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Nokia Unveils First Commercial AI-Native RAN Platform, Emphasizing Software-Driven Innovation
Nokia announced the launch of its industry‑first commercial AI‑native radio access network (AI‑RAN) platform on 15 July 2026. The platform, built on accelerated computing and the anyRAN software foundation, pairs Nokia’s open‑source RAN software with NVIDIA’s merchant GPU technology. The company said the platform will support 4G, 5G, and future 6G networks and will be available for pilot deployments by the end of 2026, with commercial availability scheduled for 2027.
The announcement did not change Nokia’s overall AI‑RAN roadmap or timeline. The company reiterated that the strategy, laid out to date, remains largely unchanged from the plans presented to analysts and investors over the past year. What has shifted is Nokia’s messaging and confidence in its merchant silicon approach. During the Mobile World Congress in Barcelona, Nokia’s executives moved from a cautious stance—highlighting the need to balance custom and merchant silicon—to a more assertive position that positions AI‑RAN as a software‑defined platform rather than a hardware story.
A key element of the new messaging is a simplified migration path. In earlier presentations, Nokia had broken the architecture into purpose‑built D‑RAN, D‑RAN vRAN, and C‑RAN vRAN. The latest presentation focuses on three deployment profiles—installed‑base leverage, high‑capacity AI‑RAN, and cloud‑native AI‑RAN—rather than specific vRAN architectures. The company said the migration strategy remains intact, with the changes reflecting refinements in packaging and messaging.
Nokia also expanded the scope of AI‑on‑RAN beyond traditional RAN optimization. The company highlighted sensing, positioning and location services, and third‑party software applications that could run on the platform. These use cases are presented as complementary software‑ecosystem opportunities, not as the primary justification for the architecture.
Spectral efficiency is a headline claim. Nokia said the platform can deliver up to a 2× improvement in spectral efficiency compared with legacy RAN. Analysts have cautioned that spectral‑efficiency gains depend heavily on deployment scenarios and baseline performance, making cross‑vendor comparisons difficult. The company’s claim aligns with its own target of more than 100 % spectral‑efficiency gains by 2028, a figure that would effectively double mobile traffic capacity.
The announcement also dovetails with Dell Oro’s market forecasts. The firm’s latest AI‑RAN and GPU‑RAN outlook projects cumulative AI‑RAN revenue of $35 billion over the next five years and a GPU‑RAN market exceeding $1 billion by 2030. Nokia’s emphasis on AI‑for‑RAN as the primary value proposition and its growing confidence in merchant silicon deployments are consistent with the view that AI‑for‑RAN adoption is accelerating as operators prepare for more software‑centric and AI‑native RAN architectures.
Nokia’s AI‑RAN strategy is part of a broader effort to reverse a decade‑long decline in its RAN market share. The company has lost roughly ten percentage points of share since the early 2010s. By positioning AI‑native RAN as a software‑driven, flexible, and high‑capacity solution, Nokia aims to strengthen its competitive standing in a highly concentrated market.
In summary, Nokia’s launch of the first commercial AI‑native RAN platform signals a continued commitment to software‑defined radio and merchant silicon. The company’s refined migration narrative, expanded software ecosystem, and confidence in GPU‑based acceleration underscore its strategy to deliver higher spectral efficiency and new capabilities to operators. The platform’s commercial rollout in 2027 and pilot deployments in 2026 will test the market’s appetite for AI‑native RAN and could influence the pace of 6G‑ready network rollouts.
The announcement did not change Nokia’s overall AI‑RAN roadmap or timeline. The company reiterated that the strategy, laid out to date, remains largely unchanged from the plans presented to analysts and investors over the past year. What has shifted is Nokia’s messaging and confidence in its merchant silicon approach. During the Mobile World Congress in Barcelona, Nokia’s executives moved from a cautious stance—highlighting the need to balance custom and merchant silicon—to a more assertive position that positions AI‑RAN as a software‑defined platform rather than a hardware story.
A key element of the new messaging is a simplified migration path. In earlier presentations, Nokia had broken the architecture into purpose‑built D‑RAN, D‑RAN vRAN, and C‑RAN vRAN. The latest presentation focuses on three deployment profiles—installed‑base leverage, high‑capacity AI‑RAN, and cloud‑native AI‑RAN—rather than specific vRAN architectures. The company said the migration strategy remains intact, with the changes reflecting refinements in packaging and messaging.
Nokia also expanded the scope of AI‑on‑RAN beyond traditional RAN optimization. The company highlighted sensing, positioning and location services, and third‑party software applications that could run on the platform. These use cases are presented as complementary software‑ecosystem opportunities, not as the primary justification for the architecture.
Spectral efficiency is a headline claim. Nokia said the platform can deliver up to a 2× improvement in spectral efficiency compared with legacy RAN. Analysts have cautioned that spectral‑efficiency gains depend heavily on deployment scenarios and baseline performance, making cross‑vendor comparisons difficult. The company’s claim aligns with its own target of more than 100 % spectral‑efficiency gains by 2028, a figure that would effectively double mobile traffic capacity.
The announcement also dovetails with Dell Oro’s market forecasts. The firm’s latest AI‑RAN and GPU‑RAN outlook projects cumulative AI‑RAN revenue of $35 billion over the next five years and a GPU‑RAN market exceeding $1 billion by 2030. Nokia’s emphasis on AI‑for‑RAN as the primary value proposition and its growing confidence in merchant silicon deployments are consistent with the view that AI‑for‑RAN adoption is accelerating as operators prepare for more software‑centric and AI‑native RAN architectures.
Nokia’s AI‑RAN strategy is part of a broader effort to reverse a decade‑long decline in its RAN market share. The company has lost roughly ten percentage points of share since the early 2010s. By positioning AI‑native RAN as a software‑driven, flexible, and high‑capacity solution, Nokia aims to strengthen its competitive standing in a highly concentrated market.
In summary, Nokia’s launch of the first commercial AI‑native RAN platform signals a continued commitment to software‑defined radio and merchant silicon. The company’s refined migration narrative, expanded software ecosystem, and confidence in GPU‑based acceleration underscore its strategy to deliver higher spectral efficiency and new capabilities to operators. The platform’s commercial rollout in 2027 and pilot deployments in 2026 will test the market’s appetite for AI‑native RAN and could influence the pace of 6G‑ready network rollouts.
