Role-Based Programme
RB1310

AI for Logistics & Warehouse Operations

Inventory Flow, Fulfilment Intelligence & Operational Efficiency

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Duration
16 Hours
Level
Intermediate
Delivery
Instructor-Led
Format
Capability Training

Programme Objectives

  • Develop practical AI capabilities for warehouse operations, inventory movement, order fulfilment, logistics coordination, and operational decision support.
  • Apply AI to analyse inventory flow, picking and packing performance, dispatch operations, transportation delays, warehouse capacity, and service-level issues.
  • Use AI to improve exception handling, root-cause analysis, workload planning, SOP creation, shift handovers, and operational reporting.
  • Strengthen logistics and warehouse performance through data-driven prioritisation, process optimisation, capacity planning, and continuous improvement.
  • Apply responsible AI practices related to inventory data, operational confidentiality, accuracy, safety, access control, and human oversight.

Tools covered

Generative AI AssistantsAI Search & ResearchWarehouse Data AnalysisInventory Flow AnalysisOrder Fulfilment AnalysisLogistics Performance AnalysisCapacity & Space AnalysisRoot-Cause AnalysisException ManagementSOP & Knowledge ManagementOperational ReportingExecutive Summarisation

Who should attend

  • Warehouse Managers
  • Warehouse Operations Executives
  • Logistics Managers
  • Logistics Executives
  • Distribution Centre Managers
  • Warehouse Supervisors
  • Inventory Control Professionals
  • Dispatch & Distribution Professionals
  • Order Fulfilment Professionals
  • Transportation Coordinators
  • Logistics Analysts
  • Warehouse Analysts
  • Operations Managers
  • Operational Excellence Professionals
  • Logistics & Warehouse Operations Leaders

Prerequisites & Participant Readiness

  • Experience in logistics, warehousing, distribution, inventory control, fulfilment, or operations
  • Familiarity with warehouse processes, inventory movement, dispatch, logistics KPIs, and operational reporting
  • Basic familiarity with Generative AI tools is recommended
  • Ability to interpret warehouse and logistics information
  • No programming knowledge required

TOC Modules

Concepts
  • Understanding Generative AI, reasoning models, multimodal AI, and AI assistants
  • Exploring AI applications across warehousing, inventory, fulfilment, dispatch, and transportation
  • Understanding how AI differs from WMS, TMS, ERP, barcode, and warehouse automation systems
  • Recognising hallucinations, incomplete recommendations, and operational risks
Practical activities
  • Mapping logistics and warehouse activities to practical AI use cases
  • Identifying high-value versus high-risk applications
  • Comparing traditional and AI-assisted operational workflows

Scenarios

Warehouse Congestion to Fulfilment Improvement Plan

Order Volume → Warehouse Flow → Capacity Analysis → Picking Delays → Bottleneck Identification → Resource Review → Process Actions → Fulfilment Improvement Plan

Participants use AI to analyse a simulated warehouse experiencing congestion and slow fulfilment, identify capacity and workflow constraints, and develop a structured improvement plan.

Delivery Delays & Inventory Errors to Logistics Recovery Strategy

Inventory Accuracy → Dispatch Data → Carrier Performance → Delivery Exceptions → Root-Cause Analysis → Corrective Actions → SOP Updates → Recovery Roadmap

Participants use AI to investigate a simulated combination of inventory errors and delivery delays, identify recurring operational causes, and develop a coordinated logistics and warehouse recovery roadmap.

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