AI-Driven Construction Project Optimisation Using Predictive Modelling and Artificial Neural Networks: A Case Study Analysis

Thoyajakshudu Chalamarla

Abstract: This study examines the role of Artificial Intelligence (AI) in optimising construction project management, with a focus on improving efficiency and reducing costs. A mixed-method approach was adopted, combining qualitative and quantitative analysis of multiple case studies involving AI applications such as computer vision, robotics, and predictive analytics. The findings indicate that AI-driven tools enhance project scheduling, risk management, and resource allocation, leading to measurable reductions in project delays, operational costs, and safety risks. Quantitative results demonstrate notable improvements in productivity and time efficiency across the analysed cases. The study highlights the potential of Artificial Neural Networks (ANN) and predictive modelling in supporting data-driven decision-making in construction. These results suggest that strategic adoption of AI can significantly improve project outcomes and operational performance in the construction industry.

Keywords: Artificial Intelligence, Construction Project Management, Predictive Modelling, Artificial Neural Networks, Cost Reduction, Project Optimisation, Machine Learning in Construction