In just six years, China Mobile (CM) has been recognized for achieving Level 4 network autonomy, with real-time autonomous network and service monitoring which is improving user download speeds in congested areas by 50%, and cut network faults by 80%, according to STL Partners.
Associate Senior Analyst, David Martin, says such metrics are key for operators seeking cost reductions and efficiency gains, “More efficient networks mean you release capacity, improve customer experience, cut out costs and free up resources for more innovation.”
While developed markets automate to protect margins, emerging markets can gain equal advantage through early adoption, overcoming skills gaps and capital expenditure (CapEx) limits while navigating surging connectivity demand.
A fully autonomous network, by the TM Forum’s Level 0 to Level 5 framework, is still only on paper. Level 4, which CM achieved, provides self-healing telecom infrastructure and strongly autonomous behavior with minimal human involvement where required.
CM’s approach began with the resolution of obvious “pain points” in some specific domains, based on AI and machine learning to predict and fix faults before they occurred, and then scaled from single-domain to cross-domain AI network automation.
An Autonomous System Is a Network Operated by One Organization
Emerging market adoption of real-time autonomous network and service monitoring is building momentum, with high adoption in the Middle East and Africa. IDC’s Kitesh Bhayani states early applications such as predictive maintenance, intelligent traffic routing, and automated customer support as key drivers of efficiency.
Challenges persist though, from multi-vendor complexity and legacy system integration issues, to AI skills shortages and regulatory hurdles. Despite some operators partnering with universities or companies, such as TCS and Accenture, Bhayani stresses automation must adapt to local contexts.
Vendor partnerships are proving vital. Telstra International’s Wayne Lotter warns that “simplifying the vendor landscape is essential” for effective automation.
CM’s progress benefits from close cooperation with Huawei and ZTE on integration, even within proprietary systems – though this approach may not translate elsewhere. Ericsson’s Open RAN automation tools, for example, help automate multi-vendor deployments.
Automation also plays a role in resilience. In Southeast Asia, AI helps detect and respond to outages caused by extreme weather or infrastructure damage.
“You can pre-empt and detect outages… ensuring it’s business as usual and customers are none the wiser,” Lotter says.
AI-based energy management is a high-impact area, with even a 5–10% improvement in efficiency being considered cost-effective.
The consensus among experts is to “start small, scale fast.” Martin advises operators to view automation as a necessity, not a luxury, while Bhayani endorses a gradual “crawl, walk, run” approach.
Lotter adds that automation is about augmenting—not replacing—human capabilities. CM’s rapid rise from Level 1 to Level 4 shows that, with the right strategy, emerging market operators could close the gap with developed markets sooner than expected.
Looking ahead, the real-time autonomous network and service monitoring and expansion of autonomous networks and investment in AI 6G infrastructure could further accelerate capabilities, positioning operators to lead in expanding the autonomous networks market while sustaining self-healing telecom infrastructure for the future.
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