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AI-Powered Sprint Planning & Backlog Management for Project Lifecycle Management

Author

Listed:
  • RaviKumar Bhuvanagiri

    (McCombs School of Business, University of Texas, Austin)

Abstract

The synergy between Artificial Intelligence (AI) and Agile Scrum methodologies is fundamentally transforming project lifecycle management. This journal explores the profound impact of AI on sprint planning and backlog management, moving beyond traditional, human-centric approaches to embrace data-driven, predictive, and adaptive strategies. We delve into how AI algorithms, machine learning models, and natural language processing can optimize sprint forecasting, automate backlog grooming, simulate capacity scenarios, and enhance risk identification. This paper proposes a comprehensive framework for integrating AI into the Scrum Master's toolkit, repositioning them as "intelligence orchestrators" who leverage AI to foster greater efficiency, predictability, and team satisfaction. Through theoretical exposition, practical applications, and future outlooks, this journal aims to provide a unique perspective on the evolution of Agile project management in the age of AI.

Suggested Citation

  • RaviKumar Bhuvanagiri, 2026. "AI-Powered Sprint Planning & Backlog Management for Project Lifecycle Management," Journal of Computer Science and Technology Studies, Al-Kindi Center for Research and Development, vol. 8(4), pages 82-89, February.
    • Handle: RePEc:alk:jcsts0:v:8:y:2026:i:4:id:12005
    DOI: 10.32996/jcsts.2026.8.4.8
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