In the rapidly evolving landscape of construction technology, a groundbreaking study led by Temitope Omotayo from the School of Built Environment, Engineering and Computing at Leeds Beckett University, is set to reshape how the UK and Turkiye approach artificial intelligence (AI) and building information modelling (BIM) within the circular economy. The research, published in the journal Buildings, offers a comprehensive state-of-the-art review and capability maturity modelling that could revolutionize the construction sector’s digital transformation.
The construction industry has long been on the cusp of a digital revolution, with AI and BIM leading the charge. These technologies promise to enhance productivity, accuracy, and sustainability, but their full potential remains untapped. Omotayo’s study delves into the current practices and capabilities of AI-enabled BIM and circular economy (CE) in the UK and Turkiye, providing a roadmap for future development.
The study, which involved a focus group of eight experts from both countries, reveals that the UK is ahead in terms of adoption, government policies, and incentives. However, there is still room for growth in technological advancement, education, training, industry readiness, and cultural attitudes. “The UK is at a defined level, but we need to push for more specific policies on AI adoption, especially for small- and medium-scale enterprises,” Omotayo explains. This push could significantly impact the energy sector, where construction projects often require precise planning and execution to maximize efficiency and sustainability.
Turkiye, on the other hand, is at the initial stage of AI adoption. The country has significant potential for technological advancements but faces barriers such as technological infrastructure limitations, skill gaps, and institutional resistance. Omotayo’s research suggests that Turkiye needs a comprehensive AI and CE roadmap to leverage existing BIM policies effectively. “Turkiye is actively seeking to adopt international best practices and standards in BIM and AI,” Omotayo notes. “Participating in global industry forums and partnerships can facilitate knowledge transfer and the adoption of proven methodologies.”
The study’s findings are particularly relevant for the energy sector, where the circular economy principles can lead to more efficient use of resources, reduced waste, and lower emissions. AI-powered BIM can help in designing and managing construction projects that align with these principles, ultimately leading to more sustainable and cost-effective energy infrastructure.
Omotayo’s research also highlights the need for increased investment in digital infrastructure, education, and training programs. “We need more extensive educational programs focused on AI, BIM, and digital construction technologies,” Omotayo emphasizes. “This includes partnerships with universities and vocational training centers to create a skilled workforce.”
The study’s recommendations for a 10-year capability maturity modelling adoption timeframe towards an optimized level could influence government, education, research, and technological policies in both countries. As the construction sector continues to evolve, this research provides a crucial framework for integrating AI and BIM within the circular economy, paving the way for a more sustainable and efficient future. The insights from this study, published in the journal Buildings, are set to shape the future of construction technology, with far-reaching implications for the energy sector and beyond.
