The rapid evolution of network architectures has introduced new security challenges, necessitating advanced network protection solutions. This chapter explores the evolution of network security, from traditional firewalls and intrusion detection/prevention systems (IDS/IPS) to modern AI-driven network security solutions. It examines key threat detection approaches, including signature-based, anomaly-based, policy-based, and reputation-based detection, and how AI and machine learning (ML) have transformed network security by enabling automated, adaptive, and real-time threat response mechanisms. The chapter also discusses the future of AI in network security, emphasizing its role in predictive analytics, behavioral analysis, and automated response systems. Additionally, it highlights the challenges and risks associated with AI-based security, such as adversarial attacks, data quality limitations, and integration issues, underscoring the need for continuous advancements in AI-driven defense strategies.