AI is going to be foundational for everything built in the future. It is the smart way to go, to maximize the knowledge from historical data and free up human capabilities from mundane tasks. However, capturing requirements for AI apps is vastly different from how we have captured waterfall or agile requirements. If we miss key aspects, an episode from Black Mirror won be far from reality. Whether it will happen or not - we can't predict, but what can we do as part of requirement analysis today - will make a difference in the development of AI solutions. We will also go through some cases and exercises to flex our analysis muscle.

Objective 1
What does AI readiness look like
Objective 2
Principle and guidance to consider when developing AI solutions
Objective 3
Understanding why AI requirements is different from before

 

Senior Advisor for the CEO and President of the International Institute of Business Analysis (IIBA).
One of the leading references for Business Analysis in Brazil and internationally, Fabrício Laguna has spent
more than 25 years helping organizations and professionals improve outcomes through Business Analysis,
strategy, innovation, and transformation.
Known for his energetic presentations, theatrical communication style, and ability to explain complex concepts
in a charming and approachable way, Fabrício combines deep professional expertise with humor, storytelling,
audience participation, and emotional connection.
Author of “Please Hold – The Power of Outcome-Driven Thinking”. His work exploring BA4AI positions Business
Analysis as an essential capability for guiding organizations through responsible and outcome-driving AI
transformation.
Performing live, on YouTube, or through his online courses attended by students in more than 73 countries,
Fabrício inspires professionals to lead with confidence, competence, and humanity in times of exponential
change.

https://thebrazilianba.com

 

ABSTRACT

 

Artificial Intelligence is rapidly transforming organizations, careers, and the way businesses make decisions. But behind the excitement and innovation, many professionals are silently asking themselves an uncomfortable question: “Am I truly prepared to lead in the age of AI?” Confidence has a massive impact on performance. It enables action, influences decision-making, inspires leadership, and motivates people to move forward even in uncertain environments. But confidence without competence can be dangerous, while competence without confidence often remains invisible and underutilized. In this energetic and highly interactive keynote, Fabrício Laguna explores how Business Analysis develops the mindset, competencies, and human skills necessary to lead AI transformation responsibly and effectively. Through storytelling, humor, audience interaction, music, and even a surprising collective samba experience, attendees will discover that confidence is not simply a personality trait or natural talent. It is a practiced capability developed through discipline, learning, collaboration, analytical thinking, and continuous improvement. The presentation explores different dimensions of confidence and trust:
• Confidence in yourself
• Trust from others
• Confidence in technology
• Trust in Artificial Intelligence
• Organizational confidence during transformation
Using the principles behind BA4AI, Fabrício demonstrates why Business Analysis professionals are uniquely positioned to help organizations navigate the opportunities, anxieties, risks, and strategic decisions surrounding AI adoption. This keynote combines inspiration, reflection, practical insight, and collective energy to help professional business analysts recognize that they already possess many of the foundational capabilities needed to lead the future. What they need now is the confidence to step forward.

 

ABOUT THE SPEAKER

 

Imtiaz Kaderbhoy is a Business Analysis consultant, trainer and co-founder of Kilts and Kente, where he designs immersive learning experiences that blend storytelling, business analysis and emerging technology.
With over 20 years’ experience delivering complex change across industries, Imtiaz specialises in helping organisations apply Business Analysis practices to modern challenges, including AI adoption, data-driven decision making and responsible technology use.
He has delivered BCS-certified training, mentored apprentices to distinction level, and spoken at international conferences, where his sessions are known for being highly interactive, practical and grounded in real delivery scenarios.
His work focuses on one core idea: strong Business Analysis is critical to ensuring AI creates value, not risk.

Workshop description

The first MindBridge Goggles were supposed to revolutionise Business Analysis. They didn't. The MVP failed, customers weren't convinced, and the business paid the price.

Now MindBridge is being relaunched — and you are the team responsible for making it work.

In this three-hour immersive Business Analysis experience, delegates will work in teams to investigate what went wrong, understand customers and stakeholders, challenge assumptions, redesign the proposition and make difficult decisions about the next generation of an AI-enabled product.

But there is a difference.

AI is now part of your team.

