Duration: 2 Days Instructor-led

Overview 

The future of business analysis lies at the intersection of human creativity and technological leverage. Our AI for Business Analysis course is an immersive and interactive journey to prepare experienced BA professionals for the AI-empowered future. Through real-world exercises with leading AI agents and tools, gain first-hand experience planning initiatives, analyzing requirements, and devising solutions. You will learn “prompt engineering” methods for using generative AI agents to produce key BA artifacts, research new subject matters, evaluate work, and conduct interviews with subject matter experts. While balancing AI’s power to create content with human judgment, you will discover AI dialogue techniques that enable iterative and incremental analysis and development. 

In This Class You’ll Learn 

• Automate analytical tasks using AI assistants 

• Rapidly developing key project artifacts like charters, stories, and models 

• Use natural language generators to accelerate documentation and prototyping 

• Train generative AI to simulate stakeholder 

• Strategize and techniques for managing the vast content created by AI 

• Create frameworks for validating and refining AI outputs for accuracy 

• Provide effective feedback to improve AI understanding progressively 

• Maintain clear human oversight and control while leveraging AI capabilities 

• Develop ethical and responsible adoption practices for AI in business analysis 

Course Outline 

Part 1: Understanding AI’s Role in Business Analysis 

Part 2: Using AI to Jumpstart a Project 

• Applying prompt engineering techniques to plan and refine a product 

Part 3: Organizing AI-Created Content 

• Transforming AI outputs and transforming them into coherent, valuable resources 

Part 4: Crafting User Stories with AI 

Part 5: AI and Stakeholder Interviews 

• Training simulated interviews by taking on 

• personas and responding to questions 

Part 6: Potential Pitfalls and Social Risks 

• Detecting “hallucinations” and critically evaluating and validating AI results 

Part 7: Requirements Analysis and Solution Design 

• Using AI to create many valuable BA artifacts such as process models and ERDs 

Part 8: AI-Assisted UI Design 

• Transforming AI outputs into visual representations to produce UI prototypes 

Part 9: Writing Tests with AI 

• Creating test scenarios and evaluating results to catch errors or gaps in coverage 

Part 10: AI for Complete, Consistent, & Coherent Analysis 

• Strategies for responsible creation of AI-created artifacts under human supervision 

Part 11: Creative Applications of Generative AI 

• Using generative AI for writing, education, and presentation design. 

Part 12: Implementing AI-Driven Business Analysis 

• Responsibly leveraging AI’s potential business analysis under human supervision