Abstract
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.
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.
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.
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.
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.
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.
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.
| Original language | English |
|---|---|
| Title of host publication | The International Research Society for Public Management (IRSPM) Conference 2025 |
| Publication status | Accepted/In press - 17 Dec 2024 |
Keywords
- Artificial Intelligence
- Decision Making
- Operational Efficiency
