Artificial Intelligence is increasingly becoming integral to Radio Access Network (RAN) deployments, with AI RAN poised to be a transformative force in the evolution of mobile networks.
AI RAN is projected to account for roughly one-third of the global RAN market by 2029 — a significant shift in how operators design, manage, and optimize networks, according to the newly released AI RAN Advanced Research Report (July 2025) from Dell’Oro Group.
A Maia Research report estimates the global RAN market at $16.3 billion in 2024, with a compound annual growth rate (CAGR) of 8.7 percent through 2029.
Market Data Forecast says the global RAN market will reach $25.8 billion by 2029 from $11.27 billion in 2023 — a CAGR of 8.35 percent.
Mordor Intelligence forecasts C‑RAN growing from $13.85 billion in 2024 to $41.6 billion by 2029, at a notably high CAGR of 24.6 percent, driven by 5G rollouts, virtualization, and IoT demand.
MarketsandMarkets predicts Open RAN increasing from $2.8 billion in 2024 to $20.9 billion by 2030, at a 39.4 percent CAGR.
Focus Shifts to D-RAN and 5G Optimization
In the immediate term, AI RAN investments are focused on Distributed RAN (D-RAN) architectures, single-purpose deployments, and enhancing existing 5G network performance. Rather than targeting new revenue streams, operators are prioritizing operational efficiency, network optimization, and energy savings.
“Near-term priorities are more about efficiency gains than new revenue streams,” said Stefan Pongratz, Vice President at Dell’Oro Group.
AI RAN is widely seen as a tool to improve user experience, reduce energy consumption, and accelerate automation — critical factors for network sustainability and long-term competitiveness. However, skepticism remains around its ability to reignite revenue growth, which has largely stagnated since the 4G era.
Global Operator Initiatives
Several major telecom operators are already moving ahead with AI RAN deployments as part of broader network modernization efforts.
Vodafone is leveraging AI for automation, dynamic spectrum management, and energy efficiency, working with vendors like Nokia, Ericsson, and VMware.
NTT DOCOMO is integrating AI for traffic prediction and orchestration through its leadership in the 5G Open RAN Ecosystem.
Deutsche Telekom is trialing AI-driven self-healing capabilities and energy optimization with Juniper Networks and VMware.
In the U.S., AT&T is deploying AI RAN features for traffic prediction and real-time control using Open RAN Intelligent Controllers (RICs), supported by Nokia and Microsoft Azure.
China Mobile has developed its i-Edge AI RAN platform for adaptive beamforming, power savings, and Massive MIMO optimization.
Reliance Jio is embedding AI across its Cloud-RAN infrastructure and future 6G initiatives through an in-house AI/ML stack.
Across Africa, MTN Group is rolling out AI RAN capabilities with support from Tech Mahindra and Rakuten, focusing on coverage expansion and cost-effective rural connectivity.
Telefonica is testing AI-driven Open RAN features in collaboration with NEC and Altiostar to manage traffic and congestion.
Orange is deploying AI-based Self-Organizing Networks (SONs) in France and Spain and participating in the AI4Green initiative to enhance energy efficiency.
Strategic Adoption Pathways
The Dell’Oro report underscores that while AI RAN may not be a short-term growth engine, it is a strategic imperative for operators dealing with increasing data demands and mounting energy concerns. Integrating virtualization, intelligence, and Open RAN (O-RAN) technologies into long-term strategies reflects the industry’s focus on scalable infrastructure and sustainable cost structures.
Vendor Positioning
Initial AI RAN deployment is expected to be hardware-centric, driven largely by AI enhancements to existing infrastructure. This plays to the strengths of the top five global RAN vendors — who controlled about 95 percent of global RAN revenue in 2024 — as they are well-positioned to lead with AI-based software enhancements built into their platforms. Their existing market dominance gives them a natural advantage in this transition.
Forecasting the Future
The report segments AI RAN growth by location, tenancy models (single vs. multi-tenant), technology stack (virtualized vs. non-virtualized), and geography, providing a nuanced roadmap for aligning operator and vendor investments with the most promising areas for efficiency gains and strategic impact.
Outlook: AI RAN as a Catalyst for Automation
As mobile networks become more complex and data-intensive, AI’s role in resource optimization, predictive maintenance, and real-time performance tuning is becoming indispensable. While not yet a driver of new revenue, AI RAN marks a major step toward autonomous and self-organizing networks (SONs), potentially leading to significant reductions in operational expenditure (OPEX) over time.
Baburajan Kizhakedath
