Article Highlights
- Business Analysis is a discipline that helps businesses run better, moving an organisation from current state to future state across People, Organisation, Process, and Information Technology (POPIT).
- Three challenges define modern BA work: the Capture challenge in busy workshops, the Speed of Analysis challenge when context decays fast, and the Consistency challenge when teams produce the same artefact five different ways.
- AI is not a replacement for the BA. It is a support system that transcribes in real time, structures raw notes faster, and aligns outputs to your team's templates and standards.
- The BAs who thrive will start small, prompt with clarity, keep their judgement central, bring their teams along, and stop waiting for permission to experiment.
This is Part 1 of a three-part series, The Journey of a Business Analyst using AI, by guest author Peter Agoro of The BA Mentor. Part 2 explores how AI maps onto the POPIT model in practice, and Part 3 covers how to embed AI into your BA practice sustainably. Look out for Part 2 on Wednesday 20 May 2026 and Part 3 on Wednesday 27 May 2026.
Live webinar with the author: Join Peter Agoro for AI + Business Analysis: A Powerful Combination on Wednesday 10 June 2026 at 12 PM EDT. Bring the questions this series raises and put them to Peter live.
The New BA Landscape: Use AI to your advantage
Imagine a world that would enhance what you do as a Business Analyst (BA).
I have been a BA for over a decade. How long have you been a BA for?
Ever thought about when you have run a busy workshop with stakeholders and you have played the role of scribe and facilitator? Ever thought that "I did not capture the last thing stakeholder A said," and realised that it was pivotal? Ever looked at a treasure trove of post-it notes that is aimed at modelling "how things get done" yet once everyone leaves the room it is more confusing than when you started?
I have answered "yes" to all and I am sure you have answered "yes" to some too.
Artificial Intelligence (AI) really does provide the answer to the challenges of the above points. Business Analysis has a new landscape, and this new landscape involves AI.
But how do we get to a point where we as BAs can embrace this new change and not see it as a threat?
What is Business Analysis, really?
Before we get there, let us remind ourselves of what Business Analysis is. Type "what is Business Analysis" into Google and you will get definitions like these:
- Business analysis is the professional practice of enabling organisational change by identifying business needs, defining problems, and recommending valuable solutions.
- Business analysis is the systematic investigation and evaluation of business needs to recommend solutions that achieve organisational objectives. It includes requirements gathering, stakeholder engagement, and process optimisation.
- Business analysis is an essential process conducted within an organisation that allows companies to thoroughly analyse every aspect of their operation, and create strategies for development.
Interesting definitions, but not quite clear for me. Was it clear for you?
After my fifth year of performing Business Analysis, I realised that Business Analysis is simply: a discipline that helps business run better.
Let us take this analogy to explain further:
- I currently weigh 100kg.
- I want to weigh 90kg.
- What do I need to do to get from 100kg to 90kg? I would need to exercise, change my diet to reduce carbs, know and understand my body type, and have good sleeping habits.
In essence, Point 3 is what we call "Business Analysis." Business Analysis is how Business Analysts help businesses get from the current state to the future state.
The only difference is that rather than the weight loss example, we apply Business Analysis to these four areas:
- People
- Organisation
- Process
- Information Technology
Some of you will know this as POPIT.
Why do we apply Business Analysis to these 4 areas? Simply, every company, whether for profit or not for profit, has people in it, has organisational structure, goals, and values, has processes (whether documented or not), and has Information Technology that enables everyone to do what they do better.
Essentially, a Business Analyst helps businesses run better by performing steps 1 to 3 of the analogy above, across all four POPIT areas, and ensures they all work synergistically together. If you are formalising this knowledge, the CBAP exam preparation case studies course is one of the most respected ways to demonstrate that practice at a senior level.
Now this is where AI comes in.
