AI-augmented Scrum: Empirical analysis of the impact of implementing AI tools on the results of IT projects - Voznytsia, A. (Problems of Informatization and Management, 2025)
The article presents the results of an empirical study on the impact of integrating artificial intelligence (AI) tools into Scrum project management processes on key performance indicators of IT projects. The influence of AI solutions on sprint duration, development cost, product quality, and stakeholder satisfaction was analyzed. The study is based on a six-month quantitative analysis of 12 IT teams, half of which applied AI assistants (ChatGPT, GitHub Copilot, n8n, Notion AI, etc.) in task management, communication, and analytics. The results indicate that the use of AI assistants in Scrum practices reduces time and financial costs while increasing process transparency and decision quality. In particular, the experimental teams using AI had on average 19% shorter sprints, 14% lower labor costs, and 2.5 times fewer delayed tasks compared to the control teams. Product quality (QA ratings) improved by about 12%, and stakeholder satisfaction increased by 17%. Team managers reported a 35–45% reduction in administrative workload due to automation, and retrospective meetings were ~25% shorter thanks to automated reporting. Utilizing ChatGPT for daily updates and reports enhanced communication transparency with stakeholders. At the same time, certain risks were noted: the need for staff training to effectively use AI tools, the risk of over-reliance on model outputs without critical thinking, and challenges regarding data security and confidentiality when using external AI services. Overall, the findings suggest that AI integration in Scrum can significantly boost team productivity and project outcomes, serving as a catalyst for an AI-Augmented Scrum approach where AI not only supports but also informs management decisions.