Role-Based Programme
RB1242

AI for Service Delivery Management

SLA Excellence, Delivery Intelligence & Customer Experience

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

Programme Objectives

  • Develop practical AI capabilities for service delivery planning, SLA management, customer communication, issue resolution, and operational performance.
  • Apply AI to analyse service volumes, SLA trends, incidents, customer feedback, delivery risks, resource constraints, and recurring service issues.
  • Use AI to strengthen service reviews, escalation management, reporting, documentation, and cross-functional coordination.
  • Improve delivery performance through structured root-cause analysis, capacity insights, workflow optimisation, and continuous improvement.
  • Apply responsible AI practices related to customer information, confidentiality, operational decisions, source accuracy, access control, and human oversight.

Tools covered

Generative AI AssistantsAI Search & ResearchService Performance AnalysisSLA Monitoring SupportCustomer Feedback AnalysisIncident & Issue AnalysisService ReportingWorkflow AnalysisCapacity & Demand AnalysisKnowledge ManagementRisk AnalysisExecutive Summarisation

Who should attend

  • Service Delivery Managers
  • Senior Service Delivery Managers
  • Client Service Managers
  • Service Operations Managers
  • Service Managers
  • Customer Service Managers
  • Service Delivery Executives
  • Technical Service Managers
  • Customer Experience Managers
  • Support Managers
  • Operations Managers
  • Service Quality Professionals
  • Service Improvement Managers
  • Account Service Managers
  • Product / Service Management Leaders

Prerequisites & Participant Readiness

  • Experience in service delivery, service operations, customer support, client management, or service management
  • Familiarity with SLAs, incidents, service reviews, customer communication, and operational reporting
  • Basic familiarity with Generative AI tools is recommended
  • Ability to interpret service-performance and customer information
  • No programming knowledge required

TOC Modules

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

Scenarios

SLA Deterioration to Service Recovery Plan

Service Data → SLA Analysis → Incident Patterns → Root-Cause Hypotheses → Capacity Review → Corrective Actions → Customer Communication → Recovery Plan

Participants use AI to analyse a simulated deterioration in service performance, identify likely causes, prioritise corrective actions, and create a structured customer-facing recovery plan.

High-Risk Customer Escalation to Delivery Stabilisation

Customer Escalation → Impact Assessment → Service History → Issue Analysis → Stakeholder Coordination → Resolution Actions → Service Review → Stabilisation Roadmap

Participants use AI to structure a simulated high-risk service escalation, coordinate evidence and actions, and develop a stabilisation roadmap focused on service continuity, customer confidence, and performance improvement.

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