Role-Based Programme
RB1296

AI for Service Delivery Operations

Smarter Service Execution, SLA Performance & Operational Efficiency

IMAGE REQUIRED
Duration
4 Hours
Level
Awareness
Delivery
Instructor-Led
Format
Awareness Session

Programme Objectives

  • Understand how AI can support Service Delivery Operations across daily execution, performance monitoring, issue management, and service coordination.
  • Explore practical AI applications for analysing SLA performance, operational bottlenecks, recurring issues, and service-delivery risks.
  • Apply structured prompting techniques to create service summaries, operational reports, escalation notes, and improvement plans.
  • Use AI to improve productivity across service reviews, workflow coordination, documentation, action tracking, and stakeholder communication.
  • Recognise data quality, confidentiality, contractual sensitivity, automation risk, and human-review requirements when using AI in Service Delivery Operations.

Tools covered

Generative AI AssistantsService Operations AnalysisSLA & KPI MonitoringIncident & Issue AnalysisWorkflow OptimizationService ReportingRisk IdentificationAction TrackingAI-Powered Documentation & Productivity Tools

Who should attend

  • Service Delivery Operations Executives
  • Service Delivery Operations Managers
  • Operations Managers
  • Service Operations Managers
  • Service Delivery Managers
  • Operations Executives
  • Service Coordinators
  • Operations Analysts
  • Service Performance Analysts
  • Service Desk Operations Professionals
  • Customer Operations Professionals
  • Operational Excellence Professionals
  • Process Improvement Professionals
  • Service Quality Professionals
  • Service Delivery Operations Team Leads

Prerequisites & Participant Readiness

  • Basic understanding of service delivery or operational processes
  • Familiarity with SLAs, service KPIs, incidents, workflows, or operational reports is helpful
  • Basic analytical, communication, and coordination skills
  • No programming or technical AI knowledge required
  • No previous AI-tool experience required

TOC Modules

Concepts
  • Understanding Generative AI and its relevance to Service Delivery Operations
  • Exploring AI applications across service execution, SLA monitoring, issue analysis, reporting, and coordination
  • Understanding the difference between AI assistance, workflow automation, analytics, and operational judgement
  • Recognising AI limitations, hallucinations, incomplete service context, and unsupported recommendations
Practical activities
  • Identifying high-value AI applications across a typical service-delivery operations workflow
  • Comparing a traditional service-operations task with an AI-assisted approach

Scenarios

SLA Performance to Service Recovery Plan

Service KPIs → AI-Assisted Analysis → SLA Gaps → Operational Bottlenecks → Risks & Dependencies → Corrective Actions → Recovery Plan

Participants use AI to analyse sample service-delivery performance, identify SLA risks and operational gaps, and prepare a structured recovery plan for operations review.

Daily Operations Data to Management Summary

Operational Updates → Incidents & Backlog → AI-Assisted Consolidation → Key Risks → Actions & Owners → Improvement Priorities → Management Summary

Participants use AI to consolidate sample daily service information, highlight critical issues and dependencies, and create a concise management-ready operations summary.

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