BIM (Building Information Modeling) is a disruptive technology that has changed the AEC industry (Architecture, Engineering and Construction) scenario, which has been growing worldwide, generating very effective solutions for the sector. In Brazil, this growth has been driven mainly by government actions through decrees and measures aimed at spreading BIM throughout the national territory. Thus, the market share that has not yet implemented this process is in a hurry to do so, and it is exactly at this point that many professionals, companies and agencies make mistakes, as they implement other processes without knowing its bases and prescriptions. It is in this context that carrying out studies such as this one becomes necessary. The main goal of this work is to generate a prioritization list of the main risks associated to BIM implementation in Brazilian public agencies. Such prioritization is based on the literature, on account of it seeking the most representative risks in the international context through a systematic mapping of the literature. These risks are submitted to a team involved with implementation processes in a representative body responsible for implementing this process in Brazil. Thus, a risk characterization is generated according to two aspects: likelihood of occurrence and impact. These data are submitted to the fuzzy rule-based inference system. Hence, through fuzzy logic, the list of prioritizations of the main risks linked to BIM adoption in the context of public agencies is generated. Using fuzzy modeling through subsystems to assess the criticality of risks related to BIM implementation is considered an innovation, which marks the originality of this article. The first three risks of the generated prioritization list are inadequate relevant knowledge and experience, interoperability issues and cultural resistance, all strongly interconnected. As a scientific contribution, this study demonstrates the themes to be initially solved in the Brazilian context for the elimination of its main obstacles. It also serves as a reference to countries that are in the same stage and context of implementation. Data like this tend to scientifically support the AEC industry and make BIM development, combined with public policies, able to reach maturity levels already presented by developed countries.