Harnessing artificial intelligence and machine learning in civil engineering: a review

The integration of artificial intelligence (AI) and machine learning (ML) in civil engineering has revolutionised traditional approaches, enabling data-driven decision making, predictive modelling and process automation across diverse domains. This review comprehensively explores the current landscape, key applications, emerging trends and challenges associated with AI and ML technologies in civil engineering. Major areas of impact include structural health monitoring, construction management, geotechnical engineering, transportation systems and environmental modelling. This review highlights how algorithms such as artificial neural networks, support vector machines, decision trees and deep learning models have been effectively utilised for tasks ranging from predictive maintenance and risk assessment to material behaviour analysis and smart infrastructure development. Despite significant advancements, challenges such as data scarcity, model interpretability and integration into existing workflows remain. The review also identifies future opportunities to enhance civil infrastructure resilience and sustainability through AI-augmented systems. This work aims to serve as a foundational resource for researchers, practitioners and policymakers seeking to adopt or advance intelligent technologies in civil engineering practice.