Artificial Intelligence Capabilities and Project Success – Analysis of Research Trends
TL;DR
The gap between the growing role of AI and current project management competency models is identified, which should be expanded to include AI-related competencies, such as AI literacy, data work, algorithmic decision-making, and technology ethics.
Abstract
Aim: The objective of this article was to systematically analyse the literature on AI-related competencies of project managers and assess how these competencies were addressed in the context of project management. Methodology: The study was conducted in accordance with the PRISMA 2020 guidelines, using bibliometric analysis (VOSviewer) and qualitative content analysis. The bibliometric analysis included 38 publications, and the qualitative analysis covered 26 works, coded into four competency categories: technological, cognitive, decision-making, and ethical-organisational. Results: The literature focuses primarily on the technological dimension of AI, while project managers' competencies are only marginally and inconsistently described. Technological and decision-making competencies dominate, cognitive and ethical-organisational competencies remain underdeveloped, and there is no consistent model of AI competencies for project managers. Implications and recommendations: Project management competency models should be expanded to include AI-related competencies, such as AI literacy, data work, algorithmic decision-making, and technology ethics. The DigComp 2.2 framework can support their systematisation. Originality/value: The article identifies the gap between the growing role of AI and current project management competency models and outlines directions for further research.