The paper is focused on an ongoing project funded by the Emilia-Romagna region and aimed at the creation of a new workflow finalizing digital data from integrated survey towards an “adaptive” Building Information Modeling (BIM). The project AIM-eBIM—Adapted Information Management for existing Buildings Information Modeling brings together regional research laboratories and companies to pursue industrial research topics towards a greater deployment of digital tools. Digital surveying has triggered huge potential for innovation, but generating new challenges in managing and using large amount of data, often unused. The quantity of surveyed data to document built or Cultural Heritage often does not correspond to the quality or reliability of information. Moreover, parametric modeling of existing heritage through BIM is becoming as pervasive as necessary, considering regulatory trends. However, these tools can be ineffective from the point of view of users (professionals, companies) who must deal with such complexity. The challenge is to bring discretization (and simplification) processes on source data toward an easier informative integration into BIM models, by facilitating and enhancing interpretation needs. In this direction, Artificial Intelligence (AI) algorithms are part of the process. The adapted informative implementation of parametric models is based on digital source data (laser and photogrammetry) segmentation by AI on specific topics (documentation, analysis, monitoring, conservation, project) and criteria (materials, techniques, components, structures).