Role-Based Programme
RB1597

AI-Powered Customer Quality & Complaint Management

Smarter Complaint Analysis, Root Cause & Service Quality Improvement

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Duration
8 Hours
Level
Basic
Delivery
Instructor-Led
Format
Workshop

Programme Objectives

  • Understand how AI can support Customer Quality and Complaint Management across complaint intake, classification, investigation, root-cause analysis, and closure.
  • Apply AI-assisted techniques to analyse customer complaints, feedback, quality incidents, service issues, and supporting data.
  • Use structured prompting for complaint summarisation, issue categorisation, investigation planning, response drafting, and corrective-action support.
  • Explore AI-supported approaches for identifying recurring complaint themes, defect patterns, customer-impact areas, and improvement opportunities.
  • Build responsible AI-assisted complaint-management workflows while maintaining accuracy, fairness, traceability, customer confidentiality, and human oversight.

Tools covered

Generative AI AssistantsAI Search & ResearchDocument AISpreadsheet & Data AnalysisComplaint Analysis AIRoot Cause Analysis AICAPA SupportSentiment & Feedback AnalysisWorkflow Automation

Who should attend

  • Customer Quality Executives
  • Customer Quality Managers
  • Complaint Management Professionals
  • Quality Assurance Professionals
  • Quality Executives
  • Customer Experience Professionals
  • Customer Service Quality Professionals
  • CAPA Coordinators
  • Quality Analysts
  • Process Excellence Professionals
  • Continuous Improvement Professionals
  • Service Quality Professionals
  • Process Owners
  • Customer Quality & Complaint Management Team Leads

Prerequisites & Participant Readiness

  • Basic understanding of Quality Management, customer complaints, or service-quality processes
  • Familiarity with complaint records, customer feedback, defects, investigations, or corrective actions is helpful
  • Basic computer, spreadsheet, and document-handling skills
  • No AI or programming knowledge required
  • No previous AI training required

TOC Modules

Concepts
  • Understanding Generative AI and its relevance to customer quality and complaint handling
  • Identifying AI applications across complaint intake, classification, analysis, response, and reporting
  • Understanding AI assistance versus quality, customer-service, and management judgement
  • Recognising limitations such as inaccurate interpretation, bias, incomplete context, and unsupported conclusions
Practical activities
  • Mapping a typical Customer Complaint Management workflow
  • Identifying repetitive and information-intensive complaint activities suitable for AI assistance
  • Comparing a traditional complaint-analysis task with an AI-assisted approach

Scenarios

Customer Complaint to Root Cause & Resolution

Customer Complaint → AI-Assisted Classification → Evidence Review → Investigation → Root Cause → Corrective Action → Customer Response → Closure

Participants use AI to structure a sample customer complaint, organise evidence, develop root-cause questions, and prepare a supported resolution workflow.

Complaint Data to Quality Improvement Plan

Complaint Data + Customer Feedback + Defect Records → AI Analysis → Recurring Themes → High-Impact Issues → CAPA Priorities → Management Report

Participants use AI to analyse sample complaint and customer-quality data, identify recurring issues and improvement opportunities, and prepare a management-ready Customer Quality Improvement Plan.

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