With the rapid development of information technology, network security issues have increasingly become a global focus. Leveraging technologies such as big data analytics, machine learning, and deep learning, artificial intelligence (AI) can monitor and analyze network traffic in real-time, identify abnormal behaviors and potential threats, and thereby achieve proactive defense and rapid response. In cybersecurity, AI technologies are primarily applied in threat detection, vulnerability management, and incident response. AI-driven intrusion detection systems (IDS) and automated vulnerability scanning significantly enhance the accuracy and speed of detection and response, reducing delays and errors caused by human intervention. However, the application of AI in cybersecurity also faces challenges such as data privacy, algorithmic bias, and adversarial attacks. As AI technology continues to advance, its application prospects in the field of cybersecurity are broad, necessitating further research and optimization focused on intelligence, efficiency, and data privacy protection to build a more secure and reliable network environment.