Artificial Intelligence (AI) has become a transformative force in the field of networking, enabling enhanced efficiency, automation, and adaptability across diverse network infrastructures. This paper examines the integration of AI techniques, such as machine learning, deep learning, and natural language processing, to optimize network performance, automate configuration, and predict potential failures. AI-driven solutions are reshaping areas like traffic management, security threat detection, anomaly detection, and resource allocation. Additionally, AI facilitates the evolution of self-healing and self-organizing networks, paving the way for robust and resilient communication systems. The implementation of AI in networking also supports the development of intelligent edge computing and 5G/6G networks, ensuring low latency and improved quality of service. While AI offers numerous advantages, challenges such as data privacy, algorithm transparency, and computational complexity are explored, along with strategies to mitigate these issues. This study underscores the transformative potential of AI in advancing network technologies and achieving smarter, more efficient networking systems.