Role-Based Programme
RB1315

AI for Inventory Management

Advanced Stock Intelligence, Demand Planning & Inventory Optimisation

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

Programme Objectives

  • Develop advanced capability to apply AI across inventory planning, replenishment, stock control, availability, ageing, working capital, and exception management.
  • Use AI-assisted analysis to identify stockouts, excess inventory, slow-moving stock, demand variability, lead-time risks, and inventory imbalances.
  • Apply AI to inventory classification, reorder planning, safety stock analysis, demand interpretation, supplier coordination, and stock rationalisation.
  • Use AI-assisted analytics to improve availability, service levels, inventory turns, working capital, stock accuracy, and operational responsiveness.
  • Build responsible AI-enabled Inventory Management workflows with strong governance, data quality, validation, control, and human oversight.

Tools covered

Generative AI AssistantsAI Search & ResearchInventory AnalyticsDemand Forecasting ConceptsReplenishment AnalysisSafety Stock AnalysisABC/XYZ ClassificationInventory SegmentationStock Ageing AnalysisInventory Risk AnalysisWorking Capital AnalyticsSupplier Lead-Time AnalysisWorkflow AutomationAI AgentsDecision-Support Tools

Who should attend

  • Inventory Managers
  • Inventory Control Managers
  • Inventory Planners
  • Materials Managers
  • Stock Control Professionals
  • Supply Chain Analysts
  • Demand Planning Professionals
  • Supply Planning Professionals
  • Warehouse Inventory Professionals
  • Materials Planning Professionals
  • Operations Analysts
  • Procurement Operations Professionals
  • Distribution Planning Professionals
  • Inventory Excellence Professionals
  • Leaders Responsible for Inventory Performance

Prerequisites & Participant Readiness

  • Experience in inventory, materials, supply chain, warehousing, planning, procurement operations, or distribution
  • Familiarity with stock levels, replenishment, lead times, safety stock, service levels, and inventory KPIs
  • Basic awareness of Generative AI and common business applications
  • Comfort working with inventory, demand, supplier, and operational data
  • No programming knowledge required

TOC Modules

Concepts
  • Understanding Generative AI, reasoning models, analytics, automation, and AI agents
  • Exploring AI applications across stock planning, replenishment, inventory control, and exception management
  • Distinguishing AI-assisted inventory decisions from fully autonomous stock control
  • Understanding hallucinations, poor data quality, forecast uncertainty, and human accountability
Practical activities
  • Mapping AI opportunities across the Inventory Management lifecycle
  • Identifying activities suitable for augmentation, automation, or continued human ownership
  • Creating an AI opportunity map for Inventory Management teams

Scenarios

Simultaneous Stockouts & Excess Inventory to Inventory Recovery Plan

Demand Patterns → Inventory Position → Reorder Logic → Safety Stock → Lead-Time Variability → Excess & Shortages → Rebalancing Actions → KPI Tracking

Participants use AI to analyse an inventory portfolio experiencing both stockouts and excess stock, identify planning and replenishment causes, and create a balanced availability and working-capital improvement plan.

High Inventory Investment to AI-Enabled Inventory Optimisation Model

SKU Segmentation → Demand Variability → Inventory Ageing → Service Levels → Supplier Lead Times → Working Capital → Optimisation Scenarios → Executive Dashboard

Participants use AI to identify where inventory investment is excessive or poorly allocated, develop segment-specific stocking policies, compare optimisation scenarios, and build a controlled inventory-management model.

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