Determinants of artificial intelligence adoption in project management: a global analysis of knowledge, drivers and barriers

This research investigates the determinants of artificial intelligence (AI) adoption in project management, focusing on knowledge, organizational drivers, and perceived barriers. Drawing on a global survey of 345 project management professionals, the research examines three models: (1) the effect of AI knowledge on adoption likelihood, (2) the influence of organizational drivers such as operational efficiency, leadership vision, and competitive advantage, and (3) the impact of perceived barriers including uncertain ROI, data privacy concerns, high costs, and lack of expertise. Results indicate that higher AI knowledge significantly increases adoption propensity. Organizational drivers, particularly leadership vision and competitive advantage, are strong positive predictors, whereas uncertain ROI acts as a significant barrier. Interestingly, concerns about data privacy and knowledge gaps exhibit a positive association with adoption, suggesting complex interactions between perceived obstacles and adoption behavior. The findings contribute to understanding AI integration in project management and provide actionable insights for organizations aiming to enhance efficiency, decision-making, and strategic AI implementation across projects.