AI for Logistics and Supply: Practical No-Code Applications for the Fuel Industry Training Course

Module 1: Fundamentals of AI in Logistics and Supply

• Exploring Artificial Intelligence: key concepts and practical uses
• AI in logistics and fuel distribution: potential opportunities and impact
• No-code AI platforms: Excel AI, ChatGPT, Power BI, and additional tools
• Real-world examples from the transport and fuel industries

Module 2: Structuring and Analyzing Operational Data

• Recognizing key logistics and supply datasets (routes, tanks, deliveries)
• Preparing volumetric control and inventory data for AI integration
• Cleaning, formatting, and validating data in Excel
• Building dynamic tables and pivot charts to generate insights

Module 3: AI-Driven Forecasting for Fuel Demand

• Grasping demand forecasting and the variables that influence it
• Leveraging Excel’s AI features and ChatGPT for predictive analysis
• Predicting short-term (1–2 week) fuel demand trends
• Practical exercise: developing a basic forecast model using existing data

Module 4: Route Planning and Resource Optimization

• Core concepts in route optimization and scheduling
• Employing AI tools to recommend optimal routes and delivery sequences
• Applying Excel and ChatGPT for route planning with actual constraints
• Practical activity: generating route alternatives for delivery units

Module 5: Cost Estimation and Logistics Optimization

• Identifying cost factors: distance, tolls, fuel usage, freight
• Using AI models to calculate logistics costs
• Comparing manual versus AI-assisted cost planning methods
• Developing cost calculation templates with dynamic inputs

Module 6: Dashboards and KPI Visualization

• Introduction to Power BI and Excel dashboards
• Designing visual reports for logistics and supply KPIs
• Integrating data from volumetric control systems
• Hands-on session: creating a real-time logistics performance dashboard

Module 7: Integrating AI into Logistics Workflows

• Automating repetitive reporting and data consolidation tasks
• Utilizing Power Automate or Excel macros for process automation
• Setting up alert systems for inventory or delivery thresholds
• Real-world example: AI-based alerts for tank refill scheduling

Module 8: 90-Day AI Adoption Plan for Logistics and Supply

• Creating a step-by-step roadmap for AI implementation
• Selecting pilot use cases and defining success metrics
• Expanding AI-assisted workflows across teams
• Establishing practices for continuous improvement and knowledge sharing

Summary and Next Steps