Role-Based Programme
RB1596

AI-Powered Customer Quality & Complaint Management

Smarter Complaint Analysis, Root-Cause Support & Customer Quality Improvement

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Duration
4 Hours
Level
Awareness
Delivery
Instructor-Led
Format
Awareness Session

Programme Objectives

  • Understand how AI can support Customer Quality and Complaint Management across complaint intake, categorisation, analysis, root-cause review, corrective action, and reporting.
  • Explore practical prompting techniques for complaint summaries, customer-impact analysis, issue classification, root-cause support, and response drafting.
  • Apply AI to organise customer-quality information, identify recurring complaint themes, and prepare structured quality outputs.
  • Identify opportunities to improve complaint-response speed, consistency, trend visibility, documentation quality, and customer-quality improvement.
  • Recognise customer confidentiality, evidence accuracy, regulatory requirements, quality procedures, and human-review responsibilities when using AI.

Tools covered

Generative AI AssistantsAI-Assisted Complaint AnalysisVoice of Customer AnalysisDocument IntelligenceRoot-Cause Analysis SupportComplaint CategorisationCAPA TrackingQuality Reporting

Who should attend

  • Customer Quality Professionals
  • Customer Quality Engineers
  • Quality Managers
  • Quality Executives
  • Quality Assurance Professionals
  • Complaint Management Professionals
  • Customer Complaint Analysts
  • Quality Control Professionals
  • CAPA Coordinators
  • Customer Experience Quality Professionals
  • Process Quality Professionals
  • Continuous Improvement Professionals
  • Quality Management Team Leads

Prerequisites & Participant Readiness

  • Basic understanding of quality, customer complaints, or corrective-action processes
  • Familiarity with complaint records, defects, customer feedback, RCA, or CAPA is helpful
  • Basic computer and spreadsheet skills
  • No AI or programming knowledge required
  • No previous Generative AI experience required

TOC Modules

Concepts
  • Understanding Generative AI and its relevance to customer-quality management
  • Identifying AI applications across complaint intake, categorisation, analysis, documentation, and reporting
  • Understanding AI assistance versus Quality and Customer Service professional judgement
  • Recognising activities where customer evidence, approved procedures, and human validation remain mandatory
Practical activities
  • Mapping common Customer Quality and Complaint Management activities to potential AI applications
  • Comparing a traditional complaint-handling task with an AI-assisted approach

Scenarios

Customer Complaint to Root Cause & CAPA

Customer Complaint → AI-Assisted Classification → Severity & Impact → Evidence Review → Potential Root Cause → Corrective Action → CAPA Summary

Participants use AI to organise a sample customer complaint, identify relevant quality information, explore potential causes, and prepare a structured corrective-action summary for professional review.

Complaint Data to Customer Quality Improvement

Complaint Records → AI Analysis → Recurring Themes → High-Impact Issues → Trends → Improvement Priorities → Management Summary

Participants use AI to analyse sample complaint records, identify recurring quality concerns, and prepare a concise management-ready summary highlighting trends, priorities, and improvement actions.

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