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What Role Does Generative AI Play in Structuring Requirements From Feedback Notes?
Understand how generative AI transforms disorganized stakeholder notes and stories into structured user stories and acceptance criteria, streamlining requirements engineering for faster, accurate systems analysis.
Question
What does generative AI do to transform stakeholder feedback into structured requirements?
A. It reduces the need for analysts to review and verify stakeholder input.
B. It converts unorganized notes or stories into clear formats such as user stories and acceptance criteria.
C. Generative AI removes repetitive and unnecessary feedback to shorten requirement documents.
D. Generative AI summarizes stakeholder conversations and feedback without organizing the content.
Answer
B. It converts unorganized notes or stories into clear formats such as user stories and acceptance criteria.
Explanation
Generative AI transforms stakeholder feedback into structured requirements by leveraging natural language processing to parse unstructured inputs like meeting transcripts, emails, notes, or user stories, then systematically extracting key elements such as functional needs, constraints, and priorities to output them in standardized formats including user stories, acceptance criteria, use cases, or requirement tables.
This process identifies ambiguities, resolves conflicts across sources, suggests refinements, and ensures traceability back to original feedback, enabling analysts to validate and iterate efficiently rather than starting from scratch. Unlike mere summarization or removal of redundancies, this structured conversion bridges the gap between raw business language and actionable technical specifications, accelerating development while maintaining completeness and alignment with stakeholder intent.