Role-Based Programme
RB1599

AI-Powered Customer Quality & Complaint Management

Intelligent Complaint Analytics, Root-Cause Resolution & Customer Quality Improvement

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Duration
32 Hours
Level
Advanced
Delivery
Instructor-Led
Format
Capability Development

Programme Objectives

  • Develop advanced capability to apply AI across customer complaints, quality feedback, case investigation, root-cause analysis, corrective action, and service recovery.
  • Use AI to analyse complaint records, customer communication, defect information, returns, quality incidents, service data, and corrective-action history.
  • Build repeatable AI-assisted workflows for complaint intake, classification, prioritisation, investigation, escalation, CAPA tracking, and closure.
  • Apply AI to identify recurring quality issues, customer-impact patterns, complaint trends, systemic causes, and improvement opportunities.
  • Design responsible AI-enabled Customer Quality & Complaint Management workflows with appropriate controls for fairness, privacy, accuracy, evidence integrity, traceability, and human oversight.

Tools covered

Generative AI AssistantsAI Search & ResearchDocument AISpreadsheet & Data AnalysisComplaint AnalyticsSentiment & Feedback AnalysisRoot Cause Analysis ToolsQuality AnalyticsReporting & Dashboard ToolsWorkflow Automation

Who should attend

  • Customer Quality Managers
  • Complaint Management Professionals
  • Quality Managers
  • Quality Assurance Professionals
  • Customer Quality Engineers
  • Quality Engineers
  • Customer Experience Quality Professionals
  • Customer Service Quality Managers
  • CAPA Coordinators
  • Continuous Improvement Professionals
  • Root Cause Analysis Professionals
  • Quality Analysts
  • Operations Quality Professionals
  • Product Quality Professionals
  • Customer Quality & Complaint Management Team Leads

Prerequisites & Participant Readiness

  • Working knowledge of Quality Management, customer complaints, Customer Service, Quality Assurance, or process improvement
  • Familiarity with complaint records, defects, returns, CAPA, customer feedback, service issues, or quality investigations
  • Basic proficiency with spreadsheets, documents, data interpretation, and workplace productivity applications
  • No previous AI course attendance required
  • No programming background required

TOC Modules

Concepts
  • Understanding Generative AI, analytical AI, Document AI, and complaint intelligence
  • Mapping AI opportunities across complaint intake, investigation, corrective action, and reporting
  • Understanding AI assistance versus qualified quality and customer-management judgement
  • Recognising privacy, bias, hallucination, and evidence-quality risks
Practical activities
  • Mapping an existing complaint-management lifecycle and identifying AI opportunities
  • Comparing manual and AI-assisted complaint-management activities
  • Creating a Customer Quality AI opportunity matrix

Scenarios

Customer Complaint to CAPA Closure

Customer Complaint → AI Intake → Classification → Evidence Review → Root Cause Analysis → Corrective Action → Customer Response → Effectiveness Verification → Closure

Participants use AI-assisted techniques to manage a simulated complaint from intake through investigation, root-cause validation, corrective action, customer communication, and final closure.

Complaint Portfolio to Continuous Quality Improvement

Complaint Data + Returns + Defects + Customer Feedback + CAPA History → AI Analysis → Recurring Themes → Priority Issues → Preventive Actions → Automated Tracking → Dashboard → Quality Review

Participants design an AI-enabled Customer Quality workflow that consolidates complaint and quality signals, identifies systemic issues, strengthens corrective and preventive action, and improves management visibility.

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