Teams will use generative AI throughout the experience to support elicitation, analyse evidence, develop requirements, challenge ideas, evaluate options and create elements of their final presentations.

The challenge is knowing when to use it — and when not to.

Across the experience, teams will confront the tensions of Speed vs Trust, Listen vs Interpret, Augment vs Replace, and Value vs Risk. AI may accelerate the work, but delegates remain responsible for validating its outputs, identifying what it has missed and making the final decisions.

Inspired by emerging SFIA thinking around working effectively and responsibly with AI, the experience asks teams to continually decide whether an activity should be automated, augmented by AI or remain human-led.

The experience culminates in teams using AI to help create and deliver their case for the new MindBridge product — defending not only what they recommend, but how they used AI to reach those decisions.

The ultimate challenge is not whether AI can perform Business Analysis.

It is:

Can humans and AI work together to create better decisions and greater business value?

Thought-provoking outcomes

By the end of the three hours, delegates will have experienced rather than simply discussed:

1. AI-Augmented Business Analysis — using AI during real BA activities rather than simply prompting a chatbot.
2. AI-Augmented Elicitation — exploring whether AI can identify what stakeholders need, including what has not been explicitly stated.
3. Requirements Engineering with AI — generating, challenging, refining, prioritising and validating AI-supported requirements.
4. Human vs AI judgement — recognising when AI accelerates analysis and when context, empathy, critical thinking and professional judgement change the answer.
5. Responsible AI — confronting questions of trust, bias, evidence, privacy, explainability, oversight and accountability.
6. Intelligent Value Creation — moving beyond “What can AI do?” towards “What should we do, for whom, and what value will it create?”
7. AI-enabled communication — using AI to turn analysis into a compelling presentation while remaining accountable for the recommendations being presented.

 

Leading AI upskilling in my team across a 100+-specialist Business Analysis Office at ELEKS taught me that most "AI for BAs" advice is either too vague or too technical - so I built an evidence-based alternative by analyzing market data, job postings, mapping skills to BABOK, and field-testing AI toolchains in in-house initiatives, R&D and commercial project workflows. What the market signals reveal is both a challenge and an opportunity: the vast majority of AI-related BA roles still hover at the "AI-ready" stage, yet professionals who bridge the gap to genuinely AI-native practice unlock a measurable career premium - and from my experience, the shift starts with blending AI tools into how we frame problems, structure knowledge, and collaborate with AI as a thinking partner. This presentation gives you the exact skills map, self-assessment scoring, and three concrete learning pathways I developed for my own team - so you can stop guessing and start closing the gap strategically.

Key takeaways

• (1) A tiny fraction of AI BA roles are truly AI-Native — that's where the significant salary premium sits, and most of us aren't there yet.
• (2) The real shift isn't learning new tools, it's rethinking how you structure problems and reason alongside AI.
• (3) A comprehensive skills map with multiple learning pathways lets you stop guessing and start closing your biggest gap first.

In today's increasingly digital and AI-driven world, successful Business Analysis requires more than gathering requirements and managing backlogs. It requires understanding people.

Business Analysts are trained to analyze information, identify patterns, uncover underlying needs, and make sense of complex situations. But what if that same analytical mindset could also be applied to people? Stakeholder interactions often involve feelings, attitudes, and concerns that are not fully expressed through words. Facial expressions and other nonverbal signals can provide additional information that helps Business Analysts develop a deeper understanding of how stakeholders are responding.

Dr. Paul Ekman's research on facial expressions of emotion identified seven universal expressions: happiness, sadness, anger, fear, surprise, disgust, and contempt. But what makes these expressions universal, and how can we recognize them in real interactions?

Recognizing an expression is only half of the task; the other half is knowing what to do with it. Ekman's research gives us a vocabulary for what we see, and this session adds a method for what to do next: SWAC (See, Wonder, Ask, Confirm). SWAC turns the observation of facial expressions into a structured habit: notice a signal, consider several possible explanations, ask open questions, and confirm understanding through conversation. By applying an analytical mindset to human behaviour, Business Analysts can become more attentive to emotional responses and attitudes, identify signals that may warrant further exploration, and better anticipate how stakeholders might respond.

