The Strategic Role of Telecom Providers Across the AI Value Chain 2026

AI offers a chance to reset the industry’s trajectory More than just the next wave of innovation, AI represents a structural realignment of the digital economy – and a fundamental shift in the role of connectivity. As AI scales, connectivity becomes the critical bridge between users and edge devices on one side and centralized or distributed compute resources on the other. Many large language models (LLMs) remain too large to run fully on end devices, while AI workloads are increasingly distributed across devices, edge locations and data centres.2 This shift is reshaping traffic patterns as networks move beyond interaction- based AI towards continuous exchanges between autonomous agents, platforms and enterprise systems. Demand for real-time inference, video- and sensor-based applications, and multimodal AI – AI that can operate across multiple types of data within a single model – further amplifies the need for secure, real-time, predictable performance. Enabling these workloads will require more than incremental network upgrades; as TM Forum highlights, operators will need a new networking core3 built on autonomous operations and experience-based charging to meaningfully participate in – and monetize – the emerging AI value chain. Telcos approach AI from a position of structural advantage: control of critical connectivity infrastructure, proximity to users and data flows, and a longstanding role as trusted, regulated operators of national-scale systems. These assets position telcos not only to support AI adoption, but to play differentiated roles in delivering and operating AI services.The shift is not just architectural – it is also geopolitical. As the sensitivity around data sovereignty intensifies, governments are accelerating the move towards national AI infrastructure. Workloads are increasingly moving from centralized clouds to sovereign, in-country compute, driving localization for minimizing transport workloads, latency, compliance and security. Governments are channelling major capital into national AI infrastructure, from Europe’s planned AI gigafactories4 to large-scale sovereign investment vehicles in the Middle East.5 International Data Corporation (IDC) expects spending on sovereign cloud worldwide to grow 27% on average from 2022 to 2027, reaching $258.5 billion6 by the end of the forecast period. By then, localized data centres will contribute nearly a quarter of new computing capacity. The drivers are clear: economic self- interest, data protection and geopolitical resilience. Given their position as trusted, secure and local stewards, CSPs are well-positioned to anchor these emerging sovereign ecosystems, with 81% of enterprises7 seeking telcos as partners for sovereign AI adoption. At the same time, realizing this opportunity will require navigation of significant constraints, including hyperscaler dominance at the edge, fragmented regulatory environments across regions and the capital intensity of building and operating sovereign AI infrastructure. The previous paper primarily had an inward-looking focus and explored how telecom operators are adopting AI use cases across functions to increase efficiency and improve customer experience. While efficiency remains essential, this paper’s focus shifts to a more challenging question: What roles can CSPs play in the era of AI? This text explores how their infrastructure, reach and trust – all factors that define the communications industry – can power the AI economy by enabling the connectivity, compute and data movement that make AI possible. The central question is no longer how AI can improve telcos, but how telcos can enable AI. As AI scales, connectivity becomes the critical bridge between users and edge devices on one side and centralized or distributed compute resources on the other. The Strategic Role of Telecom Providers across the AI Value Chain 7