Role-Based Programme
RB1309

AI for Logistics & Warehouse Operations

Smarter Inventory Flow, Fulfilment & Operational Efficiency

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Duration
8 Hours
Level
Basic
Delivery
Instructor-Led
Format
Workshop

Programme Objectives

  • Understand how AI can support Logistics and Warehouse Operations across receiving, storage, picking, fulfilment, dispatch, and delivery coordination.
  • Apply AI to analyse inventory movement, warehouse bottlenecks, order delays, capacity issues, and logistics exceptions.
  • Use AI to improve warehouse documentation, shift summaries, fulfilment analysis, exception handling, and operational reporting.
  • Develop practical skills for inventory-flow analysis, workload prioritisation, root-cause exploration, and process improvement.
  • Understand responsible AI use, safety, confidentiality, data quality, operational risk, and human oversight in logistics and warehouse environments.

Tools covered

Generative AI AssistantsInventory AnalysisWarehouse Workflow AnalysisOrder Fulfilment AnalysisLogistics Planning SupportCapacity & Space Utilisation AnalysisDelivery Exception AnalysisRoot-Cause Analysis SupportOperational ReportingContinuous Improvement Planning

Who should attend

  • Logistics Managers
  • Warehouse Managers
  • Warehouse Operations Executives
  • Logistics Operations Executives
  • Distribution Managers
  • Fulfilment Managers
  • Inventory Control Professionals
  • Warehouse Supervisors
  • Dispatch Managers
  • Transportation Coordinators
  • Supply Chain Analysts
  • Logistics Analysts
  • Operational Excellence Professionals
  • Operations Team Leads

Prerequisites & Participant Readiness

  • Basic understanding of logistics, warehousing, inventory, or distribution operations
  • Familiarity with receiving, storage, picking, dispatch, delivery, or inventory processes 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 logistics and warehouse operations
  • Exploring AI support across inventory flow, fulfilment, dispatch, issue analysis, and reporting
  • Distinguishing Generative AI from WMS, TMS, ERP, barcode, and warehouse automation systems
  • Understanding AI limitations, hallucinations, data-quality risks, and operational implications
Practical activities
  • Identifying recurring logistics and warehouse activities suitable for AI assistance
  • Comparing traditional and AI-assisted operational workflows
  • Mapping AI opportunities across the warehouse and logistics lifecycle

Scenarios

Warehouse Backlog to Fulfilment Recovery Plan

Order Backlog → Inventory Availability → Picking & Packing Capacity → Bottleneck Analysis → Priority Orders → Recovery Actions → Shift Allocation → Management Update

Participants use AI to analyse a sample warehouse backlog, identify fulfilment constraints, and develop a structured recovery plan with clear priorities and operational actions.

Recurring Delivery Delays to Logistics Improvement Plan

Shipment Data → Delay Patterns → Dispatch Review → Carrier / Process Issues → Root-Cause Hypotheses → Improvement Actions → Owners & Timelines → Leadership Summary

Participants use AI to analyse recurring logistics delays, identify potential warehouse and transportation causes, and prepare an evidence-based improvement plan for operations review.

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