Real Business Analysis situations will show how SWAC complements stakeholder conversations, elicitation, and decision-making, helping BAs recognize unspoken concerns and respond more effectively.

The goal is not to "read" minds or make assumptions about what a stakeholder thinks. SWAC treats every observation as a hypothesis to explore, adding another layer to established Business Analysis practices and helping BAs ask better questions, explore concerns more effectively, and build a richer understanding of the people behind the requirements.

Session Takeaways

What attendees will take away from this session:

• The seven universal facial expressions identified by Dr. Paul Ekman, how to recognise them in real interactions, and how culture and context still shape when we show or mask them
• SWAC (See, Wonder, Ask, Confirm), a practical loop for turning a nonverbal signal into a better question
• How to treat what you observe as a hypothesis to explore, not a conclusion about what someone thinks
• How to apply this in real BA work: stakeholder conversations, elicitation, workshops, and decision-making

“I will put more focus on my growth when things slow down.” How many times have we heard people say that? But what happens if things never slow down and everything runs fast like a bullet train? How to do your job as a BA effectively in such an environment, and lead the people at the same time. Not just any people, not just BAs, but different roles, such as engineers, QAs, designers, and BAs? How to know what each person needs and help them grow on their career path. How to balance discovery, delivery and leadership while staying competitive at the same time? I will show what it means to be a Business Analyst in a demanding and fast-paced client environment, where change is the only constant. In this environment, it is not enough to simply do a good job. To stay relevant, both individuals and teams must continuously adapt, perform and grow — often without dedicated time to do so. Unlike traditional BA leadership, this setup introduces a unique complexity: I am responsible for people I don't see daily, across roles I don't do myself (developers, QAs, designers) while being fully accountable for my own BA work in delivery and discovery. This session shows a different perspective: the BA mindset as a leadership tool and advantage.

Key takeaways

• The BA mindset is a leadership tool, not just an analysis skillset.
• You can grow people across roles, without having to deep dive into their technical domains.
• People development requires using the available time in a different way.
• Instead of perfect discovery, we can have multiple mini discoveries inside delivery.

ABOUT THE SPEAKER

Milena Mileva is a passionate and enthusiastic Business Analyst with over 25 years of experience, also having worked as a Business Architect, Product Owner, and Digital Transformation Manager. A strong advocate for agile ways of working, she brings a hands-on, practical approach to business analysis, product development, and organizational change. She is a Board Member of the IIBA Bulgaria Chapter and a Fellow of BCS, The Chartered Institute for IT.

Abstract

Business Analysts often start initiatives with a clear solution focus, only to find themselves overwhelmed by stakeholders, dependencies, and organizational silos. This session is grounded in a real-world project to implement a document management system, where contracts quickly exposed a broader challenge: managing relationships across a service ecosystem. As stakeholder analysis kept expanding, a simple question emerged: what if we started from business architecture perspectives instead? By stepping back and reframing the problem through selected business architecture tools, it became possible to reconnect fragmented views, regain context, and support better decisions. This talk shows how Business Analysts can pilot business architecture thinking in everyday projects to better understand complexity, align stakeholders, and avoid silo-driven outcomes — without launching formal architecture initiatives.

Key takeaways

• A practical introduction to selected business architecture tools for business analysts.
• How these tools make the big picture visible and discussable.
• How early use of these tools supports reuse and prevents silo-driven solutions.
• When stakeholders are not ready for new tools or techniques, modelling can still be used as a thinking aid.

As artificial intelligence becomes embedded in everyday tools and enterprise workflows, Business Analysts are facing a fundamental shift in how they create value. We are moving from writing requirements for systems to designing interactions with AI that directly shape outcomes. While generative AI tools are widely adopted, their use in business analysis is often informal, inconsistent, and difficult to scale. This session explores how prompt engineering can be understood as a natural extension of core business analysis skills, enabling more structured, reliable, and repeatable use of AI. The talk introduces a practical framework that maps familiar BA concepts — such as business context, acceptance criteria, and use cases — into effective prompt design. Prompts are positioned as “requirements for intelligence”, requiring clarity, constraints, and well-defined outcomes, just like traditional requirements. The session also addresses the limitations and risks of AI usage, such as hallucinations, bias, and over-reliance on generated outputs, highlighting the evolving role of the Business Analyst as a quality gatekeeper.

