Artificial Intelligence (AI) is rapidly transforming various sectors, including the energy industry, redefining processes and optimizing operational efficiency. It is therefore essential to understand how AI can integrate into this domain and what impact it may have on a key figure such as the energy manager. This thesis aims to achieve two main objectives: first, to explore the use of intelligent and customized chatbots to support and enhance the efficiency of energy managers; second, to develop a predictive maintenance model based on Machine Learning techniques to analyze the performance degradation of two photovoltaic (PV) plants, with a particular focus on progressive soiling and anomalies.