The recent rapid advancements of Machine Learning (ML) have significantly empowered and transformed many research domains, including architecture, engineering, and construction (AEC) area. Meanwhile, in AEC industry, Geographic Information System (GIS) is also a commonly used tool. In order to better understand the state-of-the-art ML and GIS synergies, this research conducts a bibliometric analysis to reveal hidden information from relevant literature and explore the integration cases of ML and GIS in the AEC domain. As a result, a dataset of 3387 relevant articles (including articles and conference papers) published from 2010 to 2023 was retrieved from Scopus and further analyzed. The research employs visualization techniques to highlight key publications, active research institutions, key researchers, influential journals, etc. Several research themes have been identified as the most studied areas. As a result, research gaps are captured, and several promising future research directions are suggested.