Autonomous AI Decision-Making System for National Mobile Network Resilience and Failure Prevention

This technical whitepaper presents a purpose-built autonomous AI decision-making system designed to enhance resilience and failure prevention in national-scale mobile telecommunications networks. The proposed system operates as a network-wide decision engine capable of continuously monitoring network behavior, predicting instability, identifying root causes of degradation, and autonomously executing corrective actions across radio access, transport, and traffic layers without human intervention. Unlike existing self-organizing or analytics-based solutions, the architecture is expert-informed and domain-specific, embedding operational knowledge derived from experienced telecommunications engineers into machine-interpretable decision logic. The system evolves through operational feedback, retaining validated resolutions and incorporating novel failure patterns over time, thereby transforming mobile networks from reactive infrastructures into self-governing, predictive national assets. The proposed approach addresses critical infrastructure vulnerabilities associated with large-scale mobile networks and is particularly relevant to geographically distributed national environments with high dependency on telecommunications for public safety, economic continuity, and emergency response.