasingly depend on the movement of data, workloads and inference across distributed infrastructure. At the same time, compute, networks, cloud platforms, semiconductors, and energy systems are all converging into a single strategic infrastructure layer, spanning multiple countries and continents. One solution would be to get rid of the hyperscalers altogether and that's not realistic. The innovation gap is simply too vast. No carrier can independently recreate modern AI infrastructure at hyperscale. So the real question is no longer whether operators should depend on hyperscalers, it's how to balance dependency with vulnerability.
Shazia Sobani:
Historically, when you think about the network architectures, the networks were optimized around global efficiency and centralized operations and economies of scale. And sovereignty sometimes challenges all those three pillars because it basically means that you'll have to probably move from centralized to more of a distributed architecture, if you really want to have data sovereignty. Then comes the second level, which is balancing the hyperscaler innovation with operator or carrier sovereignty. You do see that operators leverage hyperscaler infrastructure and AI tooling. We are using hyperscaler infrastructure, but we have created our own AI tool link.
Steve Saunders MBE:
That may become the compromise model of the AI era, selective dependence. Carriers retaining control over essential strategic layers while consuming hyperscaler innovation where they have to.
Speaker 6:
And I for one, welcome our new insect overlords.
Steve Saunders MBE:
Technological purity may be just a pipe dream, but total dependency doesn't have to be the alternative. In practice, this increasingly plays out through sovereign systems connected by tightly controlled policy corridors, what some in the industry are beginning to describe as sovereignty tunnels. These are architectures where data remains sovereign, while intelligence still moves across borders. Because companies increasingly want two things at the same time, global AI innovation and local control. Underneath all this sits a deeper concern. For decades, carriers controlled the network, but in the AI era, true control effectively belongs to whoever manages the intelligence layer above it.
Speaker 7:
Everything is going as planned.
Steve Saunders MBE:
Carriers who just own the pipes are the data plumbers of the digital age and very few will aspire to that role.
Masum Mir:
We also have to acknowledge in telecommunication industry, we are a very, very capital heavy industry. We're at a point that we also have to go and leap. We have to do what we have been doing, but we also have to go and leap and we have to transform ourselves and also capture the next opportunity for connecting the digital world and participate on the value chain. How do we transform and transform faster?
Steve Saunders MBE:
But carriers do have one huge advantage in this dynamic, they own the customer's trust. Companies and governments all expect critical systems to operate securely and continuously, and they expect the information moving across those systems to remain confidential. That's historically been telecom territory. The bigger problem is this, virtually every major US hyperscaler has already faced lawsuits, investigations, settlements, or regulatory penalties related to customer data handling, privacy practices, surveillance, AI training, or the monetization of user information. Amazon, Google, Meta, Microsoft, and OpenAI have all faced varying degrees of scrutiny over how data gathered from users, enterprises, or even public sources has been collected, processed, transferred, or repurposed. As hyperscalers have grown more powerful, data has increasingly ceased to be treated by them merely as customer information and instead it's become the raw material of a new industrial hyperscaler economy, one which is built on surveillance, prediction, advertising, automation, and AI training at planetary scale. That is not traditionally an area where telecom operators have lost any trust, but hyperscalers have.
Shazia Sobani:
Our biggest thing was the confidentiality of the data and how do we create a walled garden where our data stays with us. There are certain privacy requirements as well, so we have to respect those privacy requirements and we use the data, which is our data, which sometimes is sensitive customer data as well and we want to respect that for our customers.
Steve Saunders MBE:
Once AI becomes embedded into critical infrastructure, questions about confidentiality and resilience stop being policy discussions, they become infrastructure requirements. There is another reality to deal with here, sovereignty is expensive. AI infrastructure demands enormous amounts of capital, power, cooling, and specialized hardware. Rebuilding all of those layers locally in the carrier network is completely unrealistic for most telecom operators.
Logan Wolfe:
You can go open source or you can go to some of the in country providers, but ultimately is it the question is, well, so now you might be sovereign, but are you losing out to competition on some of the innovative aspects? It's always kind of like a trade-off and maybe these pieces should absolutely remain sovereign. Data is often one of them, but maybe some of these other pieces, we can structure a business around them. We can actually mitigate these risks while not going fully sovereign on these aspects.
Steve Saunders MBE:
That balancing act is now spreading across the industry, not total dependence, not total independence, strategic optionality. AI infrastructure is rapidly becoming national infrastructure, which means this debate is now bigger than telecom itself. Sovereignty increasingly becomes a question of governance, coordination and long-term planning. That's why voices like Blair Levin's matter here. Long before the current AI cycle, Levin was already thinking about how communications infrastructure can shape national competitiveness.
Blair Levin:
The FCC could play a very valuable role in addressing what do we do about universal service? What do we do about cybersecurity? So there's a number of things that the FCC could be doing to position the United States better for what is coming in terms of the AI economy.
Steve Saunders MBE:
The AI era may require something even more difficult than building networks, coordinating civilian scale systems. Right now, nobody is entirely sure who controls that transition. So where does this leave us? Sovereignty without innovation does not scale, but innovation without control may eventually become its own kind of systemic risk. Who hosts it? Who governs it? Who controls the pathways through which it moves? The next great infrastructure race will not be fought merely over roads, railways, or broadband. It will be fought over intelligence itself. Clear sovereignty strategies, combined with exceptionally high levels of trust, may well become telecom carrier's greatest strategic advantage in that contest. I'm Steve Saunders, I'll see you next time on Carrier 2.0.