Integration of generative artificial intelligence across construction management
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A4 Artikkeli konferenssijulkaisussa
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Date
2024
Department
Department of Civil Engineering
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Degree programme
Language
en
Pages
12
Series
IOP Conference Series: Earth and Environmental Science, Volume 1389, issue 1
Abstract
This research investigates the integration of generative artificial intelligence (AI) solutions in the context of construction management. Generative AI has surpassed human capabilities in various tasks, offering a unique opportunity to address longstanding development barriers in construction management. Previous research has shown how generative AI can help with individual management tasks but a wider overview of how generative AI could help in construction management is still missing. By breaking down construction management into individual tasks and linking each task to available generative AI solutions, the study uncovers multiple innovative approaches to enhance current practices. Consequently, this research introduces the mapping of management tasks and explores a range of practical implications of generative AI on construction management. The research takes a mixed-methods approach, collaborating with industry professionals from Finnish construction companies through focus group discussions (FGD), and questionnaires to gather valuable feedback. The outcome is a pragmatic summary of seven management actions, connected with generative AI solutions, and their quantitative potentiality assessment. The results indicate an overall good potential for integrating generative AI into construction management, with AI-enhanced chair and secretary actions, communication and situational awareness, data analysis and improvement, and risk management receiving the highest perceived potentiality scores.Description
Publisher Copyright: © Published under licence by IOP Publishing Ltd.
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Citation
Nyqvist, R, Peltokorpi, A & Seppänen, O 2024, ' Integration of generative artificial intelligence across construction management ', IOP Conference Series: Earth and Environmental Science, vol. 1389, no. 1, 012011 . https://doi.org/10.1088/1755-1315/1389/1/012011
