Abstract
The UK construction sector has increasingly encountered cost management inefficiencies in overruns, errors, rework and variations. This study demonstrated how Generative AI (GAI), an emerging trend in digital construction, can foster large language models (LLMs) from the industry's historical data to predict costs. The process of developing the GAI system architecture applied the V-model and agile methodological approach and BIM templates. As used in the UK construction sector, the BIM templates considered data from building cost information service (BCIS) and task information delivery plan (TIDP) to develop the architecture. The system architecture designed in this study aligned with the RICS New Rules of Measurement 1 (NRM1) for early cost advice and text-to-task models. The implication of the GAI system architecture for digital cost management presented in this study elicited the integration of GAI with the BIM processes, offering substantial benefits to the construction industry. This includes streamlined workflows, reduced errors, and improved decision-making. The implications of the system architecture offer opportunities for increased BIM uptake in the UK and the sector globally.
More Information
Divisions: | School of Built Environment, Engineering and Computing |
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Identification Number: | https://doi.org/10.7771/3067-4883.1781 |
Status: | Published |
Refereed: | Yes |
Publisher: | Purdue University |
SWORD Depositor: | Symplectic |
Depositing User (symplectic) | Deposited by Omotayo, Temitope |
Date Deposited: | 21 Aug 2025 11:12 |
Last Modified: | 22 Aug 2025 23:45 |
Event Title: | The 23rd CIB World Building Congress (WBC2025) |
Event Dates: | 19-23 May 2025 |
Item Type: | Conference or Workshop Item (Paper) |
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