Using Artificial Intelligence to Detect Underlying Issues in Projects: Seeing Beyond Current KPIs and Project Status Reports

Project status reports traditionally are the primary source of project control. However, they offer an incomplete view relying on static snapshots with limited historical context for managing projects. It is difficult obtain a real-time status of projects, relying on project status reports alone. This study explores the research question that past project performance can inform future insights, the need for which is driven by increasing workloads and the rise of artificial intelligence (AI). Project professionals face an immense pressure to deliver increased business value with limited resources. This study attempts to understand the application of AI to reduce the burden of analysing a large data source that changes over time, and to identify potential upcoming challenges in delivering successful projects outcomes. Using a machine learning approach, this study offers insights into detecting patterns and relationships in project data indicating success/failure and outline the criteria for a successful AI-enabled project management system.