This paper presents applications of artificial intelligence techniques to real-time circuit-switched network management. We focus on the problem of diagnosis making in order to detect and identify abnormal situations in the network. Two different approaches respectively based on expert system and neural trees are proposed. The methodologies underlying the two solutions are presented as well as the prototypes that have been developed. Finally, case studies leading to a comparison of both approaches are described.