AI-Driven Smart Materials in Sustainable Construction: Maximizing Efficiency, Cost Savings, and Environmental Performance

Abstract: The construction industry is undergoing a transformative shift with the integration of artificial intelligence (AI) and smart materials to enhance sustainability, cost efficiency, and structural performance. This research explores how AI-driven optimization can improve the selection, application, and lifecycle management of smart materials—such as self-healing concrete, phase-change materials (PCMs), and carbon-fiber composites—to reduce environmental impact while maximizing economic benefits. Using machine learning (ML) algorithms, predictive analytics, and IoT-enabled monitoring, this study presents a framework for real-time decision-making in sustainable construction projects. Case studies demonstrate up to 30% cost reduction, 25% decrease in material waste, and a 40% improvement in energy efficiency compared to conventional methods. The findings highlight the potential of AI-augmented smart materials in achieving net-zero construction while maintaining structural integrity and economic feasibility.