The volume of data generated by the various Supply Chain Management actors is considerable, the extraction, processing and analysis of this data becomes a priority for decision makers to better understand the origin of problems that sometimes cause disruptions in the decisionmaking process. At the same time, companies find themselves with increased competition, to persist, decision makers must act quickly by analysing their own data and those coming from outside their businesses. Traditional methods have shown their limits in terms of exploration and interpretation of this growing volume of data. The aim of this paper is to highlight the new applied methods of Artificial Intelligence in Supply Chain Management functions, we will identify the most well-known Machine Learning techniques and review the applications of Machine Learning algorithms in Supply Chain Management