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What Makes AI-Generated Question Funnels Best For Stakeholder Interviews In Systems Analysis?
Discover how generative AI organizes stakeholder interviews for HR systems by creating focused question flows from general goals to detailed requirements, boosting productivity and requirement quality.
Question
You are preparing for a stakeholder interview to gather requirements for a new HR onboarding system. You decide to use generative AI to help plan your approach.
How can generative AI best support you in conducting this stakeholder interview?
A. It can create a fixed list of interview questions that stays the same for every project and does not adapt to stakeholder roles or project stages.
B. It can automatically generate business requirements by asking a few general questions and assuming that all stakeholders share the same priorities and expectations.
C. It can finalize a complete project plan during the interview by producing detailed requirements after only a limited amount of stakeholder input.
D. It can help structure the interview by organizing questions from broad goals to specific details, making the discussion more focused and productive.
Answer
D. It can help structure the interview by organizing questions from broad goals to specific details, making the discussion more focused and productive.
Explanation
Generative AI best supports stakeholder interviews for an HR onboarding system by generating a funnel-structured question sequence—starting with broad, open-ended probes like “What are the main challenges in current onboarding?” to uncover high-level goals, then progressively narrowing to specifics such as “How should new hire document verification integrate with payroll systems?” and behavioral scenarios like “Walk me through a typical first-day workflow for remote employees.”
This logical progression, customizable by stakeholder role (e.g., HR manager vs. IT lead), maintains focus, builds rapport, reveals dependencies systematically, and ensures comprehensive coverage of functional, non-functional, and edge-case requirements without premature closure or generic uniformity. Consistent with prior exam topics on tailored questioning and prompt refinement, this approach yields richer data, minimizes follow-up sessions, and aligns outputs directly with structured requirements elicitation best practices.