AI MODEL RECOMMENDATION BASED ON SYSTEM TASK ANALYSIS AND INTERACTION DATA

In a first aspect of the invention, there is a computer-implemented method including: generate, by a processor set, an interaction usage graph based on user interaction data on user interactions with an analytical system user interface; generate, by the processor set, an interaction embedding model in a vector space based on the interaction usage graph; determine, by the processor set and based on the interaction embedding model in the vector space, a similarity of a portion of the interaction embedding model that corresponds to a particular analytical task among the user interactions with the analytical system user interface with a particular machine learning model from a set of one or more machine learning models; and output, by the processor set, to the analytical system user interface, an indication of the particular machine learning model.