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AI-Assisted Product Management: Transforming the Product Development Lifecycle

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  • Anup Raja Sarabu

Abstract

AI-Assisted Product Management transforms the traditional product development lifecycle through the integration of artificial intelligence technologies across key operational areas. The integration of AI into product management processes enables significant advancements in backlog refinement, feature documentation, user story generation, and acceptance criteria automation. Product teams leveraging these technologies experience enhanced efficiency in documentation creation, higher accuracy in effort estimation, improved backlog prioritization, and more comprehensive user story development. The AI-driven approach facilitates more precise identification of market opportunities while reducing development rework through improved requirement clarity. Notable benefits include decreased time spent on administrative tasks, allowing product managers to focus on strategic initiatives, increased sprint completion rates through better backlog management, reduced scope creep, fewer revisions needed for AI-generated documentation, and earlier detection of potential issues through intelligent edge case identification. As AI technology continues to mature, its role evolves from basic automation toward becoming a collaborative partner in product development, contributing to ideation processes and generating features with higher adoption rates. The synergy between human strategic thinking and AI-powered execution support represents the future direction of product management practices.

Suggested Citation

  • Anup Raja Sarabu, 2025. "AI-Assisted Product Management: Transforming the Product Development Lifecycle," International Journal of Scientific Research in Computer Science, Engineering and Information Technology, International Journal of Scientific Research in Computer Science, Engineering and Information Technology, vol. 11(2), pages 3803-3813, March.
  • Handle: RePEc:jbh:ijsrcs:v11:y2025:i2:id:1419
    DOI: 10.32628/CSEIT25112855
    Note: Article URL: https://ijsrcseit.com/home/article/view/CSEIT25112855
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