PUBLISHER: Global Industry Analysts, Inc. | PRODUCT CODE: 1794567
PUBLISHER: Global Industry Analysts, Inc. | PRODUCT CODE: 1794567
Global O-RAN Near-Real-Time RAN Intelligent Controllers Market to Reach US$87.0 Billion by 2030
The global market for O-RAN Near-Real-Time RAN Intelligent Controllers estimated at US$7.4 Billion in the year 2024, is expected to reach US$87.0 Billion by 2030, growing at a CAGR of 50.7% over the analysis period 2024-2030. A1 Mediator Component, one of the segments analyzed in the report, is expected to record a 43.9% CAGR and reach US$17.2 Billion by the end of the analysis period. Growth in the RIC Alarm System Component segment is estimated at 55.8% CAGR over the analysis period.
The U.S. Market is Estimated at US$1.9 Billion While China is Forecast to Grow at 48.4% CAGR
The O-RAN Near-Real-Time RAN Intelligent Controllers market in the U.S. is estimated at US$1.9 Billion in the year 2024. China, the world's second largest economy, is forecast to reach a projected market size of US$12.8 Billion by the year 2030 trailing a CAGR of 48.4% over the analysis period 2024-2030. Among the other noteworthy geographic markets are Japan and Canada, each forecast to grow at a CAGR of 45.2% and 44.4% respectively over the analysis period. Within Europe, Germany is forecast to grow at approximately 35.4% CAGR.
Global O-RAN Near-Real-Time RAN Intelligent Controllers Market - Key Trends & Drivers Summarized
How Are Near-Real-Time RICs Transforming RAN Architecture in O-RAN Ecosystems?
O-RAN near-real-time RAN intelligent controllers (near-RT RICs) are pivotal components within open and disaggregated radio access networks. They manage and optimize RAN functions with latencies of under one second, enabling dynamic control over network behaviors such as interference mitigation, traffic steering, and load balancing. These controllers sit between the non-real-time RIC (in the service management and orchestration layer) and the distributed units or base stations, translating policy into adaptive action.
Near-RT RICs enable operators to deploy vendor-neutral applications (xApps) for controlling key RAN parameters, improving efficiency without vendor lock-in. They support service innovation by allowing third-party development of AI-driven control algorithms and decision engines. This architecture underpins the flexibility and cost-efficiency goals of the broader O-RAN initiative, which aims to break the dependence on closed, vertically integrated network equipment.
What Technological Capabilities Define the Competitive Edge of Near-RT RICs?
The core capability of near-RT RICs lies in their ability to process streaming data from the RAN and make decisions within tight timeframes. These decisions include adjusting transmission power, reallocating radio resources, or triggering handovers based on real-time traffic patterns. Advanced implementations integrate AI and machine learning models that continuously learn and refine network behavior based on observed data.
Key enablers include standardized interfaces such as E2, which allow the near-RT RIC to interact with radio units and distributed units from various vendors. Containerization and cloud-native architectures support scalability and deployment flexibility across private, public, and hybrid clouds. Security frameworks are also evolving to protect data flow and control integrity across multiple disaggregated vendors and applications.
Where Is Deployment Growing and Which Use Cases Are Leading Adoption?
Near-RT RIC deployment is gaining momentum in commercial and pre-commercial O-RAN networks, particularly in regions prioritizing vendor diversity and 5G network agility. Operators in the United States, Japan, and parts of Europe are testing near-RT RICs in dense urban environments and enterprise private networks. Use cases such as energy-efficient radio scheduling, mobility robustness optimization, and anomaly detection are driving initial xApp development.
Private 5G networks in manufacturing, defense, and utilities are adopting near-RT RICs to support deterministic service quality and autonomous control. As telcos seek to reduce total cost of ownership and increase spectral efficiency, near-RT RICs provide a programmable interface for ongoing network optimization. Collaborations between open-source communities, academic research groups, and RAN vendors are accelerating functional testing and interoperability validation.
Growth in the O-RAN Near-Real-Time RAN Intelligent Controllers market is driven by several factors…
Growth in the O-RAN near-real-time RIC market is driven by factors such as disaggregation trends in mobile infrastructure, rising demand for programmable and AI-driven RAN optimization, and increasing operator investment in open, flexible network architectures. The adoption of xApps tailored to specific RAN use cases is supporting modular innovation and vendor neutrality.
Standardization of interfaces such as E2 and RIC-to-xApp APIs is enabling broader ecosystem participation and faster deployment cycles. As 5G networks expand, the need to manage dense, heterogeneous radio environments is intensifying the role of intelligent control. Integration with cloud-native orchestration platforms and AI model hosting capabilities is further enhancing the utility and value proposition of near-RT RICs in open RAN deployments.
SCOPE OF STUDY:
The report analyzes the O-RAN Near-Real-Time RAN Intelligent Controllers market in terms of units by the following Segments, and Geographic Regions/Countries:
Segments:
Component (A1 Mediator Component, RIC Alarm System Component, RIC Message Router Component, Routing Manager Component, XAPP Framework for CXX Component, XAPP Framework for Go Component, XAPP Framework for Python Component, Other Components); Deployment (Centralized Deployment, Distributed Deployment)
Geographic Regions/Countries:
World; United States; Canada; Japan; China; Europe (France; Germany; Italy; United Kingdom; and Rest of Europe); Asia-Pacific; Rest of World.
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