Key takeaways

• A practical framework for writing high-quality prompts.
• Real examples of AI in BA daily work.
• Techniques to improve the reliability of AI outputs.
• A clear understanding of the BA's role in AI governance.

Speaking experience

Experience presenting in both academic and professional environments, including training at the Faculty of Mathematics, Belgrade, and multiple workshops for colleagues and business users.

Business Analyst and leader with over 7 years of experience driving change and delivering value in complex, international environments. Specialized in regulated industries such as finance, banking, accounting, legal and pharmaceuticals. Passionate about advancing the BA profession and serves as Vice-President of Communications at IIBA Bulgaria.

ABSTRACT

This presentation explores why the future BA cannot afford to be a yes-machine. AI is great at being agreeable — it does it well, always, and quickly. BAs should not do the same. The presentation discusses how the profession is evolving toward strategic thinking, constructive challenge and human-centered influence. It examines the delicate balance between rigorous analysis and the interpersonal skills required to avoid being perceived as negative or obstructive. The talk highlights how credibility — built through subject-matter expertise, industry knowledge, experience and qualifications — helps stakeholders welcome challenge rather than resist it.

Key takeaways

• AI is very good at being agreeable — it is built that way on purpose.
• BAs should not try to compete with AI on agreeableness.
• BAs should focus on skills AI cannot replace: critical thinking, challenging assertions, and fighting for what is right.
• BAs should be able to challenge and question without being perceived as negative, through credibility, communication skills and expertise.
• Develop critical thinking, subject-matter expertise and negotiation skills to future-proof your career.

Speaking experience

In the last 12 months: speaker at the Balkan BA Conference in Bucharest 2025, the IIBA Poland Summit 2025, two IIBA Bulgaria local events, and several company-wide events.

ABOUT THE SPEAKER

Test Manager with a master's degree from the Faculty of Electrical Engineering in Sarajevo and over 15 years of experience in test automation and test management, with a strong focus on technical improvements and effective testing strategies. Proficient in C# and Java, she has built automation frameworks from scratch and now works in an AI-focused team, exploring how AI can analyse real user behaviour, improve test coverage, and transform traditional software testing.

ABSTRACT

Quality assurance is entering a new and transformative era. Traditional testing approaches, built around deterministic systems with clearly defined inputs and expected outputs, are no longer sufficient. How do we ensure reliability when behaviour is probabilistic rather than predictable? Just as importantly, how do we ensure that AI systems deliver measurable business value, align with stakeholder expectations, and support real user needs? This talk explores how software testing must adapt and introduces a structured approach to AI quality assurance, while highlighting the growing role of Business Analysis in defining requirements, evaluating risks, and connecting technical quality with business outcomes. It covers traditional vs. AI systems, an AI Testing Pyramid (model validation, bias detection, monitoring, business impact), the role of Business Analysis in AI quality, adapted tools and techniques, and a hands-on example based on a widely used AI chatbot system.

Key takeaways

• Understand the key differences between testing traditional software and AI systems — probabilistic behaviour, data dependency, and evolving outputs.
• Learn practical QA and Business Analysis strategies for validating AI solutions, defining success criteria, and ensuring alignment with business goals.
• Discover modern testing approaches, tools, and automation techniques for building reliable, scalable, and valuable AI-powered products.

Cristina Gheorghiu, CBAP, has 15 years of hands-on experience in Business Analysis across the public and private sector. A long-standing member of the Romanian Business Analysis community, she was Education and Certification Director of the IIBA Romania Chapter for 5 years and President for 1 year.

Value is often claimed but rarely examined. Projects are delivered, features are released, and processes are optimized — yet the question remains: what value was truly created? This presentation explores the art of working with value as a deliberate and continuous practice. Value does not emerge at the end of an initiative, but is shaped from the very beginning by how objectives are defined and aligned to real needs. Another highlight is that value must be measured intentionally; failing to define measures can lead to misunderstandings and false expectations. Finally, the presentation emphasizes that value is present in every decision we make — in how we explore problems, design processes, and deliver outcomes — not only in the final result. This session challenges Business Analysts to make value visible, measurable, and central to their work.

