BIM and AI in Early Design Stage: Advancing Architect–Client Communication
Omar Bagasi, Nawari Nawari, Adel Alsaffar
Abstract
The integration of Building Information Modeling (BIM) and Artificial Intelligence (AI) is reshaping the architecture, engineering, and construction (AEC) industry, particularly by bridging two critical phases: the early design stage and architect–client communication. This paper proposes a new AI-BIM framework that aims to enhance architect–client communication and streamline feedback during early design stages. Traditional methods often fail to convey complex design ideas clearly, leading to misinterpretations and inefficiencies. The proposed framework combines real-time BIM visualization with AI-driven generative design and large language models (LLMs) to facilitate better understanding and collaboration. Observations from case studies suggest improvements in iterative feedback processes, greater alignment between client needs and design outputs, and enhanced early decision-making. In addition to exploring the challenges of AI-BIM integration, including technical and ethical considerations, this research highlights strategies to support its practical application. The framework contributes to advancing design practices in the evolving AEC industry.