How AI can support your business to get from where it is to where it needs to be
Let us bring this back to the opening questions. The workshop. The post-it notes. The moment you missed what stakeholder A said. These are not small inconveniences. They happen to the best of us. I have sat in rooms with incredibly talented people and watched valuable insight get lost simply because there was too much happening at once. That is not a people problem. That is a capacity problem.
As a BA, you are expected to listen, challenge, document, manage the room, and keep one eye on the clock all at the same time. Unless there are resources to help you, a scribe or someone from the PMO, you pretty much do this by yourself.
So before we talk about what AI can do, let us be honest about where the current challenges actually sit.
What are the current challenges?
Think about a typical requirements gathering workshop. You have six stakeholders in the room, each with a different view of the world, each with their own agenda, and each speaking at the pace that suits them. You are scribing, facilitating, drawing on a whiteboard, and trying to make sure nobody talks over each other. At the end of the session you look at your notes and realise there are gaps. Not because you were not good enough. But because no single person can do all of that at full capacity at the same time. This is challenge number one: The Capture challenge.
Then there is the analysis piece. You leave the room with pages of notes, a voice memo you are not sure covers everything, and a set of post-it notes that made perfect sense in the moment when stakeholders were talking. Now you have to turn all of that into something structured, perhaps a process model, or a set of requirements, or a gap analysis. This takes time, and the longer it takes, the more context you lose. This is challenge number two: The Speed of Analysis challenge.
And then there is consistency. Every BA has their own way of working. Their own templates, their own shorthand, their own interpretation of what good looks like. When you are working in a team, that inconsistency creates friction. Stakeholders get confused when two BAs describe the same process differently. Delivery teams struggle when requirements are structured in five different ways across five different documents. This is challenge number three: The Consistency challenge.
None of these challenges are new. BAs have been managing them for years. But here is what is new. We now have tools that can genuinely help address them. And those tools sit under the umbrella of AI. If you have never formally explored what AI is and where it fits, Learning Tree's Introduction to Artificial Intelligence (AI) course is a one-day, foundation-level starting point built for exactly this audience. If you want a course built specifically for BAs working with AI, Learning Tree's AI-Driven Business Analysis course pulls together capture, analysis, and consistency in one BA-shaped curriculum.
AI will help Business Analysts do what they do better
I want to be clear about something here. AI is not here to replace you.
I have heard that fear more times than I can count and I understand where it comes from. But think back to the weight loss analogy. The goal is not to replace the person trying to lose weight. The goal is to give them better tools, better information, and a better plan so that they can actually get to the future state.
AI is the same for a BA. AI is not the BA. It is the support system around the BA.
So what does that support actually look like in practice?
For the Capture challenge, AI can now transcribe and summarise a workshop in real time. You can walk into a session, focus entirely on facilitating and challenging your stakeholders, and know that everything being said is being captured accurately in the background. No more missed moments. No more "I think stakeholder A said something important but I lost it in the noise."
For the Speed of Analysis challenge, AI can take a transcript or a set of raw notes and begin to structure them. It can identify themes, surface potential requirements, and flag areas of ambiguity that need further exploration. What used to take a BA a full day of post-workshop processing can now be turned around in a fraction of the time. The faster you can get structured output back in front of your stakeholders, the less misinterpretation there is. Approaches like the AI-Driven User Requirements course show exactly how to move from elicited need to structured artefact without losing fidelity.
For the Consistency challenge, AI can work within your frameworks. You can feed it your templates, your standards, and your ways of working, and it will produce outputs that align with them every time. That does not mean every BA becomes a carbon copy of every other. It means the baseline quality and structure is consistent. The BA adds the judgement, the relationships, and the contextual knowledge that no AI can replicate.
What do we need to do to get to the solution?
Getting to a place where AI genuinely improves how you work as a BA does not happen overnight. It requires some deliberate steps.
First, get comfortable with the tools. That does not mean becoming a technology expert. It means spending time with what is available, understanding what each tool can and cannot do, and starting to build them into your day-to-day practice. Start small. Try an AI transcription tool in your next workshop. See what it captures. See where it falls short. Learn from it.
