Theoretical Foundations of Artificial Intelligence-enabled Project Management: A Systematic Literature Review

Abstract

Artificial intelligence (AI) is increasingly transforming project management (PM) practices, yet the theoretical foundations of AI-enabled project management remain fragmented and insufficiently synthesised. Without clearer theoretical grounding, research in this area risks remaining largely descriptive and application-oriented.
This study aims to identify, map, and explain the theoretical perspectives used in research on AI-enabled project management. A systematic literature review (SLR) was conducted in accordance with PRISMA 2020 guidelines. The search covered Web of Science and Scopus and identified 712 database records published between 2015 and 2025. After screening and full-text eligibility assessment, 10 theory-oriented studies were retained as the core dataset.
The analysis shows that AI-enabled project management does not rely on a single dominant theory. Instead, the reviewed studies draw on several theoretical perspectives, including decision and behavioural theories, task–technology alignment, dynamic capabilities, stakeholder theory, complexity theory, information economics, and fuzzy set theory. Across the reviewed studies, AI is most often conceptualised as decision support or as an augmentation of managerial capabilities. The reviewed studies also differ in how AI is specified, ranging from relatively specific technologies and functions, such as generative AI, fuzzy AI models, predictive analytics, and AI-enabled monitoring, to broader conceptualisations such as AI assimilation and sociotechnical AI systems.
The study contributes by showing how theoretical lenses, specific theories, AI roles, explanatory mechanisms, and levels of analysis can be linked into explanatory chains. These chains are then aggregated into recurring explanatory configurations and emerging theoretical streams. AI technology / function types are used as an additional coding dimension to interpret technology-specific implications for project management. Given the small final sample of theory-oriented studies, the identified streams should be interpreted as emerging patterns within this body of literature rather than as definitive or generalisable classifications of the entire AI-enabled project management field.