The opportunities and challenges of AI in the construction industry / Dr Sheikh Ali Azzran Sh Said

The use of artificial intelligence ("AI") in variouseconomic sectors has the capability of boosting the efficiency and productivity of business operations. These has sparked much debated lately. This technology has brought about fierce competitions, especially among tech giants (e.g., Goog...

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Bibliographic Details
Main Author: Sh Said, Sheikh Ali Azzran (Author)
Format: Book
Published: Office of the Deputy Vice-Chancellor (Research & Innovation), 2023-11.
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520 |a The use of artificial intelligence ("AI") in variouseconomic sectors has the capability of boosting the efficiency and productivity of business operations. These has sparked much debated lately. This technology has brought about fierce competitions, especially among tech giants (e.g., Google, Amazon, Apple, Microsoft) as it influenced organisational strategies. Furthermore, the dawn of AI is inevitably a force to be reckoned with, especially in the construction industry. The multi-faceted advanced technologies used in the construction industry such as Building Information Modelling ("BIM"), Digital Twinning, the Internet of Things ("IoT"), Virtual Reality/ Augmented Reality ("VR" / "AR"), Blockchain Technology, and Big Data have opened doors of opportunities to revolutionise the entire construction ecosystem. However, there are challenges to consider before any construction organisation could embark on its journey to transform its businesses by employing AI technologies. The use of AI technology in the construction industry is no other than to transform construction structures to boost productivity, improve business models, and introduce new services to the market. As construction projects are transient and multiorganisational, the construction business would gain more by incorporating AI technology. AI can help the construction sector increase productivity, safety, and quality by automating operations and digitising procedures. Such independence makes building development more evidence-based and less reliant on implicit knowledge. Moreover, unanticipated revisions will be reduced, which will save time and money. 
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