Role-Based Programme
RB1313

AI for Inventory Management

Smarter Stock Planning, Replenishment & Inventory Optimisation

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Duration
8 Hours
Level
Basic
Delivery
Instructor-Led
Format
Workshop

Programme Objectives

  • Understand how AI can support Inventory Management across stock analysis, replenishment, availability, exception management, and reporting.
  • Apply AI to analyse stock levels, consumption patterns, lead times, demand variability, shortages, and excess inventory.
  • Use AI to improve inventory classification, replenishment reviews, exception handling, stock reports, and management communication.
  • Develop practical skills for stock-risk identification, slow-moving inventory analysis, root-cause exploration, and inventory optimisation.
  • Understand responsible AI use, data accuracy, supplier and commercial confidentiality, governance, and human oversight in inventory decisions.

Tools covered

Generative AI AssistantsInventory Data AnalysisDemand Pattern AnalysisReplenishment SupportStock ClassificationInventory Risk AnalysisSlow-Moving & Excess Stock AnalysisRoot-Cause Analysis SupportInventory ReportingContinuous Improvement Planning

Who should attend

  • Inventory Managers
  • Inventory Executives
  • Inventory Analysts
  • Inventory Control Professionals
  • Stock Control Managers
  • Warehouse Inventory Professionals
  • Materials Management Professionals
  • Supply Chain Professionals
  • Demand Planning Professionals
  • Supply Planning Professionals
  • Procurement Operations Professionals
  • Warehouse Managers
  • Operations Analysts
  • Operations Team Leads

Prerequisites & Participant Readiness

  • Basic understanding of inventory, warehousing, supply chain, or operations
  • Familiarity with stock levels, replenishment, purchase orders, lead times, or inventory reports is helpful
  • Basic spreadsheet, analytical, 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 inventory operations
  • Exploring AI support across stock analysis, replenishment, exception handling, and reporting
  • Distinguishing Generative AI from ERP, WMS, inventory-planning, and forecasting systems
  • Understanding AI limitations, hallucinations, data-quality risks, and inventory implications
Practical activities
  • Identifying recurring Inventory Management activities suitable for AI assistance
  • Comparing traditional and AI-assisted inventory workflows
  • Mapping AI opportunities across the inventory-management lifecycle

Scenarios

Inventory Shortage to Replenishment Action Plan

Demand Data → Current Stock → Incoming Supply → Lead Time → Shortage Risk → Priority Items → Replenishment Actions → Management Update

Participants use AI to analyse a sample inventory-shortage situation, identify high-risk items, and prepare a structured replenishment and prioritisation plan.

Excess & Slow-Moving Stock to Inventory Optimisation Plan

Inventory Ageing → Usage Patterns → Excess Stock → Root-Cause Hypotheses → Item Prioritisation → Corrective Actions → Monitoring Plan → Leadership Summary

Participants use AI to analyse sample ageing and slow-moving inventory, identify potential causes, and develop an evidence-based inventory optimisation plan for operations review.

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