Role-Based Programme
RB1243

AI for Service Delivery Management

Advanced Service Performance, SLA Intelligence & Delivery Excellence

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

Programme Objectives

  • Develop advanced capability to apply AI across service delivery planning, SLA management, operational reviews, customer communication, escalations, and continual improvement.
  • Use AI-assisted analysis to identify service-performance gaps, recurring incidents, customer-impact patterns, capacity constraints, and delivery risks.
  • Apply AI to improve service reporting, issue resolution, stakeholder communication, resource planning, supplier coordination, and service governance.
  • Use AI-assisted analytics to strengthen SLA achievement, service reliability, customer satisfaction, operational productivity, and management visibility.
  • Build responsible AI-enabled Service Delivery Management workflows with strong governance, validation, escalation controls, privacy, and human oversight.

Tools covered

Generative AI AssistantsAI Search & ResearchService Performance AnalyticsSLA IntelligenceIncident & Escalation AnalysisCustomer Experience AnalysisCapacity & Resource PlanningService Review IntelligenceKnowledge ManagementRisk AnalysisVendor Performance AnalysisWorkflow AutomationAI AgentsDecision-Support Tools

Who should attend

  • Service Delivery Managers
  • Senior Service Delivery Managers
  • Service Operations Managers
  • Service Managers
  • Customer Service Delivery Managers
  • Client Service Managers
  • Service Account Managers
  • Service Delivery Leads
  • Service Performance Managers
  • Service Improvement Managers
  • Operations Managers
  • Service Governance Professionals
  • Vendor & Supplier Management Professionals
  • Customer Experience Leaders
  • Leaders Responsible for Service Delivery Performance

Prerequisites & Participant Readiness

  • Experience in service delivery, service operations, customer service, service management, or operational management
  • Familiarity with SLAs, service reviews, incident management, customer communication, and performance reporting
  • 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 delivery, monitoring, reporting, escalation, and improvement
  • Distinguishing AI-assisted service management from traditional workflow automation
  • Understanding hallucinations, operational risk, weak data, and human accountability
Practical activities
  • Mapping AI opportunities across the Service Delivery lifecycle
  • Identifying activities suitable for augmentation, automation, or continued human ownership
  • Creating an AI opportunity map for Service Delivery teams

Scenarios

Repeated SLA Failures to Service Recovery Plan

SLA Data → Incident Patterns → Root Causes → Capacity & Process Gaps → Customer Impact → Corrective Actions → Governance → Recovery Metrics

Participants use AI to diagnose repeated SLA failures, identify operational and capacity causes, assess customer impact, and create a measurable service-recovery programme.

Complex Multi-Vendor Service to AI-Enabled Delivery Model

Service Scope → Vendor Dependencies → SLA Performance → Incident Trends → Customer Experience → Risk → Automation Opportunities → Governance → Operating Model

Participants use AI to analyse a complex multi-vendor service environment, identify delivery and governance gaps, improve supplier accountability, introduce controlled AI-enabled workflows, and design a scalable Service Delivery operating model.

Continue with programmes from the same capability area.

Take the next step

Ready to make this programme work for your team?

Customise modules, duration and business scenarios for your team.

Instructor-ledVirtualHybrid

Designed around your roles, tools and real workflows.