Key takeaways

• Value starts from the beginning, in how the objectives are set.
• Value is in everything we do — process or result.
• Value must be measured; don't fool yourself that you will define it or learn it later.

Natasha Kostikj Miloshevski is an experienced Business Analyst at Endava, blending technical expertise with strategic insight to drive impactful digital solutions. With a background in software development, IT security, and project leadership, she focuses on bridging business needs with engineering execution. 
Natasha works on agentic AI and AI-native product delivery, developing frameworks that enable organizations to implement autonomous systems responsibly.
She promotes a product mindset balancing autonomy, governance, and sustainability.

 

Tanja Kekenovska is a Senior Business Analyst at Endava whose work connects data, business analysis, and product thinking. She brings a strong product mindset to complex technology challenges, translating emerging capabilities into practical, value-driven solutions.
Known for her collaborative approach and structured thinking, Tanja works with cross-functional teams to design scalable, responsible systems and help organisations apply product thinking to the next generation of AI-enabled and intelligent software.

 

ABSTRACT

 

Aleksandar Jovicic is a Senior Business Analyst with over 20 years of experience in banking and software delivery, having worked as Business Analyst, Product Owner, and Product Manager on enterprise-scale systems in digital banking, payments, and treasury. He holds a PhD in IT Management, degrees in law and economics, and is certified in Scrum and SAFe.

This talk explores how large language models (LLMs) are trained and refined through human expertise, based on real-world experience working on AI systems for leading organizations. While much of the public focus is on model architectures and scale, the role of human input in shaping model behaviour remains critical. The presentation provides an inside perspective on how humans contribute to training, evaluating, and aligning AI systems — turning raw models into reliable, useful tools. It covers practical aspects of human-in-the-loop processes, including data annotation, feedback loops, quality control, and collaboration with engineering teams. Attendees will gain a clearer understanding of how AI systems actually improve over time and why human judgment remains essential.

Key takeaways

• How large language models are actually trained beyond theory and hype.
• The critical role of human feedback in shaping AI behaviour and quality.
• Real-world challenges in aligning AI systems with human expectations.
• Practical insight into human-in-the-loop workflows.
• Why human expertise remains essential despite increasing automation.

She believes the future of AI is not just in what we build—but in how we build it: embedding intelligence directly into the development process to create smarter, faster, and truly human-centered solutions.

 

Lejla Kameric brings over 25 years of experience in banking IT, currently driving SME Lending delivery at group level. From developer to business analyst to Head of IT Demand, she’s worn many hats— always focused on bridging business needs with smart tech solutions. Passionate about agile, people, and progress, she thrives at the intersection of tech and business impact.

AI is rapidly entering software delivery — from generating code and documentation to supporting analysis and testing. However, one key question remains unanswered in most organisations: is it actually improving productivity?
Many teams claim faster delivery due to AI, but traditional metrics such as story points or velocity rarely reflect real efficiency gains. In some cases, they even hide them.
In this session, I will share practical experience from introducing AI-enabled ways of working in delivery teams and the challenges of proving their impact. The focus will be on the gap between perceived and measurable productivity, and why most organisations struggle to demonstrate real benefits.

We will explore:

• Why commonly used metrics (e.g. story points, velocity) do not capture AI impact
• Typical pitfalls when trying to measure productivity improvements
• How AI adoption can distort existing performance indicators instead of improving them

The session will also present a pragmatic approach to measuring what actually matters in delivery:

• Throughput, cycle time, and delivery predictability
• Quality indicators such as defects and rework
• The role of time tracking and effort distribution in understanding real efficiency

This session is based on real delivery experience and focuses on what works, what doesn’t, and what still remains unclear when it comes to measuring AI productivity.

A product and technology professional focused on using AI to accelerate digital product development, with a particular interest in prompt engineering and rapid prototyping. Recently led the development of an AI-powered corporate banking onboarding prototype.

Discover how we built a complete B2B banking onboarding experience using intelligent prompting and rapid prototyping tools to transform complex requirements into a working application.

