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

–Cost: ❸ Retrofitting for power and cooling drives moderate investment –Complexity: ❸ Requires facility engineering but follows predictable processes –Value rationale: Attractive in AI-intensive regions but not transformational in most markets NaaS –Revenue: ❸ Programmable connectivity and APIs provide new enterprise revenue, though demand remains early-stage –Operational efficiency: ❹ Automation reduces bespoke engineering and simplifies enterprise provisioning –Cost: ❸ Requires automation, slicing and operations support system (OSS)/business support systems (BSS) integration –Complexity: ❸ Moderate technical and operational transformation required –Value rationale: Emerging monetization upside but not yet proven at scale in most markets Horizontal and vertical AI solutions –Revenue: ❺ Vertical AI represents one of the largest adjacency revenue pools for telcos –Customer satisfaction: ❹ Industry-aligned solutions deliver measurable operational outcomes –Cost: ❸ Requires investment in productization and domain expertise –Complexity: ❷ High due to vertical integration and regulated customer environments –Value rationale: Major long-term growth adjacency with multi-industry relevance GPUaaS –Revenue: ❶ Strong demand, but hyperscaler competition limits upside in non-sovereign markets –Customer satisfaction: ❸ Local compute reduces latency and simplifies enterprise procurement –Cost: ❶ GPUs, cooling and infrastructure orchestration make this extremely capital-intensive –Complexity: ❷ Requires integration with AI workflows, orchestration and SLAs –Value rationale: Demand is evident, but telcos’ competitive position is weak, limiting revenue B2C AI aggregator –Revenue: ❷ Average revenue per user (ARPU) uplift limited to bundles and churn-reduction effects –Customer satisfaction: ❹ AI assistants and personalization improve perceived service quality –Cost: ❺ Low-cost, software-driven offering with minimal infrastructure needs –Complexity: ❹ Moderate integrations but overall low implementation complexity –Value rationale: Enhances experience but offers limited commercial upside in consumer markets Sovereign AI infrastructure –Revenue: ❺ National AI programmes and sovereign AI factories offer multi-year, high-value contracts –Customer satisfaction: ❹ Supports mandatory compliance for regulated and public-sector workloads –Cost: ❶ Highest capital burden due to data centres, power systems and graphics processing unit (GPU) clusters –Complexity: ❶ Requires heavy regulatory alignment, multi-year builds and ecosystem coordination –Value rationale: One of the strongest long-term revenue pools where national investment exists The Strategic Role of Telecom Providers across the AI Value Chain 25