#techtobusiness

By Suresh Kumar Prasad

In the fast-paced world of software development, user stories in tools like Jira are essential. They help agile teams capture what needs to be done, by whom, and why. But when it’s time to engage stakeholders—especially from non-technical or business backgrounds—those user stories often aren’t enough. That’s where Business Requirement Documents (BRDs) come in.

The good news? With the help of AI, transforming Jira user stories into polished, structured BRDs is easier—and faster—than ever.

At Vidushi Infotech SSP Pvt. Ltd., we’ve integrated this AI-powered approach into our own processes, saving time and improving clarity across departments. Here's how you can do the same.

Why This Conversion Matters

Jira user stories are great for developers and project managers. They follow the “As a… I want… So that…” format, which keeps things lean and actionable.

But business stakeholders need more:

Clear goals and metrics

Process flows

Compliance and scope details

Assumptions, constraints, and acceptance criteria

A well-crafted BRD translates technical intentions into a business-readable narrative.

Step 1: Use AI to Extract Key Components

Modern AI tools (including ChatGPT, of course) can analyze Jira tickets and extract structured data points:

Who the user is

What the desired action or feature is

Why it matters

Dependencies and blockers

Tags and priority indicators

We’ve built simple internal scripts that feed Jira exports into an AI model, which then outputs initial BRD sections like “Business Objective,” “Functional Requirements,” and “Stakeholders Involved.”

Even a raw CSV of tickets can be transformed into a well-organized draft.

Step 2: Add Context from Linked Stories or Epics

Often, user stories are linked to epics, tasks, or subtasks. AI can be trained to crawl through these connections and merge them into a single narrative.

For example, three stories like:

“As a customer, I want to reset my password.”

“As a customer, I want to receive a password reset email.”

“As a system admin, I want to log password reset attempts.”

…can be combined into a single “User Authentication and Recovery” section in your BRD.

AI helps synthesize fragmented items into coherent business themes.

Step 3: Convert Technical Acceptance Criteria into Business Language

AI excels at translation—not just across languages, but across professional domains. It can take developer-oriented acceptance criteria and rewrite them into business-aligned outcomes.

Instead of:

“System should send HTTP 200 on POST /api/reset-password”

You get:

“Users should receive confirmation after initiating password reset, ensuring the request is processed successfully.”

That’s something the head of operations or the compliance officer can actually understand.

Step 4: Incorporate Visuals Automatically

Several AI tools now generate flowcharts, swimlane diagrams, or entity relationship diagrams based on text input. With structured Jira story exports, these visuals can be built into your BRD draft automatically.

We integrated Mermaid.js and PlantUML with our internal AI assistant to generate diagrams directly from summarized story logic.

It adds polish—and reduces hours of manual diagramming.

Step 5: Review, Customize, and Collaborate

No AI-generated BRD should go out unreviewed. But the point is: the first 70–80% can now be automated, allowing analysts and product managers to focus on refining, validating, and tailoring the document.

In our experience, this has cut BRD prep time by 60–70% and reduced miscommunication significantly across business and technical teams.

AI isn’t replacing business analysts—it’s empowering them.

At Vidushi Infotech SSP Pvt. Ltd., we combine AI-driven productivity with human insight to deliver accurate, actionable documentation that bridges the gap between tech and business. As a nominee for the 2025 Go Global Awards, hosted by the International Trade Council in London, we’re proud to lead innovation not just in what we build—but in how we build it.