Key takeaways

• AI-powered design: ChatGPT accelerated requirements gathering and prompt engineering, reducing planning time by 70%.
• Rapid prototyping: Lovable enabled quick iteration from concept to working prototype in days instead of weeks.
• A complete, end-to-end corporate onboarding flow covering compliance, documentation, and product selection.

• Why generic AI capability is not enough, and where the gap between prompting and
real business analysis becomes costly.
• The preparatory layer that must precede agent orchestration: problem framing,
persona and journey analysis, process and data readiness, and value definition.

• How business analysis shapes the business logic that an orchestration of specialised
agents can actually be built upon.
• A concrete, end-to-end view of a banking application reaching a working result
through analysis, AI-assisted build, and customer experimentation.
• The AI Solution Design Canvas, a practical tool for designing the future AI solution
and preparing the prototype toward an MVP.
• Why the business analyst becomes more, not less, essential as AI delivery matures.

 

Senior Advisor for the CEO and President of the International Institute of Business Analysis (IIBA).
One of the leading references for Business Analysis in Brazil and internationally, Fabrício Laguna has spent
more than 25 years helping organizations and professionals improve outcomes through Business Analysis,
strategy, innovation, and transformation.
Known for his energetic presentations, theatrical communication style, and ability to explain complex concepts
in a charming and approachable way, Fabrício combines deep professional expertise with humor, storytelling,
audience participation, and emotional connection.
Author of “Please Hold – The Power of Outcome-Driven Thinking”. His work exploring BA4AI positions Business
Analysis as an essential capability for guiding organizations through responsible and outcome-driving AI
transformation.
Performing live, on YouTube, or through his online courses attended by students in more than 73 countries,
Fabrício inspires professionals to lead with confidence, competence, and humanity in times of exponential
change.

flaguna@gmail.com.br
https://www.linkedin.com/in/fabricio-laguna/
https://thebrazilianba.com

 

 

 

 

 

Senior AI Business Analyst, trainer, and mentor specializing in Product Management and artificial intelligence (ML, Gen AI, Agentic AI). Certified CBAP, PMP, and TOGAF EA Practitioner. Experienced in training, mentoring, pre-sales, and translating AI capabilities into business outcomes for clients across Europe, North America, and the Middle East.

Agentic AI has become a buzzword, and finding practical examples of how it solves real-world business analyst hurdles is nearly impossible. This session will help you denoise what's behind Agentic AI through examples and a BABOK-aligned lens, and show how file-based context, reusable skills, and real project artifacts can ease your workload. Participants are encouraged to bring their own BA challenges, use cases, or messy project situations, which the lecturer will work through live. The session covers where Agentic AI can support BA work (elicitation, analysis, requirements engineering, stakeholder preparation, solution evaluation, modeling, documentation), how to use project documents as context, reusable AI skills and workflows for common BA activities, and visual model creation. A major part is dedicated to live audience use cases, and participants receive a curated follow-up pack of references and practice materials.

A business analysis professional with more than 20 years of experience in the IT sector, primarily in software development, across roles such as developer, team lead, project manager, director of a software house, and business analyst. He holds CBAP, PMP, AAC, and CBDA certifications and is one of the founders of the IIBA Bulgaria Chapter.

ABSTRACT

Have you ever been in a meeting that dragged on or ended without clear decisions? In this interactive workshop, participants explore Edward de Bono's Six Thinking Hats method, experimenting with parallel thinking to improve group discussions. Using the group as a “laboratory,” teams create an innovative product concept and test different structured thinking approaches in a hands-on environment. A brief theoretical introduction is combined with practical exercises designed to generate insights, “a-ha” moments, and immediately applicable techniques. Participants gain tools to structure discussions, enhance collaboration, and apply the Six Thinking Hats method in their own meetings and workshops. 

