Program Overview
Supply chains today face unprecedented complexity – volatile demand, supplier disruptions, rising costs, and pressure for real-time decision-making. This program equips supply chain teams with the skills to harness AI for forecasting, procurement analytics, production scheduling, logistics optimization, and control-tower decision support. By combining predictive models, GenAI tools, and data-driven automation, participants learn how to convert raw operational data into insights, actions, and reliability improvements. Through hands-on exercises and real-world scenarios, the course helps teams identify inefficiencies, build AI-augmented workflows, and create a roadmap for scaling AI across planning, sourcing, manufacturing, and distribution.
Features
- Use AI tools to improve demand forecasting, inventory optimization, and planning accuracy
- Apply AI to procurement analytics, supplier evaluation, and risk prediction
- Leverage AI for optimizing logistics, distribution, and production schedules
- Build an actionable 90-day roadmap for scaling AI across the supply chain function
Target audiences
- Procurement & Logistics Professionals
- Supply Chain & Manufacturing Professionals
- Operations & Planning Professionals
- Digital Transformation Team
Curriculum
- 8 Sections
- 55 Lessons
- 1 Day
Expand all sectionsCollapse all sections
- Foundations of AI in Modern Supply ChainsUnderstand how AI transforms end-to-end supply chain ecosystems7
- 1.1Shift from traditional SCM → AI-enabled, autonomous supply chains
- 1.2Where AI fits: Demand, supply, procurement, logistics, manufacturing, qualit
- 1.3ML, GenAI, RPA, digital twins — what they solve in SCM
- 1.4AI readiness model for supply chain teams (Visibility → Prediction → Optimization → Autonomy)
- 1.5The role of SCM teams as the AI catalysts of business operations
- 1.6Exercise: Identify top manual tasks across the supply chain that AI can automate
- 1.7Quick Demo: AI summarizing supply planning data or supplier reports
- AI for Demand Forecasting & Inventory OptimizationImprove forecast accuracy and inventory decisions using AI-powered models7
- 2.1Demand sensing using ML (LSTM, ARIMA, regression, clustering)
- 2.2Real-time signals: POS, weather, competitor pricing, social trends
- 2.3AI-based inventory right-sizing & safety stock calculations
- 2.4Reduction of stockouts and overstock scenarios
- 2.5Constraint-based demand planning using AI
- 2.6Exercise: AI-assisted forecast generation using sample datasets
- 2.7Exercise: AI-generated inventory optimization suggestions
- AI in Procurement & Supplier ManagementStrengthen sourcing, risk visibility, and supplier collaboration with AI7
- 3.1AI-based supplier risk scoring (financial, delivery, ESG, geopolitical)
- 3.2Automated supplier evaluation summaries
- 3.3Smart negotiation prep — AI extracting key contract terms & risks
- 3.4AI for spend analytics, category insights & savings opportunities
- 3.5Predictive supplier performance & disruption alerts
- 3.6Exercise: Use AI to analyze a supplier dataset for risk
- 3.7Exercise: Generate a negotiation brief or category strategy using AI
- AI for Production Planning & SchedulingImprove throughput, reduce delays, and optimize resources7
- 4.1AI for capacity planning & bottleneck prediction
- 4.2Digital twins for production simulation
- 4.3Dynamic scheduling & re-scheduling using AI
- 4.4AI for quality prediction & defect detection
- 4.5Automated reporting for plant operations
- 4.6Exercise: AI-assisted capacity plan creation
- 4.7Exercise: Generate a production schedule using given constraints
- AI for Logistics, Transportation & DistributionEnable smarter routing, real-time visibility, and logistics optimization7
- 5.1AI-based route optimization & load planning
- 5.2Predictive transit delays (weather, traffic, customs, compliance)
- 5.3Freight cost prediction & optimization
- 5.4AI-driven warehouse automation, slotting & picking
- 5.5Control towers with AI-generated insights
- 5.6Exercise: Create an optimal route plan using AI
- 5.7AI-generated logistics risk analysis for a shipment
- AI for Reporting, Decision Support & Control TowersUse AI to improve decision-making clarity, speed, and accuracy6
- 6.1AI for dashboard creation & KPI interpretation
- 6.2Automated supply chain reporting (OTIF, fill rate, DIO, DPO, inventory turns)
- 6.3Decision intelligence: “What-if” scenarios & recommendations
- 6.4AI for meetings, minutes, escalation briefs, and executive updates
- 6.5Exercise: Generate a supply chain performance dashboard summary
- 6.6Exercise: AI-created simulation: “What if demand spikes by 20% next month?”
- GenAI for Documentation, SOPs & Cross-Functional CoordinationReduce administrative burden and make decision-making faster7
- 7.1Auto-generation of SOPs, RFQs, contracts, meeting notes
- 7.2AI for supply chain communication templates
- 7.3Summaries of supplier reviews, QA reports, customer complaints
- 7.4Automated emails for supply planning or dispatches
- 7.5AI-based root cause analysis for supply issues
- 7.6Exercise: Convert a manual SOP → AI-generated SOP
- 7.7Exercise: Create RCA & action plan using AI based on sample data
- Responsible AI, Data Governance & SCM Implementation RoadmapBuild secure, ethical, and scalable AI adoption pathways7
- 8.1Data quality, access control & supply chain data security
- 8.2AI governance & safe prompting for SCM teams
- 8.3Evaluating AI vendors, tools, and internal rollout strategies
- 8.4Creating an AI-enabled supply chain roadmap
- 8.5Capability-building pathways for teams
- 8.6Exercise: Define your function’s AI governance checklist
- 8.7Exercise: Build an AI rollout plan for your supply chain function
Instructor
