Abstract
This study explores the integration of Scrum methodologies with
artificial intelligence (AI) in project management, focusing on the use
of data analysis to optimize team performance. By simulating a Scrum
project in Python, we analyzed task distribution, completion times, and
team velocities using various visualizations. The results reveal key
insights into task bottlenecks, workload distribution across sprints,
and team members’ efficiencies. Additionally, a machine learning model
was developed to predict task completion times, showing significant
accuracy improvements. These findings demonstrate the potential of AI in
enhancing planning processes for future sprints.