Vendors Push AI-RAN Toward $6.18 Billion Market Value, but Operators Remain Cautious

NEW YORK, Sept. 30, 2025 /PRNewswire/ -- The global telecom infrastructure market is on the verge of a significant transformation with Artificial Intelligence in Radio Access Networks (AI-RAN), which is designed to improve overall performance, automation, and reduce operational expenses. A recent report by ABI Research, a global technology intelligence firm, stated that AI-RAN revenues are projected to reach approximately US$6.18 billion by 2032, with significant acceleration anticipated from 2029 onward. Despite this promising forecast, current operator adoption remains cautious due to a lack of independently verified return on investment and field-proven performance results.

Even though vendor interest is gaining momentum, as evidenced by a membership growth rate of the AI-RAN Alliance from 11 initial members a year ago to over 80 today, operator interest is less abundant at only 8 members. The gap between vendor and operator participation signals some industry skepticism regarding the near-term value of AI-RAN. Existing pilots like SoftBank's AITRAS platform and NVIDIA's pilots in Shenzhen are promising, but those initiatives still lack third-party validation of systemwide cost savings and performance improvement.

"The real growth in AI-RAN will only come when performance benchmarks are validated in the field," explains Samuel Bowling, Research Analyst at ABI Research. "Operators need evidence that AI-RAN can deliver technical and financial outcomes at scale, with a justifiable cost model. Without that, adoption will continue to lag behind vendor enthusiasm."

One of the central factors influencing adoption is the ongoing debate around compute architecture. GPU-based platforms such as NVIDIA's Aerial RAN Computer-1 and ARC-Compact provide high-performance for use cases like massive MIMO and beamforming, though some worry remains about their high energy consumption, reliance on proprietary software stacks, and potential vendor lock-in. Meanwhile, CPU-based solutions and custom silicon implementations continue to meet current AI requirements while being more energy efficient and lower cost, which supports operators' needs for flexibility and operational efficiency. This uncertainty over architectural direction continues to slow AI-RAN decision-making across markets.

"Operators need more than hype, they need transparent, validated evidence that AI-RAN delivers real-world performance and long-term value," says Bowling. "The AI-RAN Alliance must now move beyond vision statements and facilitate real pilot deployments with Tier One operators, standardize benchmarks, and publish clear comparisons across GPU, CPU, and custom silicon solutions. Demonstrating cost savings and performance in urban, rural, and remote environments will be critical to building trust and moving from trials to widespread commercial deployments by 2030."

These findings are from ABI Research's AI-RAN Market Developments research report, part of the company's 5G, 6G, Open RAN research service, which includes research, data, and ABI insights.

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