Developing an Intelligent Model for Construction Project Management Using Artificial Intelligence and Big Data Analysis to Improve Scheduling and Reduce Delays

Introduction: Traditional construction project management approaches have consistently struggled to address the key challenges of delays, budget overruns, and operational inefficiencies. These persistent issues highlight the need for more advanced methodologies. The integration of Artificial Intelligence (AI) with Big Data Analytics has emerged as a promising solution, aiming to improve scheduling accuracy, reduce delays, and enhance operational effectiveness in construction projects. Methods: A survey was conducted with 176 construction industry professionals, including project managers, engineers, and contractors, to assess the impact of AI and Big Data Analytics on construction project management. The survey focused on the use of AI-driven systems, including machine learning and predictive analytics, to improve project scheduling and delivery. Additionally, the application of Big Data Analytics in decision-making and risk assessment was explored. Results: The findings revealed that AI-powered systems, particularly those incorporating machine learning and predictive analytics, significantly outperform traditional construction management methods in terms of scheduling accuracy and delivery speed. Furthermore, the use of Big Data Analytics provided stakeholders with a deeper understanding of large datasets, facilitating more informed decisions and more accurate risk assessments. Quality execution and delivery were also found to be closely tied to effective communication and collaboration among teams and contractors, ensuring stakeholder satisfaction. Conclusions: This research demonstrates that AI and Big Data Analytics have the potential to transform construction project management by improving scheduling precision, reducing delays, and enhancing operational efficiency. The study underscores the importance of clear communication between teams and contractors to ensure the successful delivery of projects. While challenges related to infrastructure costs and ethical production remain, the integrated framework presented in this research provides valuable academic insights and practical solutions for stakeholders and project management personnel in the construction industry.