Role-Based Programme
RB1598

AI-Powered Customer Quality & Complaint Management

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

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Duration
16 Hours
Level
Intermediate
Delivery
Instructor-Led
Format
Capability Training

Programme Objectives

  • Apply AI across Customer Quality and Complaint Management activities including complaint intake, classification, investigation, root-cause analysis, CAPA, response, and closure.
  • Use AI-assisted techniques to analyse complaint records, customer feedback, defect information, service issues, and recurring quality patterns more efficiently.
  • Develop structured workflows for complaint prioritisation, investigation, escalation, corrective action, customer communication, and effectiveness verification.
  • Analyse customer-quality data to identify recurring issues, high-impact defect themes, process weaknesses, and improvement opportunities.
  • Apply responsible AI practices covering customer-data confidentiality, evidence quality, factual accuracy, communication controls, traceability, and human oversight.

Tools covered

Generative AI AssistantsComplaint AnalyticsDocument IntelligenceVoice of Customer AnalysisRoot-Cause Analysis SupportSpreadsheet AnalysisCAPA TrackingQuality Trend AnalysisCustomer Communication SupportReporting AssistanceWorkflow Automation

Who should attend

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

Prerequisites & Participant Readiness

  • Working knowledge of quality, customer service, complaint handling, or process-improvement activities
  • Familiarity with complaints, defects, deviations, CAPA, customer feedback, or quality records is helpful
  • Basic spreadsheet and data-analysis skills
  • Basic awareness of Generative AI is helpful
  • No programming knowledge required

TOC Modules

Concepts
  • Understanding Generative AI, analytics, document intelligence, and automation in complaint management
  • Identifying AI applications across complaint intake, investigation, RCA, CAPA, communication, and reporting
  • Understanding AI assistance versus Quality professional judgement and customer-response accountability
  • Recognising risks related to inaccurate classification, unsupported conclusions, and sensitive customer information
Practical activities
  • Mapping the complaint-management lifecycle to AI-assisted activities
  • Identifying repetitive complaint and quality tasks suitable for AI support
  • Comparing traditional and AI-assisted complaint-management workflows

Scenarios

Customer Complaint to Verified Resolution

Customer Complaint → AI-Assisted Classification → Evidence Review → Root-Cause Analysis → CAPA → Customer Response → Effectiveness Verification → Closure

Participants analyse a simulated customer complaint, investigate the issue, validate the root cause, create corrective actions, and prepare a clear customer-facing resolution while maintaining traceability and review controls.

Complaint Data to Customer Quality Improvement Plan

Complaint Records + Customer Feedback + Defect Data + CAPA Status → AI Analysis → Recurring Themes → Priority Risks → Improvement Actions → Management Report

Participants consolidate customer-quality information, identify recurring complaint patterns and process weaknesses, and prepare a management-ready improvement plan with actions, owners, and priorities.

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