Generative artificial intelligence in AEC organizations: A literature and SWOT analysis

Generative artificial intelligence (GenAI) is seen as an efficient way to enhance architecture, engineering, and construction (AEC) organizations through the generation of novel content and the automation of processes and tasks. Rapid advancement in GenAI is giving rise to new potential applications in AEC orga- nizations, and this requires a detailed understanding and a strategic planning technique to evaluate the usefulness of GenAI to organizations. This study aims to address this gap by examining GenAI literature in the AEC industry to determine how GenAI contributes to the enhancement of AEC organizations. To achieve the aim, this article identifies how GenAI is used in AEC organizations, and proposes a strengths–weaknesses–opportunities–threats (SWOT) process and el- ements for the strategic evaluation of GenAI in AEC organizations. The research methodology consists of a systematic review process. The findings categorized 79 journal articles and conference papers, which revealed that GenAI was being explored to create architectural and structural designs of buildings, optimize construction processes, and enhance risk management and work safety. There are limitations in the capability of GenAI models to meet project management needs. These include low quality datasets used for training, cost, time, and computation resources required to implement GenAI effectively, and ethics and privacy issues when using GenAI in AEC organizations and projects. Addition- ally, a SWOT process is proposed, and twenty SWOT elements are developed and described: four elements for strengths, five elements for weaknesses, five elements for opportunities, and six elements for threats. The proposed elements aim at providing a foundation for AEC organizations to assess and achieve their strategic GenAI implementation goals. This article identifies the areas of research focus along with a SWOT process and elements that may be useful to researchers and industry practitioners focusing on GenAI and SWOT in the AEC industry.