COURSE OUTLINE

Day 1: The AI-Augmented BA & Discovery

Focus: Enhancing the initial phases of the project lifecycle.

• Generative AI in the BA Lifecycle: Identifying where AI adds value (Automation vs. Reasoning).
• Elicitation & Stakeholder Analysis:
• Using Gemini to categorize stakeholders and build RACI matrices.
• Drafting interview scripts and workshop agendas.
• Problem Framing & Discovery:
• Summarizing stakeholder "pain points" into a clear Problem Statement.
• Generating a preliminary Business Analysis Canvas.
• Hands-on Lab: Use Gemini to analyze a raw transcript from a stakeholder interview and extract a structured list of business needs and constraints.

Day 2: Modeling, User Stories & Solution Design

Focus: Turning raw data into structured BA artifacts.

• Process & Data Modeling:
• Using AI to draft BPMN 2.0 process flows and identify "Happy Paths" vs. "Exception Paths."
• Generating entity-relationship diagrams (ERD) and data definitions.
• Writing High-Quality User Stories:
• The INVEST principle in the age of AI.
• Generating Acceptance Criteria (AC) and Gherkin-style test scenarios.
• Prototyping & UX Logic:
• Using AI to describe functional narratives and screen-flow logic.
• Linking UI elements to specific business requirements.
• Hands-on Lab: Refine a vague business objective into 5-10 detailed User Stories with full Acceptance Criteria and a corresponding process map.

Day 3: Data Analytics, Ethics, and Governance

Focus: Smarter decision-making and responsible oversight.

• AI-Powered Data Analysis:
• Using Gemini to query spreadsheets and databases for trends and anomalies.
• Generating "Data Narratives"—turning raw metrics into executive summaries.
• Validation & Quality Control:
• Using AI to check for ambiguity and completeness in requirement documents.
• Building a Traceability Matrix with AI assistance.
• Ethics & Risk Management:
• Detecting bias in AI-generated personas and requirements.
• Understanding the EU AI Act and NIST Framework from a BA perspective.
• The Future BA Roadmap: Strategic change management and preparing the organization for AI adoption.
• Final Capstone: Participants present a "Project Initiation Document" for an AI-driven solution, including requirements, risks, and a governance plan.