Energy systems are under a profound transformation powered by the increasing penetration of renewable energy sources and the decentralization of electricity markets into local communities, in which the prosumer plays a fundamental role. As a result, the creation of Renewable Energy Communities (RECs) is becoming popular, especially in Europe, allowing their members to reduce electricity consumption from non-renewables, as well as to locally produce, store and exchange energy among themselves. This work introduces a REC management system using Artificial Intelligence/Machine Learning (AI/ML) techniques for the electricity consumption forecast. The obtained results of the simulated scheme show that, with the use of these techniques, the system is able to decrease the electricity bill of the REC as well as the energy consumption from the distribution grid.