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.
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