Management of 5G networks is a daunting task, as they are expected to support high bandwidth rates, ultra-low latencies, and high reliabilities. To meet these requirements, network infrastructures must automatically scale resources as a function of the customer demand. The autonomous and dynamic management of the 5G network infrastructure is not trivial, as solutions must account for the radio access network, the data plane traffic, the wavelength allocation, the network slicing, and the orchestration of the network functions. In addition, the management of the network must consider the federation among administrative domains. Since 5G networks are markedly more dynamic than previous generations, artificial intelligence/machine learning (AI/ML) solutions are strong candidates to learn and take quick provisioning decisions to adapt to the rapidly changing network conditions. This chapter analyzes state-of-the-art solutions for 5G network management, comparing AI/ML approaches with traditional ones. It provides a technological overview of the existing standards and solutions, as well as directions for the integration of AI/ML in 5G networks.