Role-Based Programme
RB1486

AI-Powered Application Support & Management

Smarter Incident Resolution, Application Monitoring & Service Reliability

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

Programme Objectives

  • Apply AI across Application Support and Management activities including incident handling, troubleshooting, monitoring, release support, knowledge management, and reporting.
  • Use AI-assisted techniques to analyse application errors, logs, user incidents, performance data, recurring issues, and support documentation more efficiently.
  • Develop structured workflows for application incident triage, problem investigation, escalation, change coordination, service recovery, and follow-up.
  • Improve application reliability through AI-assisted trend analysis, recurring-issue identification, knowledge capture, performance monitoring, and operational reporting.
  • Apply responsible AI practices covering production safety, credentials, sensitive application data, technical validation, access control, and human oversight.

Tools covered

Generative AI AssistantsApplication Monitoring AnalysisLog & Error AnalysisIncident Management SupportKnowledge ManagementRelease & Change SupportApplication Performance AnalyticsSpreadsheet AnalysisReporting AssistanceWorkflow Automation

Who should attend

  • Application Support Engineers
  • Application Support Analysts
  • Application Support Managers
  • Production Support Engineers
  • Application Operations Professionals
  • Technical Support Engineers
  • Application Administrators
  • Business Application Support Professionals
  • Enterprise Application Support Professionals
  • L2 / L3 Support Engineers
  • Application Reliability Professionals
  • IT Operations Analysts
  • Service Management Professionals
  • Information Technology Team Leads

Prerequisites & Participant Readiness

  • Working knowledge of application support, IT operations, software systems, or technical support
  • Familiarity with incidents, application logs, errors, ticketing systems, releases, or production support is helpful
  • Basic technical documentation and spreadsheet skills
  • Basic awareness of Generative AI is helpful
  • No advanced programming or AI knowledge required

TOC Modules

Concepts
  • Understanding Generative AI, analytics, document intelligence, and automation in Application Support
  • Identifying AI applications across incidents, troubleshooting, monitoring, releases, and reporting
  • Understanding AI assistance versus Application Support professional judgement and accountability
  • Recognising risks related to production systems, credentials, sensitive data, and unsafe recommendations
Practical activities
  • Mapping the Application Support lifecycle to AI-assisted activities
  • Identifying repetitive support and analysis tasks suitable for AI assistance
  • Comparing traditional and AI-assisted application-support workflows

Scenarios

Application Incident to Stable Resolution

User Incident → AI-Assisted Triage → Error & Log Review → Diagnostic Analysis → Escalation / Resolution → Validation → Knowledge Capture → Closure

Participants analyse a simulated application incident, structure the available evidence, develop a safe troubleshooting path, coordinate escalation where required, and capture the validated resolution for future reuse.

Application Support Data to Reliability Improvement Plan

Incident History + Performance Metrics + Release Data + Recurring Problems + SLA Results → AI Analysis → Service Weaknesses → Root Causes → Priority Improvements → Management Report

Participants consolidate Application Support information, identify recurring reliability and service issues, and prepare a management-ready improvement plan with actions, owners, and priorities.

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