AI for Business Analysts – Foundation

A practical, hands-on programme for applying AI in business analysis, from core concepts through to requirements, workflows, and governance

Overview

Artificial Intelligence is reshaping how organisations analyse problems, define requirements, and deliver change.

For Business Analysts, this is already changing the day-to-day role. Activities such as documentation, stakeholder analysis, requirements definition, and workflow design are being accelerated and augmented by AI.

This two-day course provides a structured, practical introduction to using AI within business analysis.

Participants will learn how to apply tools such as ChatGPT, Claude, Perplexity, and Gemini to real business analysis scenarios, while developing a clear understanding of how AI systems behave, how AI requirements should be defined, where AI fits within business workflows, and how to apply governance and oversight.

The focus is on practical application, not theory.

What You Will Learn

• Explain how AI is transforming business analysis and operations
• Use large language models effectively to support BA activities
• Apply prompt engineering techniques to improve output quality
• Define AI-specific requirements across multiple categories
• Integrate AI into business workflows and processes
• Apply human oversight and control mechanisms
• Identify risks, governance considerations, and ethical implications

How You Will Apply It

Throughout the course, participants will work on practical, real-world scenarios, including:

• Using AI to draft and refine business requirements
• Analysing stakeholder input using AI-assisted summarisation
• Designing AI-enabled workflows with human oversight
• Defining requirements for an AI voice assistant solution
• Evaluating risks, edge cases, and failure scenarios

Who Should Attend

• Business Analysts at all levels
• Senior Business Analysts and Lead BAs
• Product Owners and Product Managers
• Change and Transformation professionals
• Anyone involved in requirements, process design, or business change

Course Content

Day 1 – AI Foundations and the Business Analyst Role

Focus: Understanding AI, tools, and practical application in BA tasks

AI and the Modern Business Analyst

• The growing role of AI in business processes
• Practical BA use cases:
• Drafting documentation
• Summarising stakeholder feedback
• Supporting analysis activities
• The evolving BA role:
• Less manual effort
• More focus on insight, decision-making, and stakeholder engagement

Key AI Concepts

• Artificial Intelligence
• Machine Learning
• Large Language Models (LLMs)
• Natural Language Processing
• Computer Vision
• Voice AI

AI Tools for Business Analysts

• Practical use of tools including:
• ChatGPT
• Claude
• Perplexity
• Gemini
• Supporting tools:
• n8n (workflow automation)
• Vapi (Voice AI)
• ElevenLabs

The AI Development Lifecycle

• Define the problem
• Data discovery
• Model selection
• Prototyping
• Integration
• Deployment and scaling

Prompt Engineering Fundamentals

• Why prompt quality directly impacts output quality
• Techniques:
• Role Prompting
• Structured Prompts
• Few-Shot Prompting
• Chain-of-Thought Prompting

Practical Exercise – AI for BA Tasks

• Apply AI to a real business analysis task
• Refine prompts and compare outputs
• Identify opportunities and risks

Day 1 Summary

• AI enhances, not replaces, the BA role
• Outputs must be validated and reviewed
• Structured prompting improves reliability

Day 2 – AI Requirements, Workflows and Governance

Focus: Applying BA thinking to AI systems and ensuring responsible adoption

AI Requirements vs Traditional Requirements

• Deterministic vs probabilistic behaviour
• Variability in outputs
• Performance thresholds and tolerances
• Dependence on data quality

Categories of AI Requirements

• Functional Requirements
• Data Requirements
• Performance Requirements
• Explainability Requirements
• Edge Case Handling
• Ethics and Policy Requirements

Scenario – AI Voice Assistant

Designing an AI solution that:
• Books appointments
• Reschedules appointments
• Cancels appointments

With focus on:
• User experience and interaction
• Handling ambiguity and failure
• Tone and communication
• Trust and transparency

Eliciting AI Requirements

• Stakeholder interviews
• User stories
• Scenario mapping
• Prototyping approaches

Practical Exercise – Defining AI Requirements

• Define functional and non-functional requirements
• Identify data and performance needs
• Explore edge cases and risks
• Present and review outputs

AI-Powered Workflows

• Where AI fits within end-to-end business processes
• Decision points and human intervention
• Exception handling and escalation paths

Introduction to Voice AI and Computer Vision

• Voice AI
• Customer interaction
• Automation of conversations
• Computer Vision
• Image recognition
• Document processing

AI Governance and Responsible Adoption

• Data privacy and security
• Bias and fairness
• Transparency and explainability
• Accountability and ownership
• Human oversight and monitoring

Key questions explored:
• Could this AI produce harmful or biased outputs?
• What happens if it is wrong?
• Who is accountable?
• How will it be monitored?
• Do users know they are interacting with AI?

Course Summary

By the end of this programme, participants will understand how to:

• Apply AI within real business analysis scenarios
• Define robust AI requirements
• Design AI-enabled workflows with control and oversight
• Balance innovation with governance and risk management

Optional Next Step

For organisations looking to go further, this course can be followed by:

• Advanced AI for Business Analysis – Practitioner Level
• AI-Enabled Process Design and Automation Workshops
• Private team sessions tailored to your organisation’s workflows and tools