Abstract
The rapid adoption of artificial intelligence (AI) across industrial markets is transforming the conventional project management (PM) approaches. However, studies on this emerging field remain scattered across application-focused and industry-specific domains. The purpose of this study is to identify current trends and gaps within the research of AI adoption in industrial PM landscape by conducting a bibliometric analysis of the existing studies. To fulfill this purpose, a sample of 95 journal articles, published between 2019 and March 2026, were collected from Scopus database using corresponding keywords and analyzed on VOSviewer software using its embedded visualization tools and science-mapping technique. The results demonstrate a rapidly expanding research domain with prevailing number of engineering and technology-focused papers with a focus on construction industry as an empirical setting, while lacking contributions from theoretical and evidence-based works on management perspective. This trend reveals the increasing gap between the research in AI advancements and their adoption in managerial landscape, as well as a lack of empirical research addressing their practical implementation in industrial PM. The article contributes to the research by consolidating the scattered knowledge in AI adoption in industrial PM, identifying key research gaps, and highlighting prospects for future research.