Role-Based Programme
RB1297

AI for Service Delivery Operations

Smarter Workflows, SLA Performance & Operational Excellence

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Duration
8 Hours
Level
Basic
Delivery
Instructor-Led
Format
Workshop

Programme Objectives

  • Understand how AI can support Service Delivery Operations across workflow management, SLA tracking, issue handling, reporting, and continuous improvement.
  • Apply AI to analyse service data, operational bottlenecks, recurring issues, workload patterns, and performance gaps.
  • Use AI to improve service documentation, incident summaries, action tracking, operational reports, and management communication.
  • Develop practical skills for SLA analysis, root-cause exploration, process optimisation, capacity planning, and service-performance improvement.
  • Understand responsible AI use, confidentiality, data quality, governance, bias, and human oversight in operational decisions.

Tools covered

Generative AI AssistantsService Performance AnalysisSLA Monitoring SupportWorkflow AnalysisIncident & Issue AnalysisOperational ReportingRoot-Cause Analysis SupportCapacity & Workload AnalysisProcess DocumentationContinuous Improvement Planning

Who should attend

  • Service Delivery Operations Managers
  • Service Operations Managers
  • Operations Managers
  • Service Delivery Executives
  • Service Operations Executives
  • Operations Analysts
  • Service Performance Analysts
  • SLA Management Professionals
  • Incident Coordination Professionals
  • Service Excellence Professionals
  • Process Improvement Professionals
  • Operational Excellence Professionals
  • Business Operations Professionals
  • Operations Team Leads

Prerequisites & Participant Readiness

  • Basic understanding of service delivery, operations, or business processes
  • Familiarity with SLAs, service metrics, incidents, workflows, or operational reporting is helpful
  • Basic analytical, communication, and digital-tool skills
  • No programming or technical AI knowledge required
  • Prior AI-tool experience is helpful but not mandatory

TOC Modules

Concepts
  • Understanding Generative AI and its relevance to service operations
  • Exploring AI support across service monitoring, workflow analysis, issue management, and reporting
  • Distinguishing AI assistance from service-management, workflow, monitoring, and analytics platforms
  • Understanding AI limitations, hallucinations, bias, and operational risks
Practical activities
  • Identifying recurring Service Delivery Operations activities suitable for AI assistance
  • Comparing traditional and AI-assisted service workflows
  • Mapping AI opportunities across the service-delivery lifecycle

Scenarios

SLA Breach to Operational Recovery Plan

Service Data → SLA Breach → Workflow Analysis → Customer Impact → Root-Cause Hypotheses → Recovery Actions → Ownership & Timelines → Management Update

Participants use AI to analyse a sample SLA breach, identify operational gaps and possible causes, and develop a structured recovery plan with clear ownership and follow-up actions.

Service Workload to Continuous Improvement Plan

Workload Data → Capacity Review → Bottlenecks → Process Gaps → Priority Issues → Improvement Opportunities → Action Plan → Leadership Summary

Participants use AI to analyse sample workload and service-performance data, identify operational inefficiencies, and prepare a practical continuous-improvement plan for leadership review.

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