International Journal of Contemporary Research in Multidisciplinary

Artificial Intelligence (AI) is increasingly revolutionizing civil engineering, enhancing design, construction, and maintenance processes with innovative technologies. This paper provides a comprehensive review of recent advancements and ongoing challenges in the application of AI within the civil engineering domain. Key advancements include AI-driven generative design algorithms that optimize structural performance and material usage, predictive modeling for better forecasting of structural behavior, and advanced construction management tools that improve scheduling and quality control. AI also contributes to smart infrastructure through predictive maintenance and real-time structural health monitoring, significantly extending the lifespan of infrastructure and reducing operational costs. Furthermore, AI supports sustainability efforts by optimizing energy efficiency and aiding in the development of eco-friendly materials.

Despite these advancements, several challenges persist. Data quality and availability remain critical issues, as AI systems depend on accurate and comprehensive data for effective performance. Integration with existing systems and traditional workflows poses difficulties, as does addressing the skill gap among civil engineers who must acquire new expertise in AI technologies. Ethical and legal considerations, including accountability and bias, also present significant hurdles that need to be navigated. This paper highlights these advancements and challenges, emphasizing the need for ongoing research, improved data practices, and training to maximize AI’s potential in civil engineering. Future directions include the refinement of AI algorithms, integration with emerging technologies, and broader adoption across various project scales and regions.