In this thesis, I investigate the transformative role of artificial intelligence (AI) in network traffic analysis, highlighting how AI technologies enhance the monitoring and management of network data. As networks grow increasingly complex, traditional methods fall short in providing the efficiency and security needed for effective traffic management. I argue that AI's capabilities in pattern recognition and anomaly detection significantly improve network security and performance. The findings are structured into three main sections: the evolution and definition of AI technologies, an analysis of AI's impact on network security and performance, and case studies demonstrating successful AI implementations across various industries. The conclusion reiterates the importance of AI in modern network management and suggests directions for future research.