Role-Based Programme
RB1285

AI for Customer Service Operations & Quality

Smarter Quality Monitoring, Process Improvement & Service Performance

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Duration
8 Hours
Level
Basic
Delivery
Instructor-Led
Format
Workshop

Programme Objectives

  • Understand how AI can support Customer Service Operations and Quality across monitoring, analysis, reporting, coaching, and process improvement.
  • Apply AI to analyse customer interactions, quality findings, service metrics, complaints, and recurring operational issues.
  • Use AI to improve quality reviews, performance summaries, SOPs, coaching insights, and corrective-action planning.
  • Develop practical skills for trend analysis, root-cause exploration, quality calibration, workflow improvement, and management reporting.
  • Understand responsible AI use, customer privacy, data accuracy, bias, governance, and human oversight in service-quality decisions.

Tools covered

Generative AI AssistantsCustomer Service AnalyticsQuality Monitoring SupportInteraction AnalysisSentiment AnalysisProcess AnalysisRoot-Cause Analysis SupportKnowledge ManagementPerformance ReportingContinuous Improvement Planning

Who should attend

  • Customer Service Operations Managers
  • Customer Service Quality Managers
  • Quality Assurance Analysts
  • Customer Service Quality Analysts
  • Customer Support Operations Professionals
  • Contact Centre Operations Managers
  • Contact Centre Quality Analysts
  • Customer Service Team Leaders
  • Customer Experience Professionals
  • Service Excellence Professionals
  • Process Improvement Professionals
  • Customer Support Managers
  • Training & Quality Professionals
  • Customer Service & Customer Success Team Leads

Prerequisites & Participant Readiness

  • Basic understanding of customer service, support operations, or quality processes
  • Familiarity with service metrics, quality reviews, customer interactions, or SOPs is helpful
  • Basic analytical, communication, and digital-tool skills
  • No programming or technical AI knowledge required
  • Prior AI-tool experience is helpful but not mandatory

TOC Modules

Concepts
  • Understanding Generative AI and its relevance to service operations and quality management
  • Exploring AI support across interaction review, performance analysis, coaching, documentation, and improvement
  • Distinguishing AI assistance from CRM, ticketing, workforce, quality-monitoring, and analytics platforms
  • Understanding AI limitations, hallucinations, bias, and quality-assessment risks
Practical activities
  • Identifying recurring operations and quality activities suitable for AI assistance
  • Comparing traditional and AI-assisted quality workflows
  • Mapping AI opportunities across the customer-service operating lifecycle

Scenarios

Quality Decline to Service Improvement Plan

Customer Interactions → Quality Review → Recurring Gaps → Performance Metrics → Root-Cause Hypotheses → Corrective Actions → Coaching Priorities → Management Review

Participants use AI to analyse sample customer interactions and service metrics, identify recurring quality issues, and develop a structured improvement and coaching plan.

Operational Data to Continuous Improvement Action Plan

Service Metrics → Workflow Analysis → Customer Feedback → Bottlenecks → Process Gaps → Priority Improvements → Owners & Timelines → Leadership Summary

Participants use AI to combine sample operational data, customer feedback, and process information to identify service inefficiencies and prepare a continuous-improvement plan for leadership review.

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