Integrating Artificial Intelligence (AI) and Building Information Modeling (BIM) Technologies to Automate CO2 Emission Calculations and Support Low-Carbon Building Design: A Systematic Literature Review

The decarbonization of the Architecture, Engineering, Construction, and Operation (AECO) sector has increased the need to incorporate carbon metrics into design decision-making. This article presents a Systematic Literature Review (SLR), based on the PRISMA protocol, to investigate whether the automation of CO2 emission calculation combined with artificial intelligence has been used to support lower-impact design decisions in BIM-based building design. Searches were conducted in the Scopus, Web of Science, and ScienceDirect databases, considering articles published between 2021 and 2025, resulting in 2567 records. After duplicate removal and successive screening stages, 85 studies composed the final sample, classified into Core studies (BIM + CO2 + AI) and Base studies (BIM + AI, BIM + CO2, BIM + AI + Sustainability, and AI + CO2). The results indicate the predominance of partial integrations and limited representation of Core studies. Although 60% of the studies quantify carbon, only 39% use this quantification to propose, compare, or optimize design alternatives. The findings suggest that BIM + CO2 + AI integration has potential to support low-carbon building design but still requires greater standardization, interoperability, validation, traceability, and operational integration.