Integrating AI-Driven Project Management in the Construction Industry: A Framework for Optimising Decision-Making and Operational Efficiency in Industry 4.0
Purpose: This research explores the potential of Artificial Intelligence (AI) to revolutionise project management practices within the construction industry, a key sector in the context of Industry 4.0. The study examines both the advantages and challenges of AI adoption, focusing on its ability to enhance decision-making, improve operational efficiency, and enable predictive analytics for optimised project outcomes.<br/>Design/Methodology: A mixed-methods approach was employed, beginning with a Systematic Literature Review (SLR) following PRISMA guidelines, and supplemented by thematic qualitative analysis.. This process identified existing AI applications in construction and highlighted a critical bottleneck: the lack of an AI-driven project management framework within Industry 4.0, which hampers effective AI implementation in complex, multi-disciplinary environments (Tominc et al., 2023; Psyché et al., 2023). To address this, the study developed and tested a new framework built around an iterative prompt library designed to refine AI outputs, reduce inaccuracies, and minimise hallucinations, ultimately enabling the AI system to perform more efficiently.<br/>Findings: The findings demonstrate that AI holds significant potential to transform construction project management by streamlining operations and optimising decision-making. However, the study also underscores critical limitations, including ethical concerns, data quality issues, and the need for robust training programs to improve AI literacy among construction professionals.<br/>In conclusion, while AI offers exciting opportunities for enhancing project management in construction, its successful implementation requires careful consideration of technical, ethical, and educational challenges. These insights offer important directions for future research on AI frameworks tailored to the unique demands of the construction industry.
Institutions
- University of Manchester (GB)
- Manchester University (US)
Publication Details
- Journal
- Research Explorer (The University of Manchester)
- Published
- 2024-12-17
- Primary Topic
- BIM and Construction Integration
- Type
- article
- Field-Weighted Citation Impact
- 0.00