## 3 Methodology  
This study applies an SLR methodology based on a well-defined and well-planned protocol. Unlike the traditional literature review strategy in which the reviewer's subjectivity and informality can influence the outcome, the SLR method removes such prejudice by applying systematic procedures to identify, select, and evaluate a theme of interest [19]. This approach is particularly appropriate in this investigation due to its suitability to gather the most relevant research on emerging themes [20; 21; 22]. The review explores the use of AI in PM through a rigorous process that includes planning the search strategy, identifying targeted academic publications on established themes, determining inclusion and exclusion criteria, and conducting the review and reporting findings [19]. The SLR process was conducted in two phases. The first phase involves selecting keywords, establishing inclusion and exclusion criteria of papers for the study (i.e., published period, keywords, and language), and conducting the literature search. The second phase evaluates selected papers considering the latest standard of PMBOK7 principles and PDs.  
The planning of the review process was focused on analyzing and understanding the nuances of the use of AI in the stages of PM in different domains. The authors brainstormed to establish the keywords and to define the review process's conceptual boundaries. At this point, it was predetermined that the papers published from 2011 to the present (April 2022) are the appropriate time range to focus on the publications on post declaration of the Industry 4.0 era. Authors reached a consensus over the combination of the keywords as \"project management\" AND \"artificial intelligence\". Two of the largest repositories of academic articles, Web of Science and Scopus, were chosen due to their higher scientific impact and thus to search for conforming peer-reviewed journals and conference papers [23]. The literature search was delimited exclusively to English language publications. The search for title, abstract, and keywords in selected databases was performed using search strings to ensure all the papers related to the use of AI in PM are selected.  
The next level of the filtering process of the selected papers from the search process was first conducted by each author individually reviewing the articles and assessing them through screening criteria. The abstract and the conclusions of each selected article were thoroughly scrutinized at this stage. When either the authors are unsure as to whether the paper explicitly fits the study theme or concluded that the paper complies with the study criteria, the rest of the article was thoroughly read to ensure conformance to the research theme. Finally, the authors reassembled as a review panel to mutually determine the final sample of the SLR process that fits the conceptual boundary of the investigation. This compilation represents the most comprehensive body of academic work on AI in PM published to date to the best of the authors' knowledge.  
Subsequently, we present the results of the SLR bibliometric analysis and the literature review categorized under the latest PMBOK7 PDs. Then, a discussion on the significant findings of the studied theme is conducted.