This chapter highlights the critical role of artificial intelligence (AI) and big data analytics in advancing sustainability in the construction industry. Early-stage design decisions have a significant impact on the long-term environmental, economic and social outcomes of construction projects, as fundamental choices determine material use, energy efficiency and waste generation. The chapter highlights the transformative potential of AI-driven methods for analysing large datasets to improve decision-making processes and promote sustainable practices from the outset of construction projects. By using AI, particularly machine learning techniques, the construction sector can achieve more accurate predictions of building energy performance and assess the economic feasibility of retrofits. The integration of Energy Performance Certificates (EPCs) and neural networks makes it possible to predict payback periods for investments, enabling stakeholders to make informed decisions during the feasibility and design phases. The chapter also addresses the challenges of data quality, advocating for robust data governance to ensure reliable AI applications. Ultimately, the chapter presents AI as a central tool for achieving sustainable construction practices. By embedding sustainability considerations early in the project lifecycle, the industry can contribute to decarbonisation targets, reduce environmental impacts and promote long-term economic viability.