Conversational artificial intelligence in the AEC industry: A review of present status, challenges and opportunities

Abdullahi Saka, Lukumon Oyedele, Lukman Akanbi, Sikiru Abiodun Ganiyu, Daniel Chan, Surura Bello

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The idea of developing a system that can converse and understand human languages has been around since the 1200 s. With the advancement in artificial intelligence (AI), Conversational AI came of age in 2010 with the launch of Apple’s Siri. Conversational AI systems leveraged Natural Language Processing (NLP) to understand and converse with humans via speech and text. These systems have been deployed in sectors such as aviation, tourism, and healthcare. However, the application of Conversational AI in the architecture engineering and construction (AEC) industry is lagging, and little is known about the state of research on Conversational AI. Thus, this study presents a systematic review of Conversational AI in the AEC industry to provide insights into the
current development and conducted a Focus Group Discussion to highlight challenges and validate areas of opportunities. The findings reveal that Conversational AI applications hold immense benefits for the AEC industry, but it is currently underexplored. The major challenges for the under exploration were highlighted and discusses for intervention. Lastly, opportunities and future research directions of Conversational AI are projected and validated which would improve the productivity and efficiency of the industry. This study presents the status quo of a fast-emerging research area and serves as the first attempt in the AEC field. Its findings would provide insights into the new field which be of benefit to researchers and stakeholders in the AEC industry.
Original languageEnglish
Article number101869
Number of pages21
JournalAdvanced Engineering Informatics
Publication statusPublished - 3 Jan 2023

Bibliographical note

Funding Information:
The authors would like to acknowledge and express their sincere gratitude to the Engineering and Physical Sciences Research Council (EPSRC – EP/S031480/1) for providing financial support for this study.

Publisher Copyright:
© 2022 The Author(s)


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