AI for Business Analysis

This is a practical, hands-on course for experienced Business Analysts who want to integrate generative AI into real analysis work – responsibly and effectively.

Rather than treating AI as a separate skill or a replacement for analysis, the course positions AI as an accelerating collaborator that still requires your judgement, critical thinking, and accountability. You will work with leading AI assistants to explore how AI can support everyday BA activities such as starting projects, modelling processes and data, eliciting information, writing user stories, planning development, designing user experiences, and validating solutions. Throughout the course, you will engage in realistic exercises using a shared case study. By the end of the course, you will have a clear, experience-based understanding of where AI adds value and introduces risk, and how to maintain human oversight while benefiting from AI’s speed and flexibility.

During this course, you will learn about:

• Use generative AI to start analysis work
• Write prompts to clearly describe a problem, context, constraints and role
• Review AI-generated analysis to identify assumptions, bias, errors, and gaps
• Turn AI outputs into usable BA artefacts
• Maintain consistency and traceability
• Use AI for stakeholder management
• Organise and prioritise analysis work
• Recognise when AI is helping and when it is adding confusion to your analysis
• Apply ethical and responsible practices
• Create a practical plan for integrating generative AI into your own BA work

Understanding AI’s Role in Business Analysis

• Capabilities and limits of generative AI in business analysis
• Evaluate AI responses
• The impact of AI on the professional role

Using AI to Jumpstart a Project

• Apply prompting techniques
• Compare outputs from multiple chatbots
• Critique AI-generated content
• Create a preliminary Business Analysis Canvas

Modelling the Current State (Process View)

• Behavioural artefacts to describe current state
• Use AI to draft Process model diagrams
• Alternate and exception flows

Modelling the Current State (Data View)

• Identify entities, attributes and relationships
• Use AI to draft a data model diagram
• Generate data definitions
• Construct a CRUD matrix

Getting to Know People

• Identify and categorize stakeholders
• Construct RACI matrices and personas
• Detect and correct bias in AI-generated profiles
• Balance AI-driven efficiency with human engagement

 Interviewing & Elicitation

• Design interview questions and scripts
• Conduct simulated AI-generated interviews

Writing User Stories

• Generate, refine, merge user stories
• Classify stories to create a story map
• Evaluate AI-produced stories
• Maintain story-alignment

Planning Development

• Organise a Story backlog
• Use AI to propose MVP and sprint groupings
• Prioritise requirements
• Assess AI-based recommendations

 Designing User Experience

• Iterative refinement of UI prototypes
• Evaluate AI-produced designs
• Link interface elements to related requirements
• Integrate AI output and stakeholder feedback

 Writing Tests

• Generate test cases and data
• Structured formats such as Gherkin
• Evaluate AI-generated test coverage
• Automation-ready test descriptions

 Validating, Prioritizing and Coordinating

• Identify dependencies and impacts across BA artefacts
• Update related artefacts to reflect design changes
• Construct and interpret a traceability matrix
• How AI can support coordinated change management

 Implementing AI-powered Business Analysis

• Identify high-potential areas to pilot AI
• Plan change-management and measurement strategies for AI adoption
• Develop an ethical framework for responsible AI use
• Create a roadmap for AI integration

To get the most out of this course, it is recommended that participants have foundational knowledge of business analysis through formal training and have relevant experience working in a business analysis context. This is a very interactive and hands-on course. You will need access to at least two accounts with popular AI agents. The generative AI agents we will use are all available on the web and generally have free accounts. Common tools include Ms CoPilot, ChatGPT, Claude, Perplexity, and Google Gemini.

Attendees may also be interested in Expleo’s:

• BCS Certificate in Business Analysis Practice
• BCS Certificate in Requirements Engineering
• BCS Certificate in Modelling Business Processes
• BCS Foundation Certificate in Business Analysis
• BCS International Diploma in Business Analysis
• ICAgile Certified Agile Fundamentals
• ICAgile Certified Product Ownership

This course is designed for experienced Business Analysts and Product Owners who want to adopt generative AI in a grounded, professional way – improving productivity and insight without compromising rigor, responsibility, or trust. It may benefit other project team members, like Change Managers, Project Managers, Agile Coaches.