China Mobile and ZTE have developed a new \u201cDigital Employee\u201d to accelerate the move toward fully autonomous telecom networks. The solution acts as a central AI coordinator, managing multiple specialist agents to diagnose network faults, prioritise work orders, and optimise performance across multi-vendor, cross-domain environments.<\/p>\n\n\n\n
The Digital Employee combines a knowledge graph, graph neural networks, and large language models to analyse alarms, logs, performance data, and customer complaints in real time. This architecture allows it to identify root causes with high accuracy, understand fault propagation paths, and recommend temporary or permanent resolutions based on service impact, KPIs, and SLAs. Unlike traditional automation, it aligns technical actions with business outcomes and customer experience.<\/p>\n\n\n\n
In live trials across multiple Chinese provinces, the system demonstrated strong operational gains. It achieved over 90% root-cause identification accuracy, reduced mean time to diagnose faults from 15 minutes to around 3 minutes, lowered overall mean time to recovery by up to 11%, and cut on-site maintenance visits by 5%. In large-scale pilots covering tens of thousands of network elements, it also improved service continuity during severe weather events and reached automation rates as high as 95% for continuous upgrade and deployment processes.<\/p>\n\n\n\n
Beyond fault management, the Digital Employee continuously learns from each incident, generating daily operational insights and performance summaries. China Mobile and ZTE see this as a cornerstone capability for autonomous networks, enabling consistent operations, reduced reliance on scarce expert resources, and scalable automation. The solution is expected to be deployed nationwide across China by 2027 and has clear potential for adoption in global telecom markets and other industries requiring self-healing, AI-driven operations.<\/p>\n\n\n\n
Download the case study to learn how coordinated AI agents can streamline network operations, reduce manual intervention, and improve service performance.<\/strong><\/p>\n\n\n\n