O-RAN Market Moves Toward AI-Native 6G as Operators Seek Greater Control Over Network Infrastructure

July 17, 2026 - The O-RAN market is moving beyond its original focus on separating radio hardware from software. In 2026, industry attention is shifting toward AI-native network control, cloud-based processing and future 6G architecture capable of supporting communications, computing and environmental sensing on shared infrastructure. DataM Intelligence estimates that the global O-RAN Open Radio Access Networks market reached US$2.92 billion in 2024 and will reach US$45.70 billion by 2032, expanding at a 41.03% CAGR.

Request Executive Sample | Market Intelligence: https://www.datamintelligence.com/download-sample/o-ran-open-radio-access-networks-market?kailas

2026 Official Developments in AI-RAN, O-RAN and 6G Architecture

The O-RAN ALLIANCE completed Specification Release 5 in June 2026. The release introduced enhancements to AI and machine-learning workflows connecting the Non-Real-Time RAN Intelligent Controller and Near-Real-Time RAN Intelligent Controller. It also added a D2 interface for carrier aggregation across distributed units and expanded support for massive-MIMO optimisation.

At Mobile World Congress 2026, Nokia reported successful functional testing of its anyRAN software on NVIDIA's accelerated AI-RAN platform with T-Mobile US, Indosat and SoftBank. The companies demonstrated radio and AI workloads operating on shared computing infrastructure, indicating that AI-RAN is progressing from isolated laboratory projects toward operator validation.

Nokia and Orange subsequently announced an AI-RAN collaboration covering predictive radio optimisation, spectral efficiency, energy performance and integrated sensing communication. The initiative will examine how radio infrastructure can support sensing-related services while establishing a software-based migration path from 5G to 6G.

SoftBank also open-sourced a Dynamic Scoring Framework from its AITRAS Orchestrator in February 2026. The technology is designed to allocate AI and RAN workloads across multiple computing clusters according to resource availability and operational requirements.

From Open Interfaces to Intelligent Network Control

The first phase of open radio access networks concentrated on open fronthaul, virtualised baseband software and multi-vendor radio integration. The emerging phase adds intelligence that can decide how spectrum, compute capacity and network energy should be used.

A RAN intelligent controller provides the programmable layer through which applications can optimise network behaviour. However, the effectiveness of these applications depends on where models are trained, deployed and executed.

Models supporting long-term capacity planning can operate centrally, where larger datasets and computing resources are available. Applications controlling scheduling, interference or traffic steering may need to operate closer to the radio network to meet strict latency requirements.

This creates an architectural balancing act. Centralised models can access wider network context, while edge-based models can respond more quickly. Operators must also account for model-update governance, accelerator cost, data localisation, energy consumption and the risk that one model may negatively affect another network objective.

Request a Customized Report According to Your Business Strategy: https://www.datamintelligence.com/customize/o-ran-open-radio-access-networks-market?kailas

Roles Within an AI-Enabled O-RAN Architecture

The principal architecture layers perform different operational functions:

- Non-Real-Time RIC: This layer hosts rApps and supports policy management, model training, analytics and network optimisation operating over periods longer than one second. It can evaluate historical and network-wide information before providing policies or AI models to faster control layers.

- Near-Real-Time RIC: This layer hosts xApps that control or optimise radio resources through the E2 interface. Its control loops typically operate between approximately 10 milliseconds and one second, making it suitable for traffic steering, interference management, mobility and selected energy-saving decisions.

- Cloud and orchestration layer: The Service Management and Orchestration framework and O-Cloud coordinate infrastructure, software deployment, telemetry and lifecycle management. Cloud-native implementation can improve resource flexibility, but carrier-grade latency, resilience and operational visibility must be maintained.

- Radio unit and open-fronthaul layer: Radio units transmit and receive wireless signals while connecting to distributed units through standardised fronthaul interfaces. Multi-vendor value depends on conformance testing, timing accuracy, synchronisation and consistent performance under commercial network loads.

Growth Drivers and Commercial Counter-Risks

Operators are evaluating O-RAN to increase supplier choice, accelerate software innovation and improve operator network sovereignty. Open interfaces can reduce dependence on a single equipment architecture, while RIC applications can support automated optimisation and more targeted energy management.

Energy reduction is becoming a significant application area. O-RAN specifications now include use cases covering radio-unit power optimisation, carrier and cell controls, and coordination with external power sources.

The commercial case is not automatic. Multi-vendor networks require extensive testing across radios, distributed units, centralised units, cloud infrastructure and management platforms. Integration, software upgrades, fault identification and accountability can become more complex when several suppliers contribute to one service.

