Training on AI for Supply Chain and Logistics
Apply AI to enhance supply chain efficiency and visibility. AI for demand forecasting, route optimization, inventory, and risk management.
Next intake
20 Jul 2026 · Nakuru
Duration
10 days
Live instruction
Delivery
Physical + Virtual
Cohort based
Level
Intermediate
Working professionals
Certification
NITA reimbursable
For Kenyan cohorts
Language
English
All materials
About this programme
This course equips supply chain and logistics professionals with AI skills to enhance efficiency, visibility, and decision-making across the supply chain. Participants will learn to apply AI for demand forecasting, route optimization, inventory management, and supply chain risk management.
Who Should Attend:
- Supply chain and logistics managers
- Operations and distribution directors
- Procurement and sourcing teams
- Inventory and warehouse management staff
- Transportation and fleet managers
What you'll walk away with
- To equip supply chain professionals with AI skills
- To enable AI-driven supply chain optimization
- To provide tools for improving logistics performance
- To build capability for AI-enhanced supply chain management
What we cover, module by module
Module 1: Introduction to AI in Supply Chain and Logistics
- Understanding AI's role in supply chain
- AI applications across supply chain functions
- Key AI tools and platforms for supply chain
- Ethical and practical considerations
- Building an AI strategy for supply chain
- Case Study: Analyzing AI applications in supply chain
Module 2: AI for Demand Forecasting and Planning
- AI-powered demand forecasting
- Predictive analytics for demand patterns
- Integrating demand with supply planning
- Scenario analysis and planning
- Measuring forecast accuracy
- Case Study: Building a demand forecast model with AI
Module 3: AI for Inventory Optimization
- AI for inventory optimization and stocking
- Predictive inventory management
- Safety stock and reorder point optimization
- Automated replenishment with AI
- Reducing inventory costs and waste
- Case Study: Optimizing inventory with AI
Module 4: AI for Logistics and Route Optimization
- AI for route optimization and planning
- Real-time tracking and visibility
- Predictive maintenance for logistics
- Autonomous logistics and delivery
- Measuring logistics performance
- Case Study: Optimizing logistics routes with AI
Module 5: AI for Supply Chain Risk Management
- AI for risk identification and prediction
- Supply chain disruption prediction
- Supplier risk assessment and monitoring
- Resilient supply chain design
- Building a risk management framework with AI
- Case Study: Implementing supply chain risk management with AI
Module 6: AI for Procurement and Supplier Management
- AI for supplier selection and evaluation
- Predictive analytics for supplier performance
- Procurement optimization with AI
- Contract management and compliance
- Supplier relationship management with AI
- Case Study: Implementing AI in procurement
Module 7: AI for Warehouse and Operations Optimization
- AI for warehouse layout and slotting optimization
- Predictive analytics for warehouse operations
- Automation and robotics in warehouses
- Inventory visibility and tracking with AI
- Optimizing warehouse workforce with AI
- Case Study: Optimizing warehouse operations with AI
Module 8: AI for Reverse Logistics and Returns Management
- AI for returns prediction and management
- Reverse logistics optimization
- Predictive analytics for product returns
- Returns processing automation with AI
- Reducing returns costs with AI
- Case Study: Implementing AI in reverse logistics
Module 9: AI for Supply Chain Sustainability
- AI for supply chain emissions monitoring
- Sustainable sourcing and procurement
- Circular economy and waste reduction
- Carbon footprint optimization with AI
- Reporting and compliance with sustainability standards
- Case Study: Building a sustainable supply chain with AI
Module 10: Advanced Topics in AI for Supply Chain
- Digital twins for supply chain simulation
- AI-powered supply chain visibility platforms
- Blockchain and AI integration in supply chain
- AI for demand sensing and real-time adjustments
- Future trends in AI for supply chain
- Case Study: Designing an advanced AI-powered supply chain
Where the change lands
Organizational Impacts:
- Enhanced supply chain efficiency and visibility
- Optimized logistics and transportation
- Improved inventory management and demand planning
- Reduced supply chain risks and costs
Individual Impacts:
- Ability to apply AI to supply chain functions
- Skills in AI-powered forecasting and optimization
- Knowledge of AI for inventory and logistics
- Expertise in data-driven supply chain decisions
Dates and locations
Upcoming intakes
Every intake is limited to a small cohort. Booking closes when a date fills or three weeks before the start, whichever comes first.
| City | Starts | Ends | Delivery | Book |
|---|---|---|---|---|
NakuruNext | 20 Jul 2026 | 31 Jul 2026 | In-Person | Book |
Kigali | 20 Jul 2026 | 31 Jul 2026 | In-Person | Book |
Accra | 20 Jul 2026 | 31 Jul 2026 | In-Person | Book |
Kisumu | 27 Jul 2026 | 07 Aug 2026 | In-Person | Book |
Johannesburg | 27 Jul 2026 | 07 Aug 2026 | In-Person | Book |
Dakar | 27 Jul 2026 | 07 Aug 2026 | In-Person | Book |
- NakuruNext
20 Jul → 31 Jul·In-Person
Book this intake - Kigali
20 Jul → 31 Jul·In-Person
Book this intake - Accra
20 Jul → 31 Jul·In-Person
Book this intake - Kisumu
27 Jul → 07 Aug·In-Person
Book this intake - Johannesburg
27 Jul → 07 Aug·In-Person
Book this intake - Dakar
27 Jul → 07 Aug·In-Person
Book this intake
Common questions.
Still not sure? Send us a note and a facilitator will get back to you within a business day.
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Course finder
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For corporate teams
Training 10+ professionals?
We deliver Training on AI for Supply Chain and Logistics in-house at your offices, at a venue we arrange, or fully virtual. Customise the curriculum against your KPIs, and get a bespoke price for the cohort size you need.