Role-Based Programme
RB1311

AI for Logistics & Warehouse Operations

Advanced Distribution Intelligence, Warehouse Optimisation & Delivery Excellence

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

Programme Objectives

  • Develop advanced capability to apply AI across warehousing, transportation, distribution, order fulfilment, labour planning, and delivery operations.
  • Use AI-assisted analysis to identify warehouse bottlenecks, transport delays, inventory flow issues, capacity constraints, service failures, and cost drivers.
  • Apply AI to route planning, slotting analysis, fulfilment optimisation, workforce planning, carrier performance, exception handling, and operational reporting.
  • Use AI-assisted analytics to improve throughput, space utilisation, picking productivity, OTIF, delivery reliability, cost efficiency, and customer service.
  • Build responsible AI-enabled Logistics and Warehouse workflows with strong governance, safety, validation, data security, escalation, and human oversight.

Tools covered

Generative AI AssistantsAI Search & ResearchWarehouse AnalyticsTransportation AnalyticsRoute Optimisation ConceptsInventory Flow AnalysisOrder Fulfilment IntelligenceLabour Productivity AnalysisCarrier Performance AnalysisDemand & Capacity PlanningException ManagementRisk AnalysisWorkflow AutomationAI AgentsDecision-Support Tools

Who should attend

  • Logistics Managers
  • Warehouse Operations Managers
  • Distribution Centre Managers
  • Transportation Managers
  • Warehouse Supervisors
  • Logistics Analysts
  • Warehouse Analysts
  • Order Fulfilment Managers
  • Dispatch & Distribution Professionals
  • Inventory Operations Professionals
  • Transport Planning Professionals
  • Carrier Management Professionals
  • Operational Excellence Professionals
  • Supply Chain Operations Professionals
  • Leaders Responsible for Logistics & Warehouse Performance

Prerequisites & Participant Readiness

  • Experience in logistics, warehousing, transportation, distribution, fulfilment, or supply chain operations
  • Familiarity with warehouse processes, transport operations, inventory movement, delivery metrics, and service-level requirements
  • Basic awareness of Generative AI and common business applications
  • Comfort working with operational, logistics, inventory, and performance data
  • No programming knowledge required

TOC Modules

Concepts
  • Understanding Generative AI, reasoning models, analytics, automation, and AI agents
  • Exploring AI applications across warehousing, transportation, fulfilment, planning, and exception management
  • Distinguishing AI-assisted logistics decisions from autonomous operational control
  • Understanding hallucinations, operational risk, safety implications, and human accountability
Practical activities
  • Mapping AI opportunities across warehouse and logistics workflows
  • Identifying activities suitable for augmentation, automation, or continued human ownership
  • Creating an AI opportunity map for Logistics and Warehouse teams

Scenarios

Warehouse Congestion & Low Productivity to Optimised Fulfilment Model

Inbound Volume → Space Utilisation → Slotting → Picking Travel → Labour Capacity → Dispatch Delays → Workflow Redesign → Productivity KPIs

Participants use AI to diagnose warehouse congestion and low productivity, identify layout and workflow issues, improve slotting and labour deployment, and create a measurable fulfilment improvement plan.

High Freight Cost & Delivery Delays to Logistics Optimisation Plan

Shipment Data → Route Patterns → Carrier Performance → Load Utilisation → Delivery Exceptions → Cost Analysis → Routing Options → Service Metrics

Participants use AI to analyse high transport costs and unreliable delivery performance, identify carrier and routing inefficiencies, compare alternative operating scenarios, and create a balanced cost-and-service optimisation plan.

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