Role-Based Programme
RB1298

AI for Service Delivery Operations

SLA Performance, Workflow Intelligence & Operational Excellence

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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, monitoring, coordination, issue management, and performance improvement.
  • Apply AI to analyse SLAs, service metrics, incidents, workloads, dependencies, customer commitments, and operational risks.
  • Use AI to improve service reviews, documentation, root-cause analysis, escalation preparation, action tracking, and management reporting.
  • Strengthen service delivery performance through workflow optimisation, capacity analysis, preventive actions, and continuous improvement.
  • Apply responsible AI practices related to operational data, customer information, service commitments, confidentiality, accuracy, and human oversight.

Tools covered

Generative AI AssistantsAI Search & ResearchService Performance AnalysisSLA AnalysisWorkflow MappingIncident & Issue AnalysisRoot-Cause AnalysisCapacity & Demand AnalysisKnowledge ManagementRisk AnalysisOperational ReportingExecutive Summarisation

Who should attend

  • Service Delivery Managers
  • Service Delivery Executives
  • Service Operations Managers
  • Service Operations Analysts
  • Delivery Operations Professionals
  • Operations Managers
  • Service Coordinators
  • Service Management Professionals
  • Client Service Managers
  • Operations Analysts
  • Shared Services Professionals
  • Service Desk Managers
  • Operational Excellence Professionals
  • Service Delivery Team Leaders
  • Operations Heads

Prerequisites & Participant Readiness

  • Experience in service delivery, service operations, customer operations, shared services, or operational management
  • Familiarity with SLAs, service KPIs, incidents, escalations, workflows, and operational reporting
  • Basic familiarity with Generative AI tools is recommended
  • Ability to interpret service and operational information
  • No programming knowledge required

TOC Modules

Concepts
  • Understanding Generative AI, reasoning models, multimodal AI, and AI assistants
  • Exploring AI applications across service monitoring, issue management, reporting, and improvement
  • Understanding how AI differs from service-management, workflow, monitoring, and analytics systems
  • Recognising hallucinations, incomplete recommendations, and operational risks
Practical activities
  • Mapping the service delivery lifecycle to practical AI applications
  • Identifying high-value versus high-risk AI use cases
  • Comparing traditional and AI-assisted service delivery workflows

Scenarios

SLA Breach to Service Recovery Plan

Service Metrics → SLA Breach → Incident Review → Root-Cause Analysis → Dependency Check → Corrective Actions → Customer Communication → Recovery Plan

Participants use AI to analyse a simulated SLA breach, identify contributing factors, structure corrective actions, and prepare a customer-ready service recovery plan.

Growing Service Demand to Operational Capacity Strategy

Demand Trends → Workload Analysis → Capacity Review → Bottleneck Identification → Risk Assessment → Resource Options → Improvement Actions → Service Delivery Roadmap

Participants use AI to analyse increasing service demand, identify capacity and workflow constraints, and develop a structured service-delivery roadmap focused on sustainable performance and customer commitments.

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