Authors: Alberto Sainz Dalda (BAERI/LMSAL)

This session will start with a critical review of the usage of machine learning (ML) and data assimilation (DA) in Heliophysics – beyond Space Weather prediction. First, we should wonder if we need these techniques to make science or we are using them because it is just cool to do it. If we really need to use these advanced techniques, then we will discuss the needs of the solar community, how we may use them more easily and frequently, and how we can make them part of the toolbox of our everyday job.  Through the brief review of some tools already available and some results already published, we will debate about the present and the future of using ML and DA to solve general questions or problems in Heliophysics. We will pay especial attention to the efforts that the Academia and the scientific institutions, especially observatories and numerical model incubators, may consider to facilitate the usage of ML and DA techniques. Thus, at the end of this session, we will create a list of suggestions and strategies to be eventually addressed to these institutions to make ML, DA and AI tools feasible and available for the community.