Role-Based Programme
RB1238

AI for Service Management

Service Excellence, Customer Experience & Operational Intelligence

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

Programme Objectives

  • Develop practical AI capabilities for service planning, service delivery, customer experience, issue analysis, and operational improvement.
  • Apply AI to analyse service requests, incidents, customer feedback, SLA performance, recurring issues, and service-demand patterns.
  • Use AI to strengthen service documentation, knowledge management, root-cause analysis, communication, and continuous improvement.
  • Improve service-management decisions through structured performance analysis, prioritisation, workflow optimisation, and risk identification.
  • Apply responsible AI practices related to customer information, confidentiality, source accuracy, service decisions, automation governance, and human oversight.

Tools covered

Generative AI AssistantsAI Search & ResearchService Performance AnalysisCustomer Feedback AnalysisService Request AnalysisKnowledge ManagementProcess AnalysisSLA Monitoring SupportRoot-Cause AnalysisService ReportingWorkflow Automation ConceptsExecutive Summarisation

Who should attend

  • Service Managers
  • Service Delivery Managers
  • Service Operations Managers
  • Customer Service Managers
  • Service Owners
  • Service Management Professionals
  • Service Operations Analysts
  • Customer Experience Managers
  • Support Managers
  • Service Desk Managers
  • Service Improvement Managers
  • Product Service Managers
  • Business Operations Professionals
  • Service Quality Professionals
  • Product / Service Management Leaders

Prerequisites & Participant Readiness

  • Experience in service management, service delivery, customer support, operations, or customer experience
  • Familiarity with service requests, SLAs, operational processes, service reporting, or customer feedback
  • Basic familiarity with Generative AI tools is recommended
  • Ability to interpret service and operational information
  • No programming knowledge required

TOC Modules

Concepts
  • Understanding Generative AI, reasoning models, multimodal AI, and AI assistants
  • Exploring AI applications across service delivery, customer support, reporting, and improvement
  • Understanding how AI differs from service-management platforms, workflow systems, and analytics tools
  • Recognising hallucinations, incomplete analysis, unsupported recommendations, and AI limitations
Practical activities
  • Mapping the service-management lifecycle to practical AI applications
  • Identifying high-value versus low-value service use cases
  • Comparing traditional and AI-assisted service-management workflows

Scenarios

High Service Volume to Operational Improvement Plan

Service Requests → Demand Analysis → Issue Categorisation → SLA Review → Root-Cause Analysis → Workflow Gaps → Automation Opportunities → Improvement Plan

Participants use AI to analyse a simulated high-volume service environment, identify recurring causes and process inefficiencies, and develop a structured operational improvement plan.

Declining Customer Satisfaction to Service Recovery Strategy

Customer Feedback → Service Journey → Complaint Themes → SLA Performance → Root Causes → Communication Gaps → Corrective Actions → Service Recovery Plan

Participants use AI to investigate a simulated decline in customer satisfaction, connect customer feedback with service-performance data, and develop a structured service recovery and experience-improvement strategy.

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