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Make ANL4 real

URN C25.5.862

Topics AI (Artificial Intelligence), Autonomous networks, Digital twin

A high value scenario that qualify for AN L4 attributes that has a high business impact to the industry.

Project companies

As customer needs grow more complex, autonomous networks (AN) are gaining momentum, driven by key factors: the CSP’s urgent need to cut operational costs by reducing manual intervention (to lower errors); escalating network complexity from 5G, IoT, and SDN/NFV, making manual management impractical; and rising user demands for seamless, high-performance, low-latency services requiring proactive issue resolution. This Catalyst puts forward an agentic-AI solution that exhibit the self-X capability that delivers zero-X experience. Leveraging AI, digital twins, and agentic AI-powered automation, its focus goes beyond task automation: it aims to reimagine network operations, enabling them to anticipate issues, respond with intelligence, and deliver more effective customer service. With this ANL4 solution, it enhances operational efficiency and productivity by reducing reliance on high-skill experts and minimizing manual efforts. In doing so, it enables CSPs to resolve complex issues more quickly and deliver consistently superior service The Catalyst demonstrates how ANL4 can deliver measurable improvements to service operations, with clear impact on customer experience and business results. For Agentic AI-based Intelligent Fault Management value scenario, the estimated business outcome is reducing MTTR by 40% for RAN scenario, cutting data loss by 20% and projecting annual customer complaint volume by 20%. In another value scenario, as explained by Luthfi Auzan, VP - Head of Operations Transformation & Analytics at Indosat Ooredoo Hutchison (IOH): "Importantly, the architecture enables new services. For example, the project shows how 'latency-as-a-service' can be launched using a transport-layer digital twin. This offering alone has the potential to generate a few million dollars in new B2B revenue annually. This Catalyst offers a model for integrating GenAI into daily workflows, bridging the gap between intent and action. Importantly, it enhances service operations with robust traceability and control—equipping teams to work faster, with greater confidence, and with a clearer view of business impact. As CSPs strive for greater autonomy and efficiency, this initiative demonstrates how ANL4 solution could be realized in their daily network operations.