Artificial intelligence and machine learning tools for building lifecycle carbon reduction

The global construction industry is a primary contributor to greenhouse gas (GHG) emissions. Traditional carbon mitigation strategies often struggle with the scale and complexity of modern building projects in terms of the scale, complexity, and interdependence of building systems and data. This chapter is focused on exploring the transformative role of Artificial Intelligence (AI) and Machine Learning (ML) in decarbonising the entire building lifecycle, from early design to end-of-life. The rapid advancement of AI technologies has transformed the construction industry across multiple dimensions. This chapter investigates the role of AI and its advanced domains, namely, Computer Vision (CV), Data Pattern Recognition, Natural Language Processing (NLP), Geospatial Artificial Intelligence (GeoAI), and Explainable Artificial Intelligence (XAI), which are discussed in various applications in optimising energy and material decisions, improving construction workflows, automating compliance, supporting regional planning, and enhancing transparency in carbon reporting. Furthermore, the emergence of Foundation Models beyond the Large Language Models has been examined for their capability to analyse multidimensional, vast datasets to provide actionable decarbonisation insights. Finally, it is established that AI is not a complementary innovation, but a critical enabler of a sustainable Net-Zero Built Environment.