Artificial Intelligence -Driven Sustainability and Human-Centric Optimization in Structural Engineering

Abstract The fields of structural and civil engineering are changing significantly due to the rise of new technologies, sustainability goals, and the need to manage uncertainties. Artificial Intelligence (AI), Machine Learning (ML), and Deep Learning (DL) are transforming the industry. They provide useful, data-driven tools for optimizing designs, predicting material properties, and detecting structural damage. At the same time, there is a strong emphasis on sustainability. This pushes the focus toward a complete assessment of building technologies, considering environmental, social, economic, and technical effects. This matter is especially important since buildings account for a large part of global energy consumption and resource use. Building Information Modelling (BIM) serves as an important digital framework for managing this complex information throughout a building's entire lifecycle, although its implementation in existing structures can be tricky. Also, a systematic approach is needed to tackle the various uncertainties in structural engineering, such as variations in material properties, model limitations, and human error. By combining AI and BIM with sustainability and uncertainty management practices, the industry can build stronger, more efficient, and environmentally friendly infrastructure. This integration shows the potential of these fields and points to a future with smarter, more sustainable, and safer buildings.