Now Available: 2025 AI in the Mobile RAN

AI Integration: Reshaping Mobile Network Horizons

Artificial intelligence (AI) and Generative AI (GenAI) are fundamentally reshaping mobile Radio Access Networks (RANs), initiating a transformation poised to redefine the telecommunications landscape. We recently published our latest research brief, AI in the Mobile RAN: A Transformational Opportunity for Telcos, delving into how AI is optimizing network performance, automating complex operations, and unlocking entirely new revenue possibilities for operators navigating the 5G-Advanced and 6G eras.  

How is AI evolving beyond basic automation in the RAN? What architectural shifts are essential for an AI-native future? Can the RAN edge truly become a new frontier for monetization? What role do Open RAN and the RAN Intelligent Controller (RIC) play? Is the future of RAN compute dominated by GPUs or specialized ASICs? We explore these critical questions and more in our comprehensive research brief. Download the report now to get the full analysis.

AI's Ascent: From Optimization to Native Integration

This research brief offers a detailed assessment of AI's growing influence on mobile RANs, charting the necessary architectural evolution, the significant opportunities and hurdles facing telcos, and the shifting vendor ecosystem. It is designed to guide strategic decision-making as operators plan their transition towards AI-native networks.  

The telecom industry's quest for greater efficiency, lower latency, and enhanced performance is being supercharged by AI. Moving beyond early Self-Organizing Networks (SONs), the industry is now embracing AI-native architectures where intelligence is woven into every network layer and domain. This report examines the accelerating drive towards AI-native RAN, highlighting how networks can meet future demands by covering:  

• The evolution from rule-based SON to adaptable, AI-native RANs.  

• Rethinking network architecture: embracing openness, O-RAN, and the RIC.   

• Key AI Use Cases: AIOps for zero-touch operations, AI for RAN processing/control, and AI at the Edge RAN for monetization.   

• The dynamic role of GPUs versus ASICs and FPGAs in AI-optimized RAN computing.  

• The potential of Cloud vs. Distributed AI compute, including Federated Learning.  

• The AI Revolution in Operations & Management: Zero-Touch Networks and the impact of GenAI/LLMs.  

• Market Dynamics: Balancing AI opportunities (efficiency, new business models) with challenges (vendor lock-in, data privacy, skills gap).  

• And much more…  

AI: The Engine for Next-Generation Mobile Networks

AI is no longer a future concept for RAN; it's a present-day imperative, essential for the demands of 5G-Advanced and 6G. Across the mobile network, AI technologies are forcing a strategic rethink of operations, resource management, and service delivery. From the physical layer processing to network-wide orchestration, AI is transforming the RAN. Innovations in AI-driven traffic management, energy efficiency, predictive maintenance, and intelligent control loops via the RIC are paving the way for next-gen mobile networks. Furthermore, the vision of leveraging RAN infrastructure for edge AI services (AI-and-RAN / AI-on-RAN) presents a significant opportunity for telcos to create new value and revenue streams beyond connectivity. Industry collaborations, like the AI-RAN Alliance, are crucial in accelerating this integration and fostering innovation.  

Navigating the AI Integration Challenge: Efficiency, Complexity, and Trust

Despite the immense opportunities, the path to fully realized AI-native RANs involves navigating significant challenges. Obstacles such as vendor lock-in, the inertia of legacy systems, data privacy and security considerations, a shortage of AI expertise within telco workforces, and the need for substantial architectural innovation present considerable hurdles. The complexity of orchestrating AI models alongside real-time RAN functions, ensuring quality of service, managing data effectively, addressing potential regulatory concerns, and demonstrating clear ROI adds further layers to the challenge. Successfully integrating AI requires not only technological advancement but also strategic planning, investment in skills, robust security measures, and fostering trust in AI-driven operations.  

Download the AI in the Mobile RAN Research Brief

To access our in-depth analysis and strategic recommendations regarding AI in the Mobile RAN, including insights for operators navigating this transformation, download the full research brief.

This report is an essential resource for anyone tasked with understanding and navigating the transformative impacts of AI on mobile network infrastructure and strategy. Grab your copy now! 

To discuss your organization’s specific needs or to participate in future AvidThink reports, contact us at [email protected].