The AI Revolution: How BAs Can Leverage GenAI for Requirements Elicitation

Introduction: Is AI a Threat or a Superpower for Business Analysts?

Are you a Business Analyst feeling the pressure of an AI-driven future?

With Generative AI (GenAI) moving into workplaces quickly, many Business Analysts (BAs) are worried whether their job of collecting requirements will disappear. Activities like talking to stakeholders, reviewing documents, and running workshops raise a common question—will AI take over all of this?

The answer is no.

In fact, GenAI is becoming a powerful assistant for modern Business Analysts. It helps them gather deeper insights, start projects faster, and create better-quality requirements than ever before.

This article explains how BAs can use Generative AI for requirements elicitation, without losing their critical role in an AI-powered world.

Why Traditional Requirements Elicitation Isn’t Enough Anymore

Collecting requirements has always been a core part of the role of a Business Analyst. However, traditional methods come with several challenges.

Common Issues for Business Analysts

• Stakeholders are often busy or unavailable

• Requirements may be unclear or conflicting

• Reviewing legacy documents takes a lot of time

• Manual note-taking can miss critical details

• Project delays occur due to slow discovery cycles

Real-World Example

Consider a BA working on a banking digital transformation project. They face:

• More than 200 pages of old Business Requirements Documents (BRDs)

• Multiple stakeholder groups such as IT, Compliance, and Operations

• Very tight delivery timelines

This is exactly where GenAI creates massive value.

What is Generative AI and Why It Matters for Business Analysts?

Generative AI is a type of AI that can:

• Understand natural language

• Generate text, summaries, insights, and questions

• Analyze unstructured data

• Support better decision-making

For Business Analysts, GenAI works like a smart assistant, not a replacement.

According to IBM on Generative AI, GenAI improves human decision-making rather than replacing human roles.

Problem / Solution: GenAI as the BA’s Hidden Tool

The Problem

Many BAs worry that AI might make their role obsolete.

The Reality

GenAI cannot understand business context, organizational politics, or long-term strategy. That responsibility still belongs to the Business Analyst.

The Solution

A BA who learns GenAI becomes:

• Faster

• More insightful

• More strategic

• More valuable to the organization

How Business Analysts Can Use GenAI for Requirements Elicitation

1. AI-Helped Stakeholder Interview Preparation

Instead of reusing generic questions, BAs can use GenAI to:

• Generate role-specific interview questions

• Identify hidden assumptions

• Predict potential problem areas

Example
A BA working on an HR payroll system uses GenAI to review project scope and prepare customized questions for HR, Finance, and IT stakeholders—identifying missing compliance requirements before meetings even begin.

This enhances traditional requirements elicitation techniques.

2. Smart Analysis of Stakeholder Interviews

After interviews, GenAI can:

• Summarize conversations

• Identify common themes

• Highlight conflicting requirements

• Detect emotions like urgency or frustration

Real-World Example
For an e-commerce website redesign, a BA conducts 10 stakeholder interviews. GenAI helps by:

• Grouping feedback into features and constraints

• Identifying repeated checkout issues

• Highlighting high-risk areas needing attention

The BA still validates and prioritizes the findings—but much faster.

3. Automated Document Review (BRDs, Policies, Contracts)

Reading long documents is one of the biggest pain points for BAs.

GenAI can:

• Summarize lengthy documents

• Extract key business rules

• Detect missing or conflicting requirements

• Compare old and new documentation

Example
A BA analyzing healthcare compliance policies uses GenAI to extract mandatory regulations and map them directly to system requirements—reducing analysis time from weeks to hours.

4. Helping to Write Initial Requirements

GenAI can generate:

• Draft user stories

• High-level functional requirements

• Acceptance criteria

⚠️ Important Note:
The Business Analyst must still:

• Validate accuracy

• Apply business judgment

• Align requirements with business goals

Agile Example
In a Scrum environment, a BA uses GenAI to convert stakeholder inputs into well-structured user stories, following user story writing best practices and accelerating backlog creation.

5. Finding Hidden Needs and Risks

GenAI is also effective at identifying:

• Missing non-functional requirements

• Security and performance risks

• Unclear dependencies

Example
In a fintech application, GenAI highlights the absence of audit trails and unclear data retention policies. The BA confirms these gaps with stakeholders, preventing costly issues later.

Speed + Insight Like Never Before

With GenAI:

• Discovery cycles are faster

• Insights are deeper and data-driven

• BA work shifts from documentation to strategy

This transformation is supported by research such as McKinsey’s insights on AI in business transformation.

Why GenAI Won’t Replace Business Analysts

GenAI lacks:

• Business judgment

• Stakeholder trust

• Negotiation skills

• Industry intuition

• Ethical decision-making

Only a Business Analyst can:

• Resolve conflicting stakeholder needs

• Align requirements with business objectives

• Navigate organizational politics

According to Gartner’s analysis on AI and analytical roles, AI enhances analytical work—it does not replace it.

Skills BAs Should Develop in the GenAI Era

To stay future-ready, Business Analysts should focus on:

• Prompt engineering for business use cases

• Critical thinking and validation

• Stakeholder communication

• Data literacy

• Ethical and responsible AI usage

Learn more from IIBA on future Business Analyst skills.

Bold Truth: The AI Revolution Helps BAs, Not Hurts Them

The AI revolution is not about eliminating Business Analysts—it’s about redefining excellence in the BA role.

BAs who embrace GenAI will:

• Deliver insights faster

• Reduce project risk

• Create higher business value

• Lead AI-driven initiatives

Final Thoughts: The Future Belongs to AI-Enabled BAs

Generative AI is no longer optional. It is a career accelerator.

By combining:

• Human judgment

• Business expertise

• AI-powered insights

Business Analysts will remain central to project success in 2026 and beyond.

Call to Action

To future-proof your BA career:

• Learn GenAI tools

• Practice AI-assisted requirements elicitation

• Position yourself as an AI-powered Business Analyst

• Related Articles:

1️⃣ Business Analyst Fundamentals

URL:
https://www.bacareers.in/how-to-become-a-business-analyst/

2️⃣ Requirements Elicitation Techniques

URL:
https://www.bacareers.in/effective-requirement-elicitation-techniques/

3️⃣ Agile Context (GenAI + Agile)

URL:
https://www.bacareers.in/agile-methodology-for-business-analysts/

External Authority Links (High Trust + SEO Safe)

These links improve E-E-A-T (Experience, Expertise, Authority, Trust) and should be placed where concepts are discussed.

🌐 1️⃣ IIBA (Official BA Authority)

URL:
https://www.iiba.org/

🌐 2️⃣ Gartner – AI & Analytics

URL:
https://www.gartner.com/en/topics/artificial-intelligence

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Pallavi

Business Analyst , Functional Consultant, Provide Training on Business Analysis and SDLC Methodologies.

🌐 Founder of BACareers.in| Freelance Business Analyst & Content Writer | Banking Domain Expert | Agile Practitioner | Career Mentor

I am the founder and content creator of BACareers.in, a specialized platform for aspiring and experienced Business Analysts. I share real-world insights, career tips, certification guidance, interview prep, tutorials, and case studies to help professionals grow in the BA career path.

We have strong experience in Banking, Financial Services, and IT. We bring deep domain knowledge and hands-on expertise in core banking systems, payment integrations, loan management, regulatory compliance (KYC/AML), and digital banking transformations.

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