Role-Based Programme
RB1284

AI for Customer Service Operations & Quality

Smarter Performance Monitoring, Quality Analysis & Service Improvement

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

Programme Objectives

  • Understand how AI can support Customer Service Operations and Quality across performance monitoring, interaction reviews, reporting, and service improvement.
  • Explore practical AI applications for analysing customer interactions, operational KPIs, recurring service issues, and quality gaps.
  • Apply structured prompting techniques to create quality summaries, coaching observations, operational reports, and improvement recommendations.
  • Use AI to improve productivity across quality audits, performance reviews, service reporting, process analysis, and management communication.
  • Recognise customer privacy, data quality, bias, confidentiality, compliance, and human-review requirements when using AI in Customer Service Operations.

Tools covered

Generative AI AssistantsCustomer Service AnalyticsQuality MonitoringInteraction ReviewSLA & KPI AnalysisCustomer Feedback AnalysisProcess ImprovementCoaching SupportAI-Powered Reporting & Productivity Tools

Who should attend

  • Customer Service Operations Managers
  • Customer Service Operations Executives
  • Customer Support Operations Professionals
  • Customer Service Quality Managers
  • Quality Analysts
  • Quality Assurance Executives
  • Contact Centre Quality Professionals
  • Customer Service Managers
  • Customer Support Managers
  • Service Performance Analysts
  • Customer Experience Analysts
  • Workforce & Operations Professionals
  • Process Improvement Professionals
  • Customer Service Supervisors
  • Customer Service Operations & Quality Team Leads

Prerequisites & Participant Readiness

  • Basic understanding of customer-service or support operations
  • Familiarity with service KPIs, quality reviews, customer interactions, or operational reports is helpful
  • Basic analytical, communication, and process-improvement skills
  • No programming or technical AI knowledge required
  • No previous AI-tool experience required

TOC Modules

Concepts
  • Understanding Generative AI and its relevance to customer-service operations and quality
  • Exploring AI applications across performance monitoring, quality reviews, reporting, and process improvement
  • Understanding the difference between AI assistance, analytics, automation, and operational judgement
  • Recognising AI limitations, hallucinations, incorrect classifications, and unsupported conclusions
Practical activities
  • Identifying high-value AI applications across a typical customer-service operations workflow
  • Comparing a traditional quality-review activity with an AI-assisted approach

Scenarios

Customer Interactions to Quality Improvement Plan

Customer Interactions → AI-Assisted Quality Review → Quality Gaps → Recurring Themes → Coaching Needs → Process Improvements → Action Plan

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

Service KPIs to Operations Performance Review

Customer Service KPIs → AI-Assisted Analysis → Performance Gaps → Operational Bottlenecks → Quality Signals → Priority Actions → Management Summary

Participants use AI to review sample service-performance data, identify operational and quality gaps, and create a concise management action plan.

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