In today’s fast-paced digital landscape, business analysts (BAs) face growing complexity in gathering, clarifying, and validating requirements. Traditional elicitation techniques—such as stakeholder interviews, workshops, brainstorming, or document analysis—are still valuable, but they often demand significant time, coordination, and human effort. Enter Generative AI (GenAI) tools: intelligent assistants that can accelerate, enrich, and transform requirements elicitation into a more collaborative, data-driven, and continuous process.
This blog explores how generative AI is revolutionizing requirements elicitation, its advantages, potential pitfalls, and practical applications for business analysts and organizations.
Requirements elicitation is the process of discovering, gathering, and clarifying stakeholders’ needs and expectations for a product, service, or system. It is not just about asking “What do you want?” but about uncovering implicit needs, aligning conflicting perspectives, and translating business goals into actionable requirements. According to the BABOK® Guide, elicitation includes activities like preparing for elicitation, conducting sessions, confirming results, and communicating findings.
Traditionally, elicitation techniques include:
These approaches rely heavily on human facilitation skills, domain knowledge, and stakeholder availability. But with GenAI tools, the landscape changes dramatically.
Generative AI tools—such as ChatGPT, Claude, Gemini, or enterprise-grade domain-specific assistants—bring automation, creativity, and scalability into elicitation. Here are some ways they are reshaping the practice:
Before a requirements session, analysts spend hours reviewing existing documentation, industry standards, and stakeholder profiles. GenAI tools can summarize lengthy documents, extract key business rules, and generate interview questions or discussion guides tailored to each stakeholder group.
Example: A BA uploads a 200-page policy manual into an AI assistant, which then generates a concise set of elicitation questions aligned with compliance rules.
During workshops or interviews, GenAI can act as a co-facilitator. With the right prompts, it can simulate different stakeholder personas, propose clarifying questions, or suggest what-if scenarios to uncover hidden needs.
Example: A BA might ask the AI:
“Generate five probing questions to uncover potential risks in a loan approval workflow.”
Within seconds, the tool produces insightful queries, ensuring no critical area is overlooked.
Stakeholders often struggle to imagine new possibilities. GenAI tools can generate alternative solution ideas, user stories, or even mock prototypes based on partial inputs. This stimulates creativity and broadens the discussion.
Example: When eliciting requirements for a mobile banking app, the AI suggests additional features such as biometric login, AI-driven savings tips, or gamification elements—ideas stakeholders might not have considered.
One of the most time-consuming tasks for BAs is documenting elicitation results. GenAI tools can transcribe meetings, summarize discussions, and produce structured requirement artifacts such as:
This reduces manual effort and ensures stakeholders receive outputs quickly for review.
Requirements evolve. Generative AI can act as a living repository that continuously checks for ambiguities, conflicts, or missing details. By cross-referencing requirements with industry best practices or regulatory standards, it ensures higher quality and completeness.
While powerful, GenAI in elicitation is not without challenges:
The key is to treat GenAI as a co-pilot, not an autopilot.
Here are five real-world scenarios where GenAI tools can enhance requirements elicitation:
To effectively integrate GenAI into requirements elicitation, BAs should adopt these best practices:
As generative AI continues to evolve, we can expect even more advanced capabilities:
This evolution suggests a future where elicitation becomes continuous, intelligent, and predictive, empowering business analysts to focus more on strategic alignment and stakeholder value rather than clerical tasks.
Requirements elicitation has always been the cornerstone of successful projects. With the arrival of Generative AI tools, business analysts gain a powerful ally—one that accelerates preparation, enriches discussions, automates documentation, and ensures quality. However, success depends on using AI responsibly, blending human expertise with machine intelligence, and treating AI as a partner in discovery, not a substitute for critical thinking.
Organizations that embrace GenAI in elicitation will not only streamline their projects but also unlock new levels of innovation, stakeholder satisfaction, and business value.