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 use cases
• The role of AI in logistics and fuel distribution: potential and impact
• Overview of no-code AI tools: Excel AI, ChatGPT, Power BI, and more
• Real-world examples from the transportation and fuel industries

Module 2: Organizing and Analyzing Operational Data

• Identifying critical logistics and supply datasets (routes, tanks, deliveries)
• Structuring volumetric control and inventory data for AI integration
• Cleaning, formatting, and validating data in Excel
• Generating insights through dynamic tables and pivot charts

Module 3: AI-Driven Fuel Demand Forecasting

• Understanding demand forecasting and key influencing factors
• Applying Excel’s AI capabilities and ChatGPT for predictive analysis
• Projecting short-term (1–2 week) fuel demand trends
• Practical exercise: developing a simple forecast model using available data

Module 4: Route Planning and Resource Optimization

• Core concepts in route optimization and scheduling
• Using AI tools to recommend optimal routes and delivery sequences
• Leveraging Excel and ChatGPT for route planning with real-world constraints
• Hands-on activity: generating route options for delivery units

Module 5: Cost Estimation and Logistics Efficiency

• Recognizing cost drivers: distance, tolls, fuel usage, and freight
• Employing AI models to estimate logistics costs
• Comparing manual planning versus AI-assisted cost estimation
• 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: building a real-time logistics performance dashboard

Module 7: Integrating AI into Logistics Workflows

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

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

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

Summary and Next Steps