The global construction sector is undergoing a major shift driven by Construction 4.0, where traditional structural design methods are increasingly complemented or replaced by advanced digital technologies. This systematic review evaluates how Artificial Intelligence (AI), Generative Design (GD), and Building Information Modeling (BIM) contribute to sustainable development in architecture and civil engineering. Using the PRISMA protocol, the study synthesizes current evidence on the role of algorithmic intelligence in supporting UN Sustainable Development Goals (SDGs), particularly Goals 9, 11, 12 and 13. Findings indicate that transitioning from deterministic engineering approaches to AI-based heuristic methods enables significant optimization of material use and structural mass, thereby reducing embodied carbon in the built environment. Performance-driven generative workflows and physics-informed neural networks (PINNs) emerge as key enablers of circularity and early-stage Life Cycle Assessment (LCA) integration. However, the review also identifies gaps, such as limited applications of genetic algorithms in sustainable steel structure design and the substantial energy consumption associated with large-scale AI models. The study concludes that while digital tools provide transformative potential for decarbonizing the construction sector, future research should focus on improving algorithm transparency, reducing black-box limitations, and standardizing performance metrics to support broader adoption in engineering practice. The review can be a framework to help researchers, engineers, and policymakers integrate emerging AI-tools into sustainable design and advancing decarbonized, resilient built environments.
Szewczyk et al. (Thu,) studied this question.