Role-Based Programme
RB1307

AI for Supply Chain Operations

Advanced Demand Intelligence, Inventory Optimisation & Supply Chain Resilience

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

Programme Objectives

  • Develop advanced capability to apply AI across demand planning, supply planning, inventory, logistics, warehousing, order fulfilment, and supplier coordination.
  • Use AI-assisted analysis to identify demand variability, inventory imbalances, supply constraints, delivery risks, bottlenecks, and cost drivers.
  • Apply AI to planning, exception management, supplier performance, logistics optimisation, operational reporting, and disruption response.
  • Use AI-assisted analytics to improve forecast quality, inventory availability, fulfilment performance, service levels, working capital, and supply chain resilience.
  • Build responsible AI-enabled Supply Chain Operations workflows with strong governance, validation, data security, escalation controls, and human oversight.

Tools covered

Generative AI AssistantsAI Search & ResearchDemand Forecasting ConceptsInventory AnalyticsSupply PlanningSupplier IntelligenceLogistics AnalyticsWarehouse IntelligenceOrder Fulfilment AnalysisNetwork Planning ConceptsRisk & Disruption AnalysisKPI DashboardsWorkflow AutomationAI AgentsDecision-Support Tools

Who should attend

  • Supply Chain Operations Managers
  • Supply Chain Managers
  • Demand Planning Professionals
  • Supply Planning Professionals
  • Inventory Managers
  • Logistics Managers
  • Warehouse Operations Managers
  • Order Fulfilment Managers
  • Supply Chain Analysts
  • Distribution Operations Professionals
  • Procurement & Supplier Operations Professionals
  • Supply Chain Excellence Professionals
  • Planning & Operations Analysts
  • Supply Chain Transformation Professionals
  • Leaders Responsible for Supply Chain Performance

Prerequisites & Participant Readiness

  • Experience in supply chain, logistics, inventory, planning, warehousing, procurement operations, or distribution
  • Familiarity with demand, supply, inventory, suppliers, fulfilment, logistics, and supply chain KPIs
  • Basic awareness of Generative AI and common business applications
  • Comfort working with operational, planning, supplier, and logistics data
  • No programming knowledge required

TOC Modules

Concepts
  • Understanding Generative AI, reasoning models, analytics, automation, and AI agents
  • Exploring AI applications across planning, inventory, suppliers, logistics, warehousing, and fulfilment
  • Distinguishing AI-assisted supply chain decisions from autonomous operational control
  • Understanding hallucinations, data-quality risks, operational uncertainty, and human accountability
Practical activities
  • Mapping AI opportunities across the end-to-end supply chain
  • Identifying activities suitable for augmentation, automation, or continued human ownership
  • Creating an AI opportunity map for Supply Chain Operations teams

Scenarios

Inventory Imbalance & Service Failures to Supply Chain Recovery Plan

Demand Data → Forecast Variance → Inventory Position → Supply Constraints → Supplier Risk → Fulfilment Gaps → Rebalancing Actions → Service Metrics

Participants use AI to diagnose simultaneous stockouts and excess inventory, identify forecasting and supply constraints, prioritise corrective actions, and create a measurable service and inventory recovery plan.

Major Supply Disruption to Resilient Supply Chain Response

Disruption Signal → Supplier Dependency → Inventory Exposure → Customer Impact → Alternate Supply Options → Logistics Scenarios → Recovery Plan → Executive Dashboard

Participants use AI to assess a major supply disruption, identify the most exposed products and customers, compare sourcing and logistics alternatives, and build a controlled resilience and recovery plan.

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