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

Module 1: Introduction to AI in Logistics and Supply

• Grasping Artificial Intelligence: key concepts and uses
• AI in logistics and fuel distribution: potential benefits and impact
• No-code AI solutions: Excel AI, ChatGPT, Power BI, and others
• Real-world examples from the transport and fuel industries

Module 2: Structuring and Analyzing Operational Data

• Recognizing essential logistics and supply datasets (routes, tanks, deliveries)
• Preparing volumetric control and inventory data for AI processing
• Data cleansing, formatting, and validation using Excel
• Building dynamic tables and pivot charts to generate insights

Module 3: AI-Assisted Forecasting for Fuel Demand

• Comprehending demand forecasting and key influencing factors
• Leveraging Excel’s AI capabilities and ChatGPT for predictive analysis
• Predicting short-term (1–2 week) fuel demand trends
• Practical task: constructing a simple forecast model using existing data

Module 4: Route Planning and Resource Optimization

• Core concepts in route optimization and scheduling
• Utilizing AI tools to recommend optimal routes and delivery sequences
• Applying 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 Optimization

• Identifying cost drivers: distance, tolls, fuel usage, freight
• Using AI models to predict logistics costs
• Comparing manual versus AI-assisted cost planning approaches
• Creating cost calculation templates with dynamic inputs

Module 6: Dashboards and KPI Visualization

• Overview of Power BI and Excel dashboards
• Designing visual reports for logistics and supply KPIs
• Incorporating data from volumetric control systems
• Practical session: building a real-time logistics performance dashboard

Module 7: Integrating AI into Logistics Workflows

• Automating repetitive reporting and data consolidation tasks
• Using Power Automate or Excel macros for task 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

• Developing 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