Abstract
The promotion of uptake of building information modelling (BIM) and circular economy (CE) in the UK and Turkiye construction sectors can be enhanced with the addition of AI. Thus, AI-enabled BIM and CE must be addressed from the viewpoint of current practices and capabilities. This study conducted a comparative study of capability maturity modelling (CMM) backed by a state-of-the-art (SOTA) review of 24 peer-reviewed publications via a validatory approach using a focus group webinar of eight experts in the UK and Turkiye. The findings, as extracted through a validated CMM framework of seven dimensions, were used to identify the position of the UK and Turkiye in terms of AI in BIM and CE. It was discovered that the UK is in a position regarding adoption, government policies and incentives at a defined level. AI growth is required in terms of technological advancement, education and training, industry readiness, cultural attitudes and resistance because they are in a managed phase. It was confirmed that Turkiye is at the initial stage of AI adoption, education, training, incentives, policies, technology and cultural attitudes. The originality of this study lies in the recommendations for a 10-year CMM adoption timeframe towards an optimised level. The conclusions of this manuscript will influence government, education, research and technological policies in the UK and Turkiye.
More Information
Divisions: | School of Built Environment, Engineering and Computing |
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Identification Number: | https://doi.org/10.3390/buildings15081224 |
Status: | Published |
Refereed: | Yes |
Publisher: | MDPI AG |
Additional Information: | © 2025 by the authors |
Uncontrolled Keywords: | AI; BIM; Construction sector; Circular economy; UK; Turkiye; 1201 Architecture; 1202 Building; 1203 Design Practice and Management; 3301 Architecture; 3302 Building; 4005 Civil engineering |
SWORD Depositor: | Symplectic |
Depositing User (symplectic) | Deposited by Omotayo, Temitope |
Date Deposited: | 09 Apr 2025 14:09 |
Last Modified: | 18 Apr 2025 05:16 |
Item Type: | Article |
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