Cybersecurity requirements also expand as the network exposes additional interfaces, applications and cloud components. Security controls must address xApps, rApps, model supply chains, certificate management, APIs, open fronthaul and the possibility of manipulated network data.

Total cost of ownership must therefore include more than equipment prices. Operators must account for systems integration, testing, accelerated computing, energy consumption, cloud operations, application lifecycle management and long-term support.

Decision-Useful Market Segmentation

DataM Intelligence segments the market by offering, component, deployment, frequency band and end user. Offerings include hardware, software and services, while components include the RIC, radio units, distributed units and centralised units.

Commercial strategies should further distinguish:

- Public, private and hybrid cloud-native RAN deployments.
- Sub-6 GHz, millimetre-wave and future 6G frequency requirements.
- Greenfield networks from brownfield modernisation programmes.
- Public mobile operators, private industrial networks and government infrastructure.
- Open-fronthaul projects from wider AI-native RAN transformation.
- Network-optimisation applications from sensing and edge-AI workloads.

Country Opportunity Outlook

The United States is progressing through large-scale network modernisation and AI-RAN validation. AT&T reported further Open RAN readiness work in March 2026 and demonstrated AI-native link adaptation on an Intel-powered Cloud RAN platform with Ericsson.

Japan remains an important commercial reference market. NTT DOCOMO and SK Telecom published 2026 requirements for evolving vRAN toward AI-RAN, while SoftBank is developing shared AI and radio-computing infrastructure through AITRAS.

Germany and wider Europe combine operator trials with strong priorities around infrastructure sovereignty, sustainability and interoperability. Deutsche Telekom demonstrated an in-house service-management platform and rApps for AI-enabled Open RAN management at MWC 2026, while Orange is assessing AI-RAN for sensing and predictive optimisation.

India is positioning virtualised and open RAN within its longer-term 6G strategy. Department of Telecommunications discussions in 2026 highlighted open and virtual RAN architectures as enablers of flexible future networks, while India and Germany identified Open RAN, 6G, telecom AI and cybersecurity as areas for bilateral cooperation.

Purchase Corporate License | Market Intelligence: https://www.datamintelligence.com/buy-now-page?report=o-ran-open-radio-access-networks-market?kailas

Strategic Company Profiles

1. AT&T - operator lens: AT&T, a DataM-listed participant, is pursuing an open, programmable network while testing multi-vendor radios, cloud-based RAN and portable AI functions.

2. Nokia - network OEM lens: Nokia, also identified by DataM, is combining O-RAN-compatible radios, cloud-native anyRAN software and NVIDIA-accelerated AI infrastructure to create an upgrade path toward AI-native 6G.

3. AWS - cloud-platform lens: AWS provides cloud architecture for RIC, centralised and distributed network functions, observability and resource orchestration, positioning cloud infrastructure as an operating layer for programmable RAN.

4. NVIDIA - semiconductor and accelerated-computing lens: NVIDIA's AI Aerial platform combines accelerated hardware, libraries and development tools for AI-RAN and 6G research, simulation and commercial deployment.

"The O-RAN market is moving from interface openness toward programmable network intelligence," said a DataM Intelligence spokesperson. "The next competitive phase will be determined by who can govern AI models, integrate multiple suppliers and deliver carrier-grade performance without losing control of cost, security or operational responsibility."

The transition to AI-native radio networks will not eliminate the need for disaggregation and interoperability. It will make those foundations more important as operators prepare for sensing, distributed computing and software-defined 6G services.

DataM Intelligence provides customised operator and vendor benchmarking, country-readiness analysis, RIC application mapping, cloud-RAN architecture assessment, sovereign-infrastructure evaluation and O-RAN deployment-roadmap intelligence for organisations assessing the next phase of open and AI-native network infrastructure.

Read Exclusive Report Description: https://www.datamintelligence.com/research-report/o-ran-open-radio-access-networks-market

Contact Us:
Sai Kiran
Business Development Manager
DataM Intelligence 4market Research LLP
6th Floor, M2 Tech Hub, Lalitha Nagar, Habsiguda,
Secunderabad, Hyderabad, Telangana 500039
USA: +1 877-441-4866
Email: Sai.k@datamintelligence.com

About DataM Intelligence
DataM Intelligence is a global market research and business intelligence firm delivering actionable insights across healthcare, pharmaceuticals, chemicals, energy, technology, food, and industrial sectors. Through syndicated reports, custom research, consulting, and competitive intelligence services, the company helps organizations identify growth opportunities, navigate market challenges, and make informed strategic decisions in over 50+ countries worldwide.

This release was published on openPR.