📝 General Introduction

As digital transformation accelerates across industries, artificial intelligence (AI) has emerged as a game-changer in supply chain optimization. Among its most impactful applications are demand forecasting and intelligent resource allocation.

Traditional forecasting methods rely heavily on historical data and static models, often failing to capture real-time market dynamics. AI, however, leverages machine learning algorithms and predictive analytics to anticipate customer behavior, optimize inventory levels, and allocate resources with precision.

This 5-day workshop is designed to equip professionals with the knowledge and tools to apply AI effectively in supply chain planning. Participants will explore forecasting models, resource distribution algorithms, data analysis techniques, and system integration strategies.

Through hands-on exercises and case studies, attendees will learn how to build smart operational frameworks that reduce waste, improve responsiveness, and support sustainable growth. Whether you're managing logistics, planning inventory, or leading digital innovation, mastering AI in supply chain operations is essential for future-ready performance.

🎯 Target Audience

• Supply chain and planning managers
• Operational data analysts
• Digital transformation and innovation officers
• Industrial and commercial operations teams
• Entrepreneurs in e-commerce and distribution

🎯 Expected Objectives

• Understand the fundamentals of AI in supply chain operations
• Apply predictive models to improve demand forecasting accuracy
• Use intelligent algorithms for efficient resource allocation
• Analyze operational data to support decision-making
• Build smart, AI-driven operational models for scalability and agility

📚 Scientific Topics:

Axis 1: Introduction to AI in Supply Chains

Session 1: Core Concepts of Artificial Intelligence

• AI vs. machine learning
• Types of algorithms used in supply chains
• Real-world applications and case studies

Session 2: Strategic Importance of AI

• Enhancing forecast accuracy
• Reducing operational costs
• Improving market responsiveness

Axis 2: Demand Forecasting with AI

Session 1: Predictive Modeling Techniques

• Historical data analysis
• Neural networks and regression models
• Seasonal and dynamic forecasting

Session 2: Forecasting Tools and Platforms

• AI-powered forecasting software
• Integration with ERP and SCM systems
• Evaluating and improving forecast accuracy

Axis 3: Intelligent Resource Allocation

Session 1: Allocation Algorithms

• Priority-based distribution
• Smart geographic allocation
• Resource matching with predicted demand

Session 2: Real-Time Resource Management

• Live tracking and monitoring
• Automated redistribution
• Waste reduction and efficiency gains

Axis 4: Data Analysis and Decision Support

Session 1: Data Analytics Tools

• Using Power BI and Python
• Trend and pattern analysis
• Linking data to operational KPIs

Session 2: Smart Decision-Making

• Interactive dashboards
• Predictive performance indicators
• Data-driven strategic planning

Axis 5: Practical Implementation and Sustainability

Session 1: Building a Smart Operational Model

• Designing AI-based scenarios
• Integrating AI into daily workflows
• Testing and refining models

Session 2: Sustaining AI Solutions

• Updating models with market changes
• Training teams on AI tools
• Measuring impact and ROI