Artificial Intelligence in Sustainable Building and Infrastructure Development: The Adaptation and Challenges

Artificial Intelligence (AI) provides an opportunity to advance the building and infrastructure sectors while also aligning with the Sustainable Development Goals, more specifically goal 9, 11 and 12, representing Industry, Innovation and Infrastructure, Sustainable Cities and Communities, Responsible Consumption and Production, respectively. This paper analyzes the potential of AI for better efficiency and sustainability during the construction lifecycle. It takes into consideration the various features of the technology, from generative design, resource optimization, smart buildings, to circular economy enablement. Key AI adaptations include minimizing the material waste, optimizing energy performance, easing the process of life cycle assessment, and enabling innovative construction methodologies. However, the adoption of the technologies is not spreading, in fact, it is held back by many obstacles. Some of these obstacles are challenges with data quality, system integration, the high economic cost, uncertain ROI, lack of clear rules, regulations, in addition to the social and organizational resistance to change. To get past these challenges, organizations need to introduce AI in careful stages, having government and private companies work together, investing in better technology for data, training people with new skills, and creating helpful rules to support this work. Case studies such as Neom and The Edge highlight AI's benefits in reducing carbon footprints and improving resource efficiency. Ultimately, realizing AI's full potential in sustainable construction requires all stakeholders to work together to encourage an ecosystem that supports responsible innovation, while addressing the complexities of integrating AI into this traditional industry.