GenAI for Supply Chain Optimization
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GenAI for Supply Chain Optimization
Instructors: Mustafa Bayulgen
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What you'll learn
Identify Generative AI and its key applications within supply chain management, its impact on operational efficiency and decision-making processes.
Evaluate common Generative AI techniques and methodologies used in supply chain optimization.
Describe how Generative AI integrates with existing supply chain technologies.
Assess current advancements and innovations in Generative AI technology and their implications for the future of supply chain management.
Skills you'll gain
- Supply Chain Planning
- Responsible AI
- Supply Chain Systems
- Inventory and Warehousing
- Data Ethics
- Predictive Analytics
- Demand Planning
- AI Integrations
- Operational Efficiency
- Inventory Control
- Emerging Technologies
- Supply Chain Management
- Customer Demand Planning
- Transportation, Supply Chain, and Logistics
- AI Enablement
- Automation
- Logistics Management
- Supply Chain
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There are 2 modules in this course
In this course, youβll explore how Generative AI is reshaping supply chain management, from optimizing inventory and forecasting demand to enhancing logistics. With practical insights and real-world case studies, this course provides a comprehensive overview of AI applications in the supply chain, helping you stay ahead in an industry rapidly adopting advanced technologies. By the end, youβll understand how Generative AI can solve key supply chain challenges, preparing you to apply these innovations in your own work.
This course is ideal for logistics and supply chain professionals, operations managers, warehouse and transportation experts, production planners, and students of supply chain management. If youβre looking to leverage AI for improved efficiency and decision-making, this course offers the foundational knowledge you need. A basic understanding of supply chain management principles and terminology will be helpful, as well as familiarity with general business operations. Most importantly, bring a strong interest in emerging technologies and a curiosity about how AI can transform supply chain processes. By the end of this course, you will be able to identify and apply Generative AI techniques to optimize supply chain operations. Youβll evaluate common AI methods in demand forecasting and inventory management, understand how AI integrates with existing technologies, and gain insights into future trends and ethical considerations in AI-powered supply chain management.
This module introduces learners to the fundamentals of Generative AI and how it is revolutionizing supply chain management. Youβll explore essential AI concepts, understand the connection between Generative AI and core supply chain operations, and analyze real-world applications through detailed case studies. By the end of this module, learners will be able to define key supply chain challenges, explain where Generative AI fits within those processes, and apply foundational techniques to optimize planning, forecasting, and inventory management.
What's included
7 videos3 readings2 assignments
7 videosβ’Total 39 minutes
- Introduction to the Course & Meet Your Instructorβ’3 minutes
- Defining Supply Chain Management and Generative AIβ’6 minutes
- Common Challenges in Supply Chain Managementβ’5 minutes
- The Role of Generative AI in Solving Supply Chain Management Problemsβ’7 minutes
- Inventory Optimization with Gen AI Case Study β Part 1β’6 minutes
- Inventory Management and Optimization with Gen AI Case Study β Part 2β’5 minutes
- Inventory Management and Optimization with Gen AI Case Study β Part 3β’7 minutes
3 readingsβ’Total 15 minutes
- Welcome to the Course: Course Overviewβ’5 minutes
- Generative AI Beyond: How It Works and Real Use Casesβ’5 minutes
- AI-Powered Inventory Control by Amazonβ’5 minutes
2 assignmentsβ’Total 60 minutes
- Inventory Optimization with Generative AI β’30 minutes
- Understanding Supply Chain Management and Generative AIβ’30 minutes
Building upon the foundational skills from Module 1, this module focuses on how to implement, scale, and govern Generative AI solutions across existing supply chain systems. Learners will evaluate readiness for AI adoption, design integration roadmaps, and explore strategies to overcome implementation challenges. The module concludes with an examination of future trends, responsible AI practices, and ethical considerations in global supply chain contexts. By the end, learners will be prepared to lead AI transformation initiatives with a strategic and ethical mindset.
What's included
7 videos2 readings1 assignment1 peer review
7 videosβ’Total 41 minutes
- Evaluating Your Supply Chain for AI Integrationβ’6 minutes
- Implementation Roadmap for Generative AI in Supply Chainβ’7 minutes
- Overcoming Challenges in AI Adoptionβ’7 minutes
- Emerging Trends in Generative AI and Supply Chainβ’5 minutes
- Ethical Considerations in Generative AI Use β’6 minutes
- Building a Responsible AI Strategy for Your Supply Chain β’6 minutes
- Congratulations and Continuous Learning Journeyβ’2 minutes
2 readingsβ’Total 10 minutes
- Integrating Generative AI into Supply Chain Operationsβ’5 minutes
- Ethics of Generative AI in Healthcare Supply Chains: A Cross-Country Analysisβ’5 minutes
1 assignmentβ’Total 20 minutes
- GenAI for Supply Chain Optimizationβ’20 minutes
1 peer reviewβ’Total 60 minutes
- Exploring Generative AI in Supply Chain Managementβ’60 minutes
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Frequently asked questions
In this course, it means using generative AI to support supply chain decisions in areas like demand forecasting, inventory management, and logistics planning. The emphasis is on understanding where AI fits in supply chain work, what kinds of problems it can help with, and how people still review and interpret the results.
You would use this approach when supply chain decisions depend on changing conditions, uncertain demand, or multiple variables that are difficult to manage with fixed rules alone. The course places it in practical situations such as forecasting demand, setting inventory levels, and adjusting logistics plans.
This approach fits after you have identified a supply chain problem and before you expand a solution across day-to-day operations. The course shows it as part of a broader process that includes selecting a use case, preparing and checking data, reviewing AI outputs, and planning integration with existing systems.
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