Introduction

Generative AI can help Performance Quality Assurance teams produce clearer, faster, and more consistent QA reports—summarizing findings, drafting narratives, and preparing executive-ready packs. This practical program equips Grade 5 specialists with simple, safe workflows to use generative AI for QA reporting while maintaining accuracy, confidentiality, and strong human review.

Course Objectives

• Use generative AI to draft QA reports and summaries
• Standardize QA language, ratings, and recommendations
• Create executive-ready dashboards narratives and briefs
• Apply quality checks to prevent errors and hallucinations
• Follow safe-use rules for sensitive QA data

Target Audience

• Grade 5 Performance QA specialists
• KPI and reporting coordinators
• Performance management support teams
• Quality and controls staff supporting reports
• Teams preparing executive performance packs

Course Outline

Day 1: GenAI Basics for QA Reporting

• Where GenAI helps in QA
• What GenAI cannot do
• Prompting basics for reports
• Safe use and confidentiality
• Activity: Build a QA prompt set

Day 2: Writing QA Findings Clearly

• Finding structure: issue, impact, evidence
• Severity ratings and wording
• Root cause vs. symptom language
• Recommendation writing basics
• Workshop: Rewrite findings with AI

Day 3: Building QA Report Packs

• QA report templates and sections
• Summarizing multiple findings
• Executive summary drafting
• Action log and follow-up tables
• Activity: Create a full QA pack

Day 4: Quality Control and Verification

• Fact checking and evidence checks
• Preventing hallucinations
• Consistency checks across reports
• Version control and approvals
• Case study: Fixing AI report errors

Day 5: Governance and Adoption

• Review workflow and sign-offs
• Standard prompt library management
• Performance metrics for reporting
• 90-day adoption plan
• Final project: GenAI QA reporting playbook