TY - GEN
T1 - The Economic Paradox of Design and the integration of Artificial Intelligence (AI) within Building Information Modelling (BIM)
AU - Baldessin, Guilherme Quinilato
AU - Melhado, Silvio
N1 - Publisher Copyright:
© 2026 International Association on Automation and Robotics in Construction. All Rights Reserved.
PY - 2026
Y1 - 2026
N2 - The management of data in complex construction projects represents a significant challenge in the design and realization of infrastructure. This paper examines the implementation of an integrated Common Data Environment (CDE) to centralize graphical and non-graphical information, aiming to optimize coordination, improve quality, and increase productivity throughout the project lifecycle. The study advocates for shifting effort to the initial design phases where decisions have the maximum impact on performance and cost. It further explores the integration of Artificial Intelligence (AI) within Building Information Modelling (BIM) workflows, emphasizing that structured data collection is a prerequisite for advanced automation. The methodology aligns with Integrated Project Delivery (IPD) models and Concurrent Design principles to foster stakeholder collaboration. Results indicate that establishing a centralized data repository allows for the effective deployment of predictive AI models. The article concludes that the successful digital transformation of the construction sector requires a collective commitment to collaborative cultures and rigorous data centralization from the onset of conception.
AB - The management of data in complex construction projects represents a significant challenge in the design and realization of infrastructure. This paper examines the implementation of an integrated Common Data Environment (CDE) to centralize graphical and non-graphical information, aiming to optimize coordination, improve quality, and increase productivity throughout the project lifecycle. The study advocates for shifting effort to the initial design phases where decisions have the maximum impact on performance and cost. It further explores the integration of Artificial Intelligence (AI) within Building Information Modelling (BIM) workflows, emphasizing that structured data collection is a prerequisite for advanced automation. The methodology aligns with Integrated Project Delivery (IPD) models and Concurrent Design principles to foster stakeholder collaboration. Results indicate that establishing a centralized data repository allows for the effective deployment of predictive AI models. The article concludes that the successful digital transformation of the construction sector requires a collective commitment to collaborative cultures and rigorous data centralization from the onset of conception.
KW - Artificial Intelligence
KW - Common Data Environment
KW - Information Management
KW - Integrated Project Delivery
UR - https://www.scopus.com/pages/publications/105046003349
U2 - 10.22260/ISARC2026/0103
DO - 10.22260/ISARC2026/0103
M3 - Contribution to conference proceedings
AN - SCOPUS:105046003349
T3 - Proceedings of the International Symposium on Automation and Robotics in Construction
SP - 802
EP - 809
BT - Proceedings of the 43rd International Symposium on Automation and Robotics in Construction, ISARC 2026
A2 - Chen, Qian
A2 - Lee, Gaang
A2 - Liang, Ci-Jyun
A2 - Zhang, Jiansong
A2 - Kamat, Vineet R.
PB - International Association for Automation and Robotics in Construction (IAARC)
T2 - 43rd International Symposium on Automation and Robotics in Construction, ISARC 2026
Y2 - 22 June 2026 through 26 June 2026
ER -