NICT NTT Telefonica I+D The adoption of artificial intelligence (AI) in network management (NM) solutions is the way to resolve complex management problems arisen from the adoption of NFV, SDN, and network slicing technologies. The AINEMA framework, as discussed in this document, includes the functions, capabilities, and components that MUST be provided by AI modules and models to be successfully applied to NM. This is enlarged by the consideration of seamless integration of different services, including the ability of having multiple AI models working in parallel, as well as the ability of complex reasoning and event processing. In addition, disparate sources of information are put together with limited complexity, through the definition of a control and management service bus. It allows, for instance, to involve external events in NM operations. Using all available sources of information --- namely, intelligence sources --- allows NM solutions to apply proper intelligence processes instead of simple AI-based guesses. Such processes are highly based in reasoning and formal and target-based intelligence analysis and decision --- providing evidence-based conclusions and proofs for the decisions. This will allow computer and network system infrastructures --- and user demands --- to grow in complexity. The construction and maintenance of AINEMA-compatible components MUST consider the existence several mechanisms, which are extended beyond machine learning (ML). For instance, intelligent reasoning is a key aspect of AINEMA that MUST be taken into account by autonomic management components and solutions. It will provide enormous benefits to NM solutions by, for example, inferring new knowledge and applying different kind of rules (e.g. logical) to choose from several actions. While ML solutions work with data, so they only require to retrieve data from the network infrastructure, AINEMA modules MUST work in collaboration to the network it is managing. This makes the challenges arisen from intelligent reasoning essential for the evolution of NM. They will be addressed within the context of AINEMA.