Routing optimization in mobile telephony aims to enhance network efficiency and service quality by addressing complex and dynamic challenges such as call routing, handover management, load balancing, and energy consumption. Artificial intelligence (AI) and machine learning techniques are key to solving these problems, allowing for real-time, data-driven decisions that optimize resources, reduce latency, and ensure seamless communication. This paper explores various aspects of routing optimization, including cell site placement, radio resource allocation, quality of service (QoS)-based routing, and network security, highlighting AI’s crucial role in modern mobile networks.