Cambridge
Academy
In London

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 Outlines

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