Huawei Unveils Autonomous Network Tech

The push for network autonomy is driven by the increasing complexity of telecom systems, especially with the advent of 5G and the development of 6G. Huawei's approach is centered on its "Telecom Foundation Model," an AI model trained on the company's extensive telecommunications expertise to power intelligent applications for network management. This model underpins the ICNMaster solution, providing what Huawei calls "role-based copilots" and "scenario-based agents" to assist network engineers. A key technology integrated into ICNMaster is the digital twin, which creates a virtual replica of the physical network. This allows for simulations and proactive identification of potential issues, like signaling storms, before they impact live services. This shift from reactive to proactive maintenance is a core goal of moving towards higher levels of network autonomy. The industry standard for measuring network automation is a five-level scale from the TM Forum, with Level 4 representing a significant leap where the system can autonomously detect, analyze, and resolve issues without human intervention. Most telecom operators are currently at Level 2 or 3, making the transition to Level 4 a major industry focus. Huawei's ICNMaster is designed to help operators make this jump. In a practical deployment with China Mobile in Zhejiang, Huawei's ICNMaster demonstrated significant efficiency gains. The system's intelligent agents reduced the average handling time for core network alarm tickets from 90 minutes to just 12, an 87% improvement. Similarly, the time to process customer complaint tickets dropped from 14.6 hours to 5.2 hours, a 64% increase in efficiency. The move to Level 4 autonomy offers substantial benefits for telecom operators, including reduced operational expenditures, improved network reliability, and faster delivery of new services. Some operators have seen a 15% drop in energy usage in their wireless networks after implementing Level 4 automation. Both Huawei and its main competitor, Ericsson, are recognized as leaders in the 5G core network automation and orchestration market. While both leverage AI and machine learning, Huawei emphasizes its end-to-end intelligent O&M and disaster recovery solutions using digital twins. Ericsson, on the other hand, strongly focuses on dynamic network slicing, which allows for the creation of multiple virtual networks with specific qualities on a shared physical infrastructure. The commercial deployment of Level 4 autonomous networks began to pick up in 2025. Huawei has been actively involved in these deployments, with its ICNMaster solution being used by 14 leading operators worldwide as of early 2026. This push towards highly autonomous networks is seen as essential for managing the complexity and unlocking the full potential of 5G-Advanced and future 6G services.