With the rapid development of information technology, the issue of network security has become increasingly prominent, and has become an important factor affecting national security, enterprise development and even personal privacy. The traditional means of network security protection are inadequate to cope with the increasingly complex and unpredictable network threats. Therefore, the use of artificial intelligence technology to evaluate the network security situation has become an innovative and effective method. The significance of this study is to propose a new network security situation assessment algorithm based on artificial intelligence. This algorithm can effectively integrate and analyze large amounts of network data, detect potential threats in time, and provide accurate security assessments to help network security managers make faster and more accurate decisions. Advanced artificial intelligence technologies such as deep learning and pattern recognition will be used in the study to comprehensively analyze multi-source data such as network traffic, user behavior and system logs. By training the algorithm model to identify and predict network security threats, the dynamic assessment of network security situation is realized. It can be seen from the experimental data that the test parameters of the network security situation assessment algorithm of artificial intelligence are the assessment accuracy rate, the processing scheme accuracy rate, the improvement scheme accuracy rate and the data reporting accuracy rate, and the four data are above 95%. Therefore, it is not difficult to find the hidden potential of artificial intelligence network security situation assessment algorithm in practical application.