Purpose: This paper aims to enhance a practice-oriented understanding of Artificial Intelligence (AI) applications in project management by systematically identifying and categorizing use cases. It addresses the dual objective of analyzing the current state of research and highlighting promising, yet underexplored, application areas. Methodology: The study employs a systematic literature review of peer-reviewed journal articles and conference papers, identified through structured searches across four major databases. The findings were analyzed using a two-dimensional framework that combines AI capabilities (e.g., predicting, decision-making, reasoning) with the ten project management knowledge areas defined by the PMBOK® Guide. Findings: The heat map resulting from this analysis shows a high concentration of AI use cases involving predictive analytics, particularly in time, cost, and quality management – core elements of the project management triangle. AI functions such as generating and acting, typically associated with generative AI and autonomous systems, are notably underrepresented. Communication- and stakeholder-oriented domains are also lacking in AI adoption, pointing to significant research gaps. The study highlights a lag between technological innovation and peer-reviewed academic research, especially concerning recent advancements such as generative AI. It offers two main contributions by systematically identifying and categorising AI use cases in different areas of project management: a conceptual framework and a practical overview for researchers and practitioners alike. First, it advances implementation on AI in project management by supporting practitioners identify potential AI use cases within projects: AI use case suggestions can enhance project management by automating tasks, improving forecasting, aiding communication, managing risks, monitoring performance, and ensuring quality. Second, the categorization of promising use cases in the form of a heat map introduces a new and valuable direction for future research.
Hewing et al. (Thu,) studied this question.