Course Overview
AI for Business Analysis 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 judgment, critical thinking, and accountability. You will work with leading AI assistants to explore how AI can support everyday BA activities such as starting projects, modeling 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. You will use AI to generate analysis artifacts, then evaluate those outputs for accuracy, completeness, bias, and assumptions. The emphasis is not on producing more content faster, but on learning how to guide, question, refine, and connect AI-generated material into coherent, usable analysis. You will apply techniques such as comparative prompting, iterative refinement, traceability, and ethical review across the full lifecycle of business analysis work.
By the end of the course, you will have a clear, experience-based understanding of where AI adds value, where it introduces risk, and how to maintain human oversight while benefiting from AI’s speed and flexibility. The course is designed for business analysts, product owners, and related roles who want to adopt generative AI in a grounded, professional way—improving productivity and insight without compromising rigor, responsibility, or trust.
Who should attend
- Business Analysts wanting to utilize AI to automate and assess analytical tasks and artefacts.
- Development team members wanting to accelerate content creation and insights whilst balancing responsible and ethical oversight.
- Anyone looking to be skilled in AI augmentation and innovation.
Prerequisites
To get the most out of this course, it is recommended that participants have foundational knowledge of business analysis through formal training like our Business Analysis Bootcamp course or have relevant experience working in a business analysis context.
Course Objectives
- Use generative AI to get started on analysis work even when information is incomplete.
- Write prompts that clearly describe your problem, context, constraints, and role as a business analyst.
- Review AI-generated analysis artifacts and identify errors, gaps, assumptions, and bias.
- Turn AI output into usable BA artifacts such as process models, data models, user stories, and backlogs.
- Keep requirements, stories, designs, and tests consistent and traceable with AI support.
- Use AI to prepare for stakeholder interviews and analyze interview results.
- Organize and prioritize analysis work using AI while retaining control over decisions.
- Recognize when AI is helping your analysis and when it is adding confusion or noise.
- Apply ethical and responsible practices when using AI, including attention to data sensitivity and bias.
- Create a practical plan for integrating generative AI into your own business analysis work.
Course Content
- Understanding AI’s Role in Business Analysis
- Using AI to Jumpstart a Project
- Modeling the Current State (Process View)
- Modeling the Current State (Data View)
- Getting to Know People
- Interviewing and Elicitation
- Writing User Stories
- Planning Development
- Designing the User Experience
- Writing Tests
- Validating, Prioritizing, and Coordinating
- Implementing AI‑Powered Business Analysis