The BA’s Role in a GenAI World – Adapt, Thrive, Lead

A couple of years ago, the idea of a tool helping me write user stories or summarise a 50-page requirements document in minutes would have sounded like wishful thinking. Now, it’s just another Tuesday. Generative AI (GenAI) is no longer some distant “future tech” — it’s quietly becoming part of our daily workflows, whether we’ve embraced it or not.

As Business Analysts (BAs), our role has always been about connecting the dots: understanding business needs, translating them into clear requirements, and making sure solutions deliver real value. But in a world where AI can “write,” “analyse,” and even “suggest” solutions, it’s natural to wonder — where do we fit in?

The answer is simple: we fit right at the centre.

1. Framing the Problem — Still a Human Job
From experience, I’ve found AI great for sparking ideas, but it still can’t judge whether we’re tackling the right challenge. In one project, for instance, a client requested a reporting dashboard. Before jumping in, I used AI to map out possible features — but then had a conversation with stakeholders that revealed the real issue was inconsistent data entry. A dashboard would have been useless without fixing that.

That’s where BAs come in — we filter the noise, validate assumptions, and make sure the problem is worth solving before drafting a single requirement.

2. Using AI in Everyday BA Work
Over the past year, I’ve started weaving AI into my BA toolkit, not as a replacement, but as a sidekick. Here are some real examples from my work:

Writing User Stories:
When drafting user stories, I sometimes start by giving AI a short project brief and a couple of acceptance criteria. It spits out a rough draft, and then I rework it to reflect the project’s language, priorities, and the nuances only a human BA would notice. It saves lot of my time and effort.
Tools I’ve used: ChatGPT, Microsoft Copilot (Word / Excel)

Requirement Clean-Up:
When my requirement matrix starts to look like alphabet soup, AI helps me spot inconsistencies and standardise formatting.
Requirement docs have a way of getting messy — different formats, phrasing, and a few half-written lines from several people. Instead of spending hours fixing it by hand, I paste the content into an AI tool and ask it to put everything into one consistent structure.
The cleaned-up doc is much easier for the team to scan and review.
Tools I’ve used: ChatGPT, Microsoft Copilot (Word / Excel)

Data Insights: 
I’ve pasted raw defect logs into AI tools to quickly see patterns — like a spike in errors after a particular release. It’s not the final analysis, but it gives me a head start.
Large defect logs or feedback lists can be overwhelming. I run them through an AI assist to flag trends or spikes — for example, a jump in errors tied to a single API after a release. That gives me a clear starting point for a deeper investigation.
Tools I’ve used: ChatGPT (with data prompts), Copilot for Excel / Power BI

Workshop Prep: 
In a recent discovery workshop, I used Miro’s AI to sort sticky notes from our brainstorming into clear themes. It shaved off about half an hour of manual work and let the team stay in the flow of the conversation.
Tools I’ve used: Miro

Writing Stakeholder Summaries:
After long workshops or calls, I drop my rough notes or transcript into an AI summariser to get a tidy first draft of decisions and action items. I make sure to tweak the tone and check facts. It actually saves a lot of rewriting time.
Tools I’ve used: Fireflies (for transcripts), ChatGPT or Grammarly for summarising and polishing

Drafting Survey Questions:
If I need to run a quick survey, I tell AI the goal and the audience and it suggests a list of questions I can reuse or edit. It’s a fast way to get a helpful first-pass set of questions.
Tools I’ve used: ChatGPT, Google Forms (templates)

Building Quick Visual Aids:
A simple diagram can clear up confusion faster than paragraphs. I give AI a short description of the process and it suggests a draft flow or diagram that I refine in the usual tool. It speeds up stakeholder alignment.
Tools I’ve used: Miro AI, Lucidchart, Whimsical

Competitor & Market Research: 
When I need to understand what competitors are doing, I collect their product pages, reviews, or updates and feed them into AI. It gives me a fast snapshot so I can go into stakeholder meetings with sharper questions.
Tools I’ve used: Perplexity AI, ChatGPT (with browsing), plain Google searches

The trick here isn’t just using AI — it’s knowing when to trust it, and when to double-check.

3. AI Won’t Replace Core BA Skills
Yes, tools like ChatGPT can produce a neat-looking set of requirements, but they don’t know the “why” behind them. They don’t see the tension between two departments, or understand that a certain workflow was kept in place to meet a regulatory rule.

BAs do more than gather requirements — we interpret context, manage conflicts, and bridge the gap between technical teams and business users. AI can draft a user journey map, but it won’t pick up on the subtle user frustration you notice in a stakeholder interview.

4. Collaborating Across Roles
A surprising advantage of AI is its ability to help me connect people who speak completely different “work languages.” Something I didn’t expect is how AI can smooth communication between very different stakeholders. For example, if I’m working with a developer who talks in API calls and a business manager who only cares about getting their report on time, AI can help me translate — creating a quick diagram or plain-English summary that everyone understands.

5. Adapting Without Losing Your Edge
I know some BAs are nervous about AI “taking over,” but here’s how I see it: the professionals who learn to work with AI will outpace those who ignore it. This doesn’t mean blindly accepting everything AI produces — it means using it to get past the grunt work so we can focus on strategic thinking and relationship building.

If a BA spends less time formatting a document, they have more time to challenge assumptions, validate requirements, and explore alternative solutions — all the things that actually create business value.

Final Thoughts
For Business Analysts, the job isn’t disappearing — it’s just taking on a new shape. We’re still the ones who dig into the real problems, check if the fixes will hold, and translate between the people building the solution and the people who’ll use it. What’s new is simply a tool that lets us pick up the pace. So keep your curiosity sharp and your eyes on value, and the road ahead feels full of opportunities.

“The future of the BA role isn’t written yet — and that’s the most exciting part.”