Sagar Nangare
October 9, 2025
5 Minutes read
How Telecom Players Are Powering the New Era of Sovereign AI Infrastructure
The concept of data sovereignty gained traction in the late 2010s, as cloud hyperscalers began expanding rapidly and social media platforms like Facebook and YouTube became dominant forces. In response, many countries and regions introduced compliance frameworks to safeguard sensitive information and prevent critical data from crossing national borders. This concern extended beyond data storage to include how data is processed and used by applications.
Today, we are amid an AI revolution, driven by Generative AI and Agentic AI, which are reshaping industries and business models. In this context, AI sovereignty has emerged as a vital issue. It is now widely accepted that data is the new oil—and nations that control vast amounts of internet data are better positioned to lead in AI innovation. After all, data is the fuel that enables AI systems to learn, adapt, and evolve.
The article explores how telecom operators are strategically positioning themselves to deliver Sovereign AI solutions to their customers. While they may lag behind tech companies and hyperscalers in terms of technological advancement, telecoms have a unique opportunity to capitalize on this shift—especially in B2B, and increasingly, B2C markets. Their ultimate goal? To monetize this opportunity and potentially establish dominance in a rapidly growing sector.
What Exactly Is Sovereign AI?
In recent months, “Sovereign AI” has emerged as one of the most discussed concepts shaping the future of artificial intelligence and digital infrastructure.. But what does it really mean?
At its core, Sovereign AI refers to AI systems, infrastructure, and data ecosystems that are owned, managed, and governed under the authority of a specific country or region. It’s about control — over data, infrastructure, and how AI is trained and used.
Here are the key pillars that define Sovereign AI:
The Forces Driving Sovereign AI
The rise of Sovereign AI is not accidental — it’s the result of multiple global and regional forces converging around trust, autonomy, and digital competitiveness. Let’s look at these drivers holistically:
- Regulatory and Privacy Pressure
Across the world, governments are tightening data protection and AI governance laws to ensure national data doesn’t fall under foreign influence or vulnerability. The push for digital sovereignty and AI transparency is stronger than ever. - National Security and Strategic Autonomy
AI is no longer just a technological enabler — it’s a strategic asset. From defense and infrastructure to economic competitiveness, countries are seeking to gain control and minimize their dependence on foreign technology in sensitive areas. - Latency, Performance, and Localization
For applications such as real-time analytics, edge AI, or generative AI in local languages, having infrastructure closer to users is crucial. Localized AI infrastructure enhances latency, ensures faster response times, and delivers experience tailored to regional needs. - Economic Value and Telecom’s Expanding Role
Telecom operators already own critical infrastructure — data centers, fiber networks, and edge facilities — making them ideal enablers of Sovereign AI. By offering GPU-as-a-Service (GPUaaS) or running AI factories, telcos can move beyond connectivity into high-value AI infrastructure services.
Analysts predict this market could generate billions in new revenue opportunities over the next decade. - Open Source and Model Portability
The open-source ecosystem is playing a key role in democratizing Sovereign AI. Countries and enterprises can now build local AI systems using open frameworks and models, thereby reducing their reliance on proprietary, foreign-controlled solutions.
Why Telecom Operators Are Central to Sovereign AI
Telecom companies are uniquely positioned to be the backbone of the Sovereign AI movement. Here’s why:
- Distributed infrastructure: Telcos already operate nationwide networks of data centers, edge nodes, and cloud platforms — all critical for low-latency AI processing.
- Regulatory alignment: As regulated entities, telecom operators are well-accustomed to compliance, data localization, and privacy requirements — making them natural custodians of sovereign digital systems.
- AI infrastructure services: By offering GPU-as-a-Service (GPUaaS) or managing AI factories, telcos can provide secure, high-performance AI infrastructure to governments and enterprises. Source
- Integration with 5G and edge computing: The combination of 5G, edge cloud, and eventually 6G will enable new real-time, distributed AI applications — from autonomous systems to smart cities — built on sovereign principles. Source
Real-World Examples of Sovereign AI in Action
The Sovereign AI wave is already taking shape worldwide. Some notable examples include:
- SK Telecom (South Korea) has launched its own sovereign AI infrastructure using NVIDIA Blackwell GPUs. Its “Haein” cluster offers GPU-as-a-Service while ensuring all data and processing remain within South Korea. Source
- TELUS (Canada) unveiled a Sovereign AI Factory, powered by NVIDIA, hosting all AI workloads and training within Canada’s borders. Source
- Telkom Indonesia partnered with IBM to deploy secure, in-country AI platforms using IBM’s WatsonX for both telecom and enterprise customers.
- According to ABI Research, telecom operators are projected to earn over US$21 billion globally from GPUaaS and sovereign AI infrastructure services by 2030.
- On the research front, studies such as “Sovereign AI for 6G” explore how next-generation mobile networks can embed control and governance directly into their AI frameworks.
Closing Thoughts
Sovereign AI represents more than just a regulatory compliance trend — it’s about reclaiming digital independence and reshaping the global AI landscape.
For telecom operators, it’s a once-in-a-generation opportunity to redefine their role — from connectivity providers to enablers of AI infrastructure.
As nations continue to balance innovation, security, and autonomy, Sovereign AI is emerging as the cornerstone of the next wave of digital transformation.
Here is the question to our readers: Can telecom operators successfully compete with established cloud hyperscalers in the AI domain, or will their role be more collaborative in nature?
Related Insights
Prompting techniques for QA Engineers
Dipali Pawar
The Hidden Threat of Data Drift in Telecom AI
Sagar Nangare
