Abstract

Project management failure is still very common as a result of poor planning, poor risk management, and resource allocation. Traditional approaches are often based on static models and human judgment, which is capable of poor handling of complexity and uncertainties in modern projects. This study is about how we can use AI power-packed predictive analytics tools to better plan and make projects more successful. A literature review points out the drawbacks of traditional practises and illustrates the role of AI applications in improving areas such as predictive forecasting, risk analytics, and decision support systems, which improves cost estimation, schedule adherence, resource optimization, and quality control. Using a qualitative approach and a case study-based methodology with secondary data deriving from real-world infrastructure and construction projects, the research results demonstrate that AI integration results in measurable improvements such as decreases in project delay, cost over-burdens, and defects as well as an increase in the overall satisfaction of stakeholders. The discussion highlights the role of AI in transitioning project management from reactive to proactive practises, the underlying mechanisms of predictive analytics in failure reduction, and the issues of adoption as it relates to quality of data and organisations and governance. The study concludes that AI enhanced predictive analytics is a transformative solution for managing a project. Recommendations include strategic AI integration and capacity building, piloting and continuous improvement with future research ideas focusing on longitudinal/quantitative in different project situations.