The integration of Artificial Intelligence (AI) into Building Information Modeling (BIM) has the potential to revolutionize the Architecture, Engineering, and Construction (AEC) industry by enhancing efficiency, improving decision-making processes, and making BIM models more accessible and intuitive for professionals across various disciplines. This thesis introduces DAVE (Digital Assistant for Virtual Engineering), a prototype of a Generative Pre-trained Transformer (GPT)-powered digital assistant designed to facilitate seamless, real-time interactions and updates within BIM environments through natural language processing (NLP) and voice commands. By integrating with Autodesk Revit using Python scripts, the Revit API, and the OpenAI API, DAVE demonstrates a practical application of conversational AI in the AEC sector, aiming to make BIM workflows more intuitive and reducing the cognitive load on users.

The development and implementation of DAVE involve a comprehensive system architecture that combines Python scripting, a Dynamic-Link Library (DLL), and a JavaScript Object Notation (JSON) file for efficient data management and interaction with BIM models. The prototype's testing and validation phase highlights its capability to handle a variety of commands, from simple tasks such as undoing actions to more complex operations like updating room names and numbers. Through a detailed analysis of system performance and user interaction, this thesis explores the challenges and limitations of integrating AI with BIM, including scalability, data integrity, and the quality of user queries. Despite these challenges, DAVE's successful demonstration of real-time BIM model management through voice and natural language commands marks a significant step forward in the digital transformation of the AEC industry.

This thesis not only contributes to the ongoing development of AI applications within BIM but also lays the groundwork for future research aimed at expanding the capabilities of AI-powered assistants in the AEC sector. By addressing the current system limitations and exploring avenues for further enhancements, such as interoperability with other BIM software and improving the efficiency of information retrieval, the study paves the way for a more connected, intelligent, and user-centric future in the built environment. The development of DAVE embodies the potential of conversational AI to revolutionize architectural and construction methodologies, offering insights into how the AEC industry can leverage AI to achieve greater efficiency, sustainability, and innovation in project management and execution.