AI-powered automation is reshaping how Mobile Network Operators (MNOs) handle radio access networks (RAN), especially in complex, multi-vendor environments. By adopting advanced AI solutions, MNOs are achieving self-managing and self-optimizing networks, significantly reducing manual intervention and operational costs.
RAN AI enables operators to optimize energy consumption, boost equipment performance, and enhance both fixed wireless and mobile speeds. Automated processes such as AI-driven cell coverage adjustments and dynamic anchoring improve service quality while lowering energy costs. For example, AI algorithms can identify underused network resources and automatically redistribute capacity to areas of high demand, ensuring a seamless customer experience.
Qualcomm Technologies leads this transformation by integrating Agentic and Generative AI into its RAN Automation Suite. This integration allows networks to interpret operator intentions, generate action plans, and perform closed-loop updates without human intervention. Businesses benefit from intent-based operations, where network changes are executed automatically based on high-level business goals rather than manual configuration.
Key advantages for businesses include:
- Streamlined network modernization: AI abstracts the complexity of different vendors and technologies, making upgrades and integrations faster and more efficient.
- Enhanced performance and efficiency: AI/ML algorithms continuously optimize network parameters, improving speed and reliability while reducing power usage.
- Autonomous management: Networks make real-time decisions, reducing downtime and minimizing the need for technical staff to resolve routine issues.
- Personalized services: AI can tailor network resources to specific customer needs, improving satisfaction and loyalty.
- Marketplace for automation tools: The development of intelligent controllers and rApp marketplaces allows operators to quickly adopt new automation capabilities as they become available.
Businesses leveraging AI-driven RAN automation can expect lower operational costs, improved service quality, and faster adaptation to market demands. As networks become more autonomous, companies can focus resources on innovation and strategic growth instead of day-to-day network management.
