SoftBank’s AI-RAN Whitepaper Outlines Blueprint for Telecom Transformation

SoftBank reveals AITRAS, a GPU-based AI-RAN system designed to convert telecom infrastructure into an AI-native computing platform, aiming to shift networks from cost centers to revenue engines.

SoftBank’s latest whitepaper, AI-RAN: Telecom Infrastructure for the Age of AI, lays out a comprehensive vision for reimagining telecom networks with artificial intelligence at their core. The company introduces AITRAS, a platform that integrates RAN and AI workloads on a unified GPU-based infrastructure, backed by NVIDIA Grace Hopper chips.

More than just incremental progress, this whitepaper positions AI-RAN as a turning point in the evolution of mobile infrastructure—from static, hardware-driven networks to computing-centric, software-defined systems that run both connectivity and AI services side by side.

The gRAN (GPU-RAN) architecture enables parallel processing of complex RAN tasks and AI inferencing on the same system. With use cases ranging from real-time robotics and autonomous driving to AI-native customer service, SoftBank argues that AI-RAN is not only a performance booster but also a strategic asset.

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Critically, the paper addresses sustainability and cost: real-world testing in urban Japan shows power usage on par with existing RAN systems, while unlocking new monetization models like Edge AI-as-a-Service. SoftBank forecasts a 33% ROI over five years in a “RAN-heavy” configuration, with even greater upside if AI workloads dominate.

Why It Matters:

As mobile data traffic and AI workloads surge, telecom operators face unsustainable CAPEX burdens. AI-RAN offers a way to repurpose base stations into multi-tenant, revenue-generating compute hubs, opening a path to economic sustainability in the 6G era.

Questions to Ask:

  • Can operators realistically adopt GPU-based architectures at scale, given energy and cost considerations?
  • Will AI-RAN architectures like AITRAS achieve sufficient vendor interoperability and standardization?
  • How will spectrum efficiency and latency-sensitive use cases benefit—or suffer—from co-located AI workloads?

As global RAN strategies evolve, SoftBank’s whitepaper is a timely contribution to a bigger conversation: can telecom embrace AI not just as a tool, but as a fundamental design principle?

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