Exploring Large Language Model AI tools in Construction Project Risk Assessment: Chat GPT Limitations in Risk Identification, Mitigation Strategies, and User Experience

Abstract

The last 3 years have witnessed an increasing awareness and consensus on using artificial intelligence (AI) to enhance decision-making in the construction sector. This study explores the integration of ChatGPT (Generative Pre-trained Transformer) into traditional risk management frameworks within the construction industry, contributing to the ongoing discourse on AI’s role in enhancing risk identification, analysis, and mitigation. Using a mixed-method approach comparing ChatGPT-assisted to human evaluations, interviews, and a case study, the research develops a better understanding of construction risk analysis processes and discusses decision-making errors of omission, over- and underestimation of probabilities and impacts, and treatment of the residual risk after proposed mitigation strategies. Results suggest that users’ experience of ChatGPT is primarily favorable, characterized by quick responses and an intuitive interface that enhances decision-making efficiency. Findings indicate that GPT may be especially beneficial for less experienced practitioners since it provides comprehensive risk awareness. However, experienced professionals contend that the software lacks contextual depth. The study contributes a ChatGPT-4 prompt to evaluate infrastructure risk for a given project scope. An evidenced case study on a road upgrade project in Ireland demonstrates a lessened dependence on the quality of user prompting skills and emphasizes the quality of project scope data input. A collaborative approach, including Chat-GPT early involvement and human refinement, promises to enhance conventional risk management speed and efficiency and reduce bias and inflexibility while maintaining the adaptability and ethical rigour required in the industry’s evolving risk landscape.

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