Darko Kantic
Darko is a software architect and Domain-Driven Design (DDD) practitioner with over 20 years of experience designing, building, and evolving software systems.
He helps teams solve complex business problems through deliberate software and architectural design. He collaborates closely with both domain experts and developers to translate business domain knowledge into clear development models with well-defined boundaries and sustainable system architectures.
Over the years, he has seen many systems struggle not because of technology choices, but because of a lack of comprehension of the actual business problem and poorly defined service boundaries. Domain-Driven Design has proven invaluable in addressing these challenges, enabling teams to structure software to match business reality, reduce accidental complexity, and create systems that can evolve over time.
He holds an MSc in Computer Science and has worked with organisations across finance, healthcare, the public sector, NGOs, education, and industry, including the New York Stock Exchange, Oracle, Pfizer, Oxfam, the University of Manchester, the Open University, La Poste, and Bundesdruckerei.

Branka Nesterovic Haining
Branka Nesterovic Haining is a Business Analyst at with 20+ years of experience working across complex organisations in both the UK and internationally. Throughout her career, she has worked at the intersection of strategy, people and delivery, helping organisations make sense of complexity and turn it into clear, workable action.

Her experience spans digital transformation, operational change, business analysis, process improvement and cross-functional delivery, with a particular interest in how organisations maintain clarity, alignment and effective communication as they grow and evolve.

 

ABSTRACT

 

 

Most projects begin with documents, meetings, and specifications, yet misunderstandings between business and development teams often emerge months later - when changes become costly and difficult.
This interactive workshop introduces EventStorming, a collaborative modelling technique created by Alberto Brandolini, as a way to uncover these misunderstandings early. Using a fictional case of a sports race management system, participants will work together to visually map business processes using simple tools such as sticky notes.
Through this hands-on session, participants will learn how to:
Explore and understand how a business process actually works
Reveal hidden assumptions and gaps in knowledge
Align stakeholders with different perspectives
Identify key events and critical moments within a process
This is a participatory workshop rather than a lecture. It is particularly valuable for Business Analysts, Product Owners, System Analysts, and domain experts involved in defining or improving business processes. No technical background is required.
 

What happens when business analysts stop waiting for the perfect tool and start rethinking how they work? This interactive workshop presents a practical, experience-based approach to transforming messy, unstructured input into clear, usable analysis. Grounded in BABOK v3 principles and shaped by real-world BA practice, the session demonstrates how AI can support (not replace) analytical thinking. Rather than focusing on theory or generic AI capabilities, participants will engage directly with realistic scenarios. Using raw notes (their own or provided), they will structure information and run it through an AI-supported workflow designed by experienced BAs to streamline everyday tasks. The session highlights how repetitive and time-consuming aspects of analysis can be automated while preserving the critical judgment and expertise of the BA role. It also opens a discussion on where this approach delivers real value, how it impacts daily work. 

Key takeaways

• AI can enhance, not replace, the BA’s analytical thinking and expertise
• Structured approaches remain essential when working with unstructured inputs
• Practical workflows can significantly reduce time spent on documentation
• BA professionals should actively shape how AI is applied in their field

Dženana Bričić Kerla: is a Senior Business Consultant and CBAP® certified Business Analyst with a background in software engineering and over nine years of experience in the IT industry. Her expertise spans business analysis, requirements management, and translating complex business needs into effective technology solutions. With experience across both technical and business domains, she brings a unique perspective on career development in Business Analysis and the importance of continuous professional growth..

Dženana Džaferović: As a mathematics teacher turned Business Analyst, Dženana brings a unique combination of educational experience, analytical expertise, and banking industry knowledge. Since transitioning into the banking sector in 2017, she has gained experience across different areas, beginning with an internship in Market and Liquidity Risk and progressing into the current role as a Business Analyst in Data Management. I specialize in bridging business requirements and data-driven solutions, leveraging a structured and analytical approach to address complex challenges and deliver practical outcomes. 

 

Vedran Šajević is an Agile Project Manager and Business Analyst focused on AI product development within the B2B SaaS industry. Bringing 10 years of experience in Organizational Psychology into the technology space, he connects human behaviour, business needs, and data to build products that make people’s lives better. He will also share his certification journey from a project management to business analysis perspective.

Andy Grazebrook: IIBA Program Partner Manager for Europe, brings more than 20 years of experience in relationships and business development across the institutional and not-for-profit sectors. In his current role, he develops and nurtures partnerships supporting the International Institute for Business Analysis across Europe.