Integration of Building Information Modeling (BIM) with Artificial Intelligence for Real-time Cost Estimation in Megaprojects

Abstract

The increasing complexity of megaprojects has intensified the need for more efficient and accurate cost estimation systems within the construction industry. Conventional quantity surveying methods are often characterized by manual calculations, fragmented information management, and delayed cost reporting, which contribute to budget overruns and poor financial decision-making. Building Information Modelling (BIM) has improved digital coordination in construction projects by enabling integrated project visualization and automated quantity extraction. More recently, Artificial Intelligence (AI) technologies have been introduced into BIM environments to support intelligent data processing, automated classification, and predictive cost analysis. This study investigates the integration of AI with BIM for real-time cost estimation in megaprojects. A mixed-methods research design was adopted, involving comparative analysis of documented project case studies and semi-structured interviews with industry professionals. The findings reveal that AI-assisted BIM systems improve estimation efficiency, reduce manual errors, and enhance coordination between design and commercial teams. However, challenges relating to data standardization, interoperability, implementation costs, and workforce competence continue to affect adoption. The study concludes that AI-enabled BIM systems have significant potential to improve quantity surveying and commercial management practices when supported by appropriate digital standards and organizational readiness.