Undersea cable incidents frequently disrupt global telecommunications, with a recent major cut between Asia and Europe significantly impacting network quality and customer experience. Network engineers often navigate diverse routing paths, including IX, Peering, and Transit services, but improper handling can exacerbate issues. Even after optimal rerouting, persistent service degradation, particularly at the application layer makes problem identification challenging. Manual performance analysis across platforms is labor-intensive and inefficient. AI in the network operations space offers a transformative solution. The AI continuously learns traffic behaviors, optimizes resource allocation, and prioritizes traffic based on Quality of Service (QoS) metrics to achieve better performance & resilience. GenAI is also introduced in the grand design, enabling intent-based interactions with the network. AI-driven innovations ensure consistent service quality, optimised operational costs, stronger customer trust, and more advanced automated network management. This approach addresses evolving telecommunications challenges, ensuring robust and reliable service delivery. Our catalyst explores AI-driven solutions to advance towards higher level of autonomous networks (AN Level-4/5). In the previous phase, it demonstrated three aspects: intent input via chatbot and interpreter, service decomposition and instantiation, service-to-resource management. The previous phase (Stage 1) focused on developing a reference architecture and realisation of intent-based Connectivity-as-a-Service (CaaS) orchestration. Stage 2, will focus on the full implementation of the design to achieve the endgame of AI-driven network operations for enhanced efficiency and automation.