Challenges and Insights of AI Integration in Construction Project Scheduling

Abstract

The construction industry increasingly demands greater efficiency, accuracy, and agility in project management, with effective scheduling at the core of achieving these objectives. Integrating Artificial Intelligence (AI) into construction project scheduling presents a transformative opportunity to improve accuracy, resource optimization, risk management, and cost estimation. This study explores the integration of AI in construction scheduling, focusing on identifying the key challenges, benefits, and practical insights associated with its adoption. Through a systematic literature review and analysis of case studies, the research highlights the ways in which AI enhances scheduling precision, predicts potential delays, and supports proactive decision-making. However, significant barriers impede widespread AI adoption, including data limitations, high computational requirements, integration and compatibility issues, reliance on real-time data, and workforce training gaps. The paper categorizes these challenges, evaluates their frequency and impact across various construction contexts, and offers targeted recommendations for overcoming them. It emphasizes the need for robust data infrastructure, scalable AI models, and comprehensive training programs to ensure the effective implementation of AI in construction scheduling. The findings are intended to guide industry stakeholders, including project managers and policymakers, in adopting AI solutions that can streamline project timelines, enhance coordination, and improve overall project performance, while identifying areas for future research and technological development.