Role-Based Programme
RB1236

AI for Service Management

Smarter Service Delivery, Issue Resolution & Performance Improvement

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

Programme Objectives

  • Understand how AI can support Service Management across service delivery, request handling, issue analysis, knowledge management, and performance reporting.
  • Explore practical AI applications for analysing service requests, customer feedback, recurring issues, service trends, and operational bottlenecks.
  • Apply structured prompting techniques to create service summaries, response drafts, knowledge articles, root-cause questions, and improvement recommendations.
  • Use AI to improve productivity across service reviews, documentation, stakeholder communication, reporting, and continuous improvement.
  • Recognise customer privacy, confidentiality, data quality, automation risk, and human-review requirements when using AI in Service Management.

Tools covered

Generative AI AssistantsService Request AnalysisCustomer Feedback AnalysisIncident & Issue SummarizationKnowledge ManagementService Performance AnalysisSLA ReportingProcess ImprovementAI-Powered Documentation & Communication Tools

Who should attend

  • Service Managers
  • Service Delivery Managers
  • Service Management Executives
  • Customer Service Managers
  • Service Operations Professionals
  • Service Desk Managers
  • Service Coordinators
  • Service Analysts
  • Customer Experience Professionals
  • Support Operations Managers
  • Service Quality Professionals
  • Service Improvement Managers
  • Product Support Professionals
  • Service Portfolio Professionals
  • Service Management Team Leads

Prerequisites & Participant Readiness

  • Basic understanding of service delivery, customer support, or operational processes
  • Familiarity with service requests, incidents, customer feedback, SLAs, or performance reports is helpful
  • Basic analytical and communication skills
  • No programming or technical AI knowledge required
  • No previous AI-tool experience required

TOC Modules

Concepts
  • Understanding Generative AI and its relevance to Service Management
  • Exploring AI applications across requests, incidents, service communication, knowledge, and reporting
  • Understanding the difference between AI assistance, service automation, analytics, and service-manager judgement
  • Recognising AI limitations, hallucinations, incomplete service context, and incorrect recommendations
Practical activities
  • Identifying high-value AI applications across a typical service-management workflow
  • Comparing a traditional service-management activity with an AI-assisted approach

Scenarios

Service Issue to Resolution & Knowledge Article

Service Request → AI-Assisted Issue Summary → Clarification Questions → Resolution Inputs → Customer Response → Knowledge Article

Participants use AI to analyse a sample service issue, structure the relevant facts, prepare follow-up questions, draft a customer response, and convert the resolution into reusable service knowledge.

Service Performance to Improvement Plan

Service Metrics → AI-Assisted Analysis → SLA Gaps → Recurring Issues → Possible Drivers → Improvement Actions → Management Summary

Participants use AI to review sample service-performance data, identify operational gaps and recurring issues, and create a structured improvement plan for service-management review.

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