Role-Based Programme
RB1312

AI for Inventory Management

Smarter Stock Planning, Inventory Optimization & Operational Control

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

Programme Objectives

  • Understand how AI can support Inventory Management across stock monitoring, replenishment, exception analysis, and inventory reporting.
  • Explore practical AI applications for identifying shortages, excess stock, slow-moving inventory, demand patterns, and operational risks.
  • Apply structured prompting techniques to create inventory summaries, replenishment reviews, exception reports, and action recommendations.
  • Use AI to improve productivity across stock reviews, inventory planning, coordination, documentation, and management reporting.
  • Recognise data quality, commercial sensitivity, operational risk, and human-validation requirements when using AI in Inventory Management.

Tools covered

Generative AI AssistantsInventory Data AnalysisStock Level AnalysisReplenishment Planning SupportDemand Pattern AnalysisSlow & Non-Moving Inventory AnalysisException ManagementInventory ReportingAI-Powered Documentation & Productivity Tools

Who should attend

  • Inventory Managers
  • Inventory Executives
  • Inventory Controllers
  • Inventory Analysts
  • Stock Controllers
  • Warehouse Inventory Professionals
  • Materials Management Professionals
  • Supply Chain Executives
  • Supply Chain Analysts
  • Demand Planning Professionals
  • Supply Planning Professionals
  • Replenishment Planners
  • Stores & Materials Professionals
  • Operations Analysts
  • Inventory Management Team Leads

Prerequisites & Participant Readiness

  • Basic understanding of inventory, warehousing, or supply-chain processes
  • Familiarity with stock levels, replenishment, inventory reports, or material movement is helpful
  • Basic analytical and numerical skills
  • No programming or technical AI knowledge required
  • No previous AI-tool experience required

TOC Modules

Concepts
  • Understanding Generative AI and its relevance to Inventory Management
  • Exploring AI applications across stock monitoring, replenishment, exception analysis, and reporting
  • Understanding the difference between AI assistance, inventory systems, forecasting tools, and operational judgement
  • Recognising AI limitations, hallucinations, inaccurate calculations, and unsupported inventory recommendations
Practical activities
  • Identifying high-value AI applications across a typical inventory-management workflow
  • Comparing a traditional stock-review task with an AI-assisted approach

Scenarios

Inventory Position to Replenishment Plan

Stock Levels + Demand → AI-Assisted Analysis → Shortage / Excess Risk → Lead-Time Review → Priority Items → Replenishment Actions → Inventory Summary

Participants use AI to analyse sample inventory and demand information, identify high-risk stock positions, and prepare a structured replenishment plan for operational review.

Inventory Ageing to Stock Optimization Plan

Inventory Ageing → AI-Assisted Analysis → Slow / Non-Moving Items → Business Impact → Possible Causes → Corrective Actions → Management Summary

Participants use AI to review sample inventory-ageing data, identify slow-moving and excess stock, and prepare a concise stock-optimization action plan.

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