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AN L4 Digital Twin ensures maximum service reliability

URN C25.0.828
Topics AI (Artificial Intelligence), Autonomous networks, Digital twin

Enhance service quality through proactive network change emulation

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As autonomous networks evolve, CSPs are accelerating efforts to reach Level 4 (L4) automation. Yet, despite strong industry ambition, many CSPs still lack a clear, standardized method to assess their current automation maturity. Without this clarity, it becomes difficult to identify capability gaps, plan investments, or track progress toward L4 goals. This Catalyst addresses that challenge directly. It applies the TM Forum’s latest AN Level (ANL) assessment framework—including IG1252 methodology and GB1059 tools—to live networks for the first time. Developed in collaboration with industry partners, the tool evaluates performance based on high-value AN scenarios. It builds on the TM Forum’s 2024 IG1392 white paper and consolidates earlier pilots into a comprehensive, standardized approach. The Catalyst conducts end-to-end ANL assessment, combining self-evaluation, live network validation, and gap analysis. This three-part process helps CSPs establish a baseline, uncover bottlenecks, and plan realistic, data-driven automation roadmaps. Crucially, the assessment methodology doesn’t just measure performance—it links results to practical next steps that accelerate progress. CSPs and vendors collaborate throughout the project to co-validate results and share insight. The final report, approved by all participants, offers a reference model that can be reused across the industry. It also contributes directly to the TM Forum knowledge base, supporting broader adoption of ANL standards. With this Catalyst, CSPs gain more than a score, they gain a strategic lens on automation. The validated assessment process brings structure to complex transformation efforts and helps operators focus investment where it matters. In doing so, it lays the groundwork for scalable, systematic progress toward high-performance, low-touch, autonomous networks.

Team members

China Academy of Information and Communications Technology(CAICT) logo
Champion
China Mobile Communications Corporation logo
Champion
China Telecommunications Corporation logo
Champion
China Unicom logo
Champion
China Unitechs Co.,Ltd. logo
Huawei Technologies Co. Ltd logo
Indosat Ooredoo Hutchison logo
Champion
MTN South Africa logo
Champion
ZTE Corporation logo

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