With the rapid development of digital technologies in the energy sector, the modernization of relay protection and automation systems (RPA) that ensure the stable and reliable operation of the power system is becoming increasingly important. One of the most promising areas is the introduction of artificial intelligence (AI) methods, which can improve the adaptability, accuracy, and speed of RPA systems. The energy transition and the integration of the Baltic countries into the pan-European ENTSO-E network are accompanied by an increase in the share of renewable energy sources and a complication of power system operating modes. In these conditions, the relevance of introducing adaptive intelligent RZA systems capable of responding quickly to power flow instability and generation variability is increasing. The article presents an analysis of the application of AI methods to improve the reliability of relay protection and automation in transmission networks. It also demonstrates an example of using an interpretable model based on a decision tree to classify emergency situations, taking into account the variable share of renewable energy sources. The results of the study emphasize that the introduction of AI into relay protection and automation systems can significantly increase the reliability and stability of regional power systems in the long term. This work represents the first step toward further research in this area.