Role-Based Programme
RB1719

AI-Powered Asset Management

Intelligent Asset Tracking, Lifecycle Optimisation & Maintenance Analytics

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Duration
32 Hours
Level
Advanced
Delivery
Instructor-Led
Format
Capability Development

Programme Objectives

  • Develop advanced capability to apply AI across the complete physical-asset lifecycle from acquisition and registration through utilisation, maintenance, transfer, audit, and disposal.
  • Use AI to analyse asset registers, invoices, warranties, maintenance histories, service records, utilisation data, and asset documentation.
  • Build repeatable AI-assisted workflows for asset tagging, classification, reconciliation, preventive maintenance, verification, exception handling, and reporting.
  • Apply AI to identify asset-performance patterns, utilisation gaps, recurring failures, lifecycle risks, and optimisation opportunities.
  • Design responsible AI-enabled Asset Management workflows with appropriate controls for accuracy, financial information, security, auditability, approvals, and human oversight.

Tools covered

Generative AI AssistantsDocument AIOCR & Data ExtractionSpreadsheet & Data AnalysisAsset Register AnalyticsMaintenance IntelligenceVisual AIReporting & Dashboard ToolsWorkflow Automation

Who should attend

  • Asset Managers
  • Asset Management Executives
  • Facilities Managers
  • Administration Managers
  • Asset Coordinators
  • Facilities Executives
  • Fixed Asset Professionals
  • Workplace Operations Professionals
  • Corporate Services Professionals
  • Site Administration Professionals
  • Inventory & Asset Control Professionals
  • Maintenance Coordinators
  • Property & Facility Operations Professionals
  • Asset Verification Professionals
  • Administration & Facilities Team Leads

Prerequisites & Participant Readiness

  • Working knowledge of asset, facilities, administration, inventory, or maintenance activities
  • Familiarity with asset registers, equipment records, invoices, warranties, maintenance information, or physical verification
  • Basic proficiency with spreadsheets, documents, email, and workplace productivity applications
  • No previous AI course attendance required
  • No programming background required

TOC Modules

Concepts
  • Understanding Generative AI, analytical AI, document intelligence, and workflow automation
  • Understanding the asset lifecycle from acquisition to retirement or disposal
  • Identifying AI opportunities across asset records, maintenance, utilisation, reconciliation, and reporting
  • Understanding AI assistance versus authorised financial, technical, and asset-management decisions
Practical activities
  • Mapping an existing Asset Management process and identifying AI opportunities
  • Comparing manual and AI-assisted asset-management activities
  • Creating an Asset Management AI opportunity matrix based on value, effort, and risk

Scenarios

Asset Register to Lifecycle Optimisation Plan

Asset Register → Data Cleansing → Physical Verification → Maintenance History → Utilisation Analysis → Cost & Warranty Review → Optimisation Recommendation

Participants use AI-assisted analysis to improve a sample asset register, identify discrepancies, examine maintenance and utilisation patterns, and prepare a lifecycle optimisation plan for management review.

Asset Acquisition to Retirement Workflow

Asset Acquisition → Document Extraction → Registration → Tagging → Custodian Assignment → Maintenance → Transfer → Audit → Retirement / Disposal

Participants design an end-to-end AI-assisted asset lifecycle workflow that improves traceability, documentation, maintenance visibility, verification, and governance while retaining authorised human approval for financial and disposal decisions.

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