Martin, H; James, J and Chadee, A (2025) Exploring large language model AI tools in construction project risk assessment: ChatGPT limitations in risk identification, mitigation strategies, and user experience. Journal of Construction Engineering and Management, 151(9): 04025119, ISSN 0733-9364
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.
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | artificial intelligence; chatgpt; construction; large language model; natural language processing; project management; prompt; risk management |
| Index terms: | risk management, project scope, risk assessment, artificial intelligence, project management, Ireland, construction industry, case study, efficiency, mitigation, practitioner, adaptability, construction project, decision-making, integration, bias, user experience, construction sector, risk analysis, interview, risk identification, strategy, large language model |
| Subjects: | project management theory and practice, probability and distributions, performance management, management, industry analysis, decision analysis, organizational analysis, user-centered design, risk assessment, data collection methods, artificial intelligence, data science, financial risk, Geography, production management, environmental hazards, scope management, practitioner, user focus |
| Topics: | Quality Management, Geographical Context, Project Management, Engineering Principles, Risk Management, Sustainability, Design Practice, Digital Applications, Organizational Design, Business Strategy, Cost Management, Research Practice, Roles and Professions |
| Descriptive scope: | 5 PCTEA |
N.B. Descriptive scope is a count of how many of the five facets of empirical research are indicated by the words used in title, abstract and keywords. It is not intended as a judgement on the research; merely a count of the kind of word we would expect to indicate Phenomenon, Concepts, Theoretical framing, Empirical techniques, Analytical techniques. If all five are present, then a code of “5 PCTEA” will indicate this. If you feel the coding for this record is questionable, we welcome discussion around the terms we matched or the way we categorized them. The facet you would expect may not be coded, or a facet may be coded inappropriately. This can also bear on a larger question, of which facets should be treated as defining in construction management research. Please get in touch, and we will look at it. More details here