AI for Business Analysts

• Automating analytical tasks using AI assistants
• Rapidly developing key project artifacts like charters, stories and models
• Using natural language generators to accelerate documentation and prototyping
• Training generative AI to simulate stakeholder interviews and surveys
• Strategies and techniques for managing the vast content created by AI
• Creating frameworks for validating and refining AI outputs for accuracy and providing effective feedback to progressively improve AI understanding
• Maintaining clear human oversight and control while leveraging AI capabilities and developing ethical and responsible adoption practices for AI in business analysis 

Content

Topics and exercises covered in the course include:

• Understanding AI’s Role in Business Analysis
• Using AI to Jumpstart a Project
  • Applying prompt engineering techniques to plan and refine a product
• Organizing AI-Created Content
  • Transforming AI outputs and transforming them into coherent, valuable resources
• Crafting User Stories with AI
• AI and Stakeholder Interviews
  • Training simulated interviews by taking on personas and responding to questions
• Potential Pitfalls and Social Risks
  • Detecting “hallucinations” and critically evaluating and validating AI results
• Requirements Analysis and Solution Design
  • Using AI to create many valuable BA artifacts such as process models and ERDs
• AI-Assisted UI Design
  • Transforming AI outputs into visual representations to produce UI prototypes
• Writing Tests with AI
  • Creating test scenarios and evaluating results to catch errors or gaps in coverage
• AI for Complete, Consistent, & Coherent Analysis
  • Strategies for responsible creation of AI created artifacts under human supervision
• Creative Applications of Generative AI
  • Using generative AI for writing, education and presentation design .
• Implementing AI-Driven Business Analysis
  • Responsibly leveraging AI's potential in business analysis under human supervision