In this presentation we would like to present the advantages and challenges of using the deep reinforcement learning for closed loop powertrain control algorithms. The powertrain state feedback control functions have to consider a huge variety of environmental conditions. The way to develop and customize this new generation of control functions will change our traditional system and software process. The use of artificial intelligence and in particular of deep reinforcement learning techniques will speed up the development and improve the performance and contribute to higher efficiency.