Introduction

The "AI and Automation in Supply Chain Operations" course is designed to equip supply chain professionals with the knowledge and skills necessary to leverage AI and automation technologies in their operations. Over five days, participants will delve into the transformative impact of these technologies on logistics, procurement, inventory management, and customer service, ultimately driving efficiency and competitive advantage.

Objectives
• Understand the fundamentals of AI and automation in supply chain management.
• Explore the latest AI technologies and their applications in logistics and warehousing.
• Learn how to integrate automation tools for efficient inventory management.
• Evaluate the impact of AI-driven analytics on decision-making processes.
• Develop strategies for implementing AI and automation in supply chain operations.

Course Outlines

Day 1: Introduction to AI and Automation in Supply Chain

• Overview of supply chain management and its challenges.
• Introduction to AI and automation technologies.
• The role of AI in transforming supply chain operations.
• Case studies of successful AI implementation in supply chains.
• Discussion: Current trends and future outlook.

Day 2: AI Applications in Logistics and Warehousing

• AI-driven logistics and transportation management systems.
• Robotics and automation in warehousing operations.
• Optimizing distribution networks with AI.
• Technologies for real-time tracking and visibility.
• Workshop: Designing an AI-enabled warehousing solution.

Day 3: Automation Techniques for Inventory Management

• Introduction to automated inventory control systems.
• Predictive analytics for demand forecasting and planning.
• Utilizing AI for supplier management and procurement.
• Role of IoT in smart inventory management.
• Hands-on session: Creating an automated inventory model.

Day 4: AI-Driven Analytics and Decision Making

• Understanding AI algorithms and data analytics.
• Leveraging big data for supply chain optimization.
• Tools and platforms for AI-driven business intelligence.
• Impact of AI analytics on risk management and compliance.
• Case study analysis: Decision-making with AI insights.

Day 5: Implementing AI and Automation Strategies

• Developing a roadmap for AI and automation integration.
• Overcoming challenges in implementation and change management.
• Ensuring cybersecurity and data privacy in AI applications.
• Assessing the ROI of AI and automation investments.
• Final project: Designing an AI-enhanced supply chain strategy.