Leveraging Artificial Intelligence and Data Analytics for Decision-Making in IT Project Management

Abstract

The article focuses on enhancing the justification of managerial decisions in large IT projects, characterized by persistent instability and escalating budgetary and schedule risks, through the systematic integration of artificial intelligence and advanced data analytics. The objectives of this study are twofold: first, to comprehensively describe the mechanisms for deploying predictive models and generative AI tools at every phase of the IT project life cycle; and second, to empirically validate the claimed effects using the PwC CEE IT practice. The novelty of the work lies in the combination of predictive machine learning, Monte Carlo simulations, AI scoring and the Copilot generative planner in a single decision-making loop, as well as in the fact that the author described in detail his experience of implementing and adapting these technologies in the real PMO process of PwC CEE IT. This article will be helpful to project leaders, PMO analysts, and developers of decision-support systems in IT project management.