Second, think about how you prompt. AI tools are only as good as the instruction you give them. If you ask a vague question, you will get a vague answer. But if you learn how to frame your prompts well, the outputs become genuinely useful. Think of it like briefing a junior analyst. The clearer your brief, the better the work they come back with.
Third, keep your judgement front and centre. AI will surface information, structure notes, and generate draft outputs. But AI does not know your stakeholders. It does not understand the politics in the room. It cannot sense when something said on the surface actually means something very different underneath. That is your job. That has always been your job. AI just gives you more time and headspace to do it well.
Fourth, bring your team on the journey with you. If you are working as part of a BA practice or within a delivery team, share what you are learning. Start conversations about how AI tools can be adopted consistently across the team. The consistency challenge only gets solved at the team level, not just the individual one. For an organisational view of the technology and its impact, Learning Tree's broader Artificial Intelligence Workforce Solutions is a good place to point your colleagues.
Finally, do not wait for permission. The BAs who will thrive in this new landscape are the ones who are already exploring, already experimenting, and already building their own understanding of what AI can do for them. You do not need a formal programme or a top-down mandate to start. You just need curiosity and a willingness to try.
So where does that leave us?
We are at a genuinely exciting point in the evolution of the Business Analysis discipline. The core of what we do has not changed. We still help businesses understand where they are, where they want to be, and how to get there. We still work across People, Organisation, Process, and Information Technology. We still need to build relationships, earn trust, and bring clarity to complex situations.
But the tools available to support all of that have changed significantly. BAs who recognise that and lean into it are going to find themselves doing better work, faster, and with a lot less of the friction that has always come with the job.
Coming Up Next in This Series
In Part 2 we will map AI capabilities directly onto the POPIT model and walk through real examples of how Natural Language Processing and Generative AI are already changing how BAs work across People, Organisation, Process, and Information Technology. In Part 3 we will look at how to embed AI into your BA practice sustainably, how to make the business case to your leadership, and how to stay ahead as the tools keep evolving.
For now, I want to leave you with one question to sit with.
If AI could take one thing off your plate as a BA today, what would it be?
Think about it. Because in Part 2, there is a good chance we are going to cover it. You can find more from me at The BA Mentor.
Recommended Learning Tree Training
To put the ideas in this post into practice, pair them with structured training across the disciplines an AI-driven BA needs to master:
Frequently Asked Questions (FAQs)
What is Business Analysis and why does AI matter to it now?
Business Analysis is a discipline that helps businesses run better by moving an organisation from its current state to a future state across People, Organisation, Process, and Information Technology (the POPIT model). AI matters now because it directly addresses three long-standing BA challenges, capturing stakeholder input in real time, accelerating analysis from raw notes to structured outputs, and producing consistent documentation across a team. The discipline has not changed; the toolkit has.
Will AI replace Business Analysts?
No. AI is the support system around the BA, not the BA. AI can transcribe a workshop, surface themes, and draft a first version of requirements, but it does not know your stakeholders, the politics in the room, or the contextual meaning behind what was said. Judgement, relationship building, and translation between business and technology remain human work. AI gives BAs more headspace to do those things well.
What are the three biggest challenges that AI helps BAs solve?
The Capture challenge, missing key stakeholder input while facilitating a busy workshop. The Speed of Analysis challenge, turning hours of notes, voice memos, and post-its into structured artefacts before context decays. And the Consistency challenge, different BAs producing the same output in five different shapes. AI transcription, summarisation, and template-aware generation now address all three at the source.
How should a BA start using AI without overcommitting?
Start small and stay deliberate. Pick one task that takes longer than it should, choose a single AI tool that fits, and use it on one project. Learn to write better prompts the way you would brief a junior analyst. Keep your judgement central, sense-check every output, and bring your team along by sharing prompts and patterns that work. Do not wait for a top-down mandate, curious practitioners will define what good looks like.
