Role-Based Programme
RB1239

AI for Service Management

Advanced Service Intelligence, Experience Optimisation & Operational Excellence

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Duration
32 Hours
Level
Advanced
Delivery
Instructor-Led
Format
Capability Development

Programme Objectives

  • Develop advanced capability to apply AI across service strategy, service design, delivery, support, performance management, and continual improvement.
  • Use AI-assisted analysis to understand service demand, customer expectations, service quality, operational issues, SLA performance, and improvement opportunities.
  • Apply AI to service requests, incident analysis, problem management, knowledge management, service communications, and operational workflows.
  • Use AI-assisted analytics to improve service reliability, responsiveness, customer experience, productivity, resource utilisation, and management visibility.
  • Build responsible AI-enabled Service Management workflows with appropriate governance, privacy, validation, escalation, and human oversight.

Tools covered

Generative AI AssistantsAI Search & ResearchService AnalyticsCustomer & User Feedback AnalysisService Catalogue IntelligenceSLA & Performance AnalysisIncident & Problem IntelligenceKnowledge ManagementDemand & Capacity AnalysisService Experience AnalyticsWorkflow AutomationAI AgentsPredictive Analytics ConceptsDecision-Support Tools

Who should attend

  • Service Managers
  • Senior Service Managers
  • Service Delivery Managers
  • Service Operations Managers
  • Customer Service Managers
  • Service Portfolio Managers
  • Service Owners
  • Service Management Analysts
  • Service Desk Managers
  • Service Excellence Professionals
  • Service Improvement Managers
  • Customer Experience Professionals
  • Operations Professionals Responsible for Service Delivery
  • Product Managers Responsible for Services
  • Leaders Responsible for Service Performance & Experience

Prerequisites & Participant Readiness

  • Experience in service management, service delivery, operations, customer service, product/service management, or service improvement
  • Familiarity with service processes, customer requests, SLAs, performance metrics, incidents, and service reviews
  • Basic awareness of Generative AI and common business applications
  • Comfort working with customer, operational, service, and performance information
  • No programming knowledge required

TOC Modules

Concepts
  • Understanding Generative AI, reasoning models, analytics, automation, and AI agents
  • Exploring AI applications across service planning, support, operations, knowledge, and improvement
  • Distinguishing AI-assisted Service Management from traditional workflow automation
  • Understanding hallucinations, operational risk, data quality, and human accountability
Practical activities
  • Mapping AI opportunities across the Service Management lifecycle
  • Identifying activities suitable for augmentation, automation, or continued human ownership
  • Creating an AI opportunity map for service-management teams

Scenarios

Recurring Service Failures to Service Improvement Plan

Incident Data → Pattern Analysis → Problem Identification → Root Cause → SLA Impact → Customer Experience → Corrective Actions → Improvement Metrics

Participants use AI to analyse recurring service disruptions, identify underlying causes, assess SLA and customer impact, and create a structured corrective and preventive improvement plan.

High Service Demand to AI-Enabled Service Operating Model

Service Demand → Request Analysis → Capacity → Workflow Bottlenecks → Knowledge Gaps → Automation Opportunities → SLA Design → Performance Dashboard

Participants use AI to analyse a high-volume service environment, identify operational inefficiencies, redesign fulfilment and support workflows, introduce controlled AI automation, and establish a scalable service-management operating model.

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