Developing AI-Driven BIM Frameworks for Sustainable Infrastructure Projects

Abstract

This research looks at how Artificial Intelligence (AI) can be used together with Building Information Modeling (BIM) to promote sustainable infrastructure development. These frameworks depend on machine learning, deep learning and predictive analytics to minimize energy, improve performance of materials and look after the entire lifecycles of buildings during construction projects. Researchers used surveys on 150 building professionals and carried out semi-structured interviews with another 15 experts in the industry to gather their views. SPSS v26 results pointed to a strong relationship between AI-BIM integration and notable sustainability measures, for example, risk distribution (r = 0.712), how much material is used (r = 0.698) and project timeline (r = 0.675). Results from the regression model indicate that AI and BIM work together to contribute a major 59.2% share to overall sustainability performance. Although these benefits exist, challenges such as compatibility problems, safety risks and expensive implementation were discovered. Therefore, the study suggests a number of strategic tips concentrating on adopting standards, giving more professional training and using digital twin technologies to help AI-BIM become more useful on a larger scale. The results support the belief that AI BIM can shape sustainability in construction by raising efficiency and reducing natural footprints.