Benefits of Artificial Intelligence in Lean Construction Management in the Planning Phase

Abstract

The construction industry is undergoing significant changes due to increasing complexity, rising demands for sustainability, and ongoing inefficiencies. Lean Construction Management (LCM), derived from the Toyota Production System, seeks to enhance workflows, minimise waste, and increase project efficiency. However, traditional lean methods often struggle to adapt to changing construction settings. Artificial Intelligence (AI) presents a significant opportunity to support lean principles by enhancing scheduling, resource management, waste reduction, and facilitating real-time decision-making.

This study examines the integration of AI into Lean Construction Management. It also examines AI frameworks, their practical applications, and the challenges associated with industry adoption. A mixed-methods research approach is employed, incorporating a comprehensive literature review and expert interviews in the fields of construction and AI. Key findings show that AI-driven solutions, such as machine learning for predictive scheduling, computer vision for safety monitoring, and optimisation algorithms for resource allocation, enhance lean methods. This leads to greater efficiency and sustainability.

Despite these potential benefits, several barriers prevent adoption. These include issues with data availability, lack of trust, resistance to change, and legal concerns. The study introduces an AI-Lean integration framework that outlines best practices for implementation. It emphasises the importance of organised data collection, gradual deployment and ethical considerations. Case studies from major projects, such as Crossrail in the UK and Sutter Health Hospital in the United States, demonstrate how AI has effectively enhanced construction productivity and waste management.

This research adds to the understanding of AI’s role in lean construction and offers practical strategies for achieving efficiency gains driven by AI. It highlights the need for a human-centred approach to ensure that AI supports decision-making in construction processes rather than replacing it. The study concludes with recommendations for scalable AI adoption and future research directions.