AI-RAN Automation Spending to Reach $1.1 Billion by 2030
Autonomous network tools are cutting energy use by 20% and cell outages by 60% as carriers prepare for the 6G era.
Updated on Oct. 28, 2026 in Robotics
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Mobile operators are increasingly deploying AI to automate radio access networks, with global annual spending projected to reach $1.1 billion by 2030. This shift toward autonomous infrastructure is currently delivering measurable operational improvements.
Why it matters
Radio access networks represent a significant portion of mobile infrastructure costs and energy consumption. Automating these systems is essential for operators aiming to move toward fully autonomous network operations before the rollout of 6G systems.
Early deployments show energy savings of 20% and a 60% reduction in cell outages during major events. Operators are achieving these figures by running rApps—modular software applications—on the non-real-time RAN intelligent controller layer to optimize multi-vendor environments.
The players
AT&T
A global telecommunications corporation currently integrating AI-driven automation into its existing radio access network infrastructure.
Rakuten Mobile
A mobile operator that has implemented highly autonomous operation levels within its live radio access network environment.
SNS Telecom & IT
An industry research firm focused on mobile infrastructure, market forecasting, and telecommunications technology trends.
The details
Operators utilize AI-based real-time optimization software delivered as subscription-based upgrades for existing network platforms. These systems analyze traffic and performance data to adjust network parameters without manual intervention. By managing the radio access network (the physical connection points between mobile devices and the core network) via intelligent controllers, providers can handle multi-vendor hardware constraints more efficiently than traditional static configuration methods.
Timeline
2026-2030 marks the primary growth period for the AI-RAN automation market.
Annual market spending is forecast to reach $1.1 billion by 2030.
The Tech Race
The transition to AI-managed radio networks marks a shift from manual configuration to highly autonomous operations. This trajectory prepares global infrastructure for 6G, which is being designed as an AI-native system from the outset.
As operators upgrade to AI-RAN systems, mobile users should experience fewer service interruptions, particularly during high-traffic events. These performance gains are rolling out globally as carriers transition their existing hardware platforms to automated, subscription-based management software.
The takeaway
The move toward AI-managed radio networks is accelerating, with measurable benefits in energy efficiency and uptime already reported. Industry observers should watch for the integration timelines of these rApp platforms in the lead-up to the 2030 forecast window.
Further reading
For broader trends in autonomous systems, see our latest coverage in Robotics.
Source note: This article includes information reported by IT Brief Australia.
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