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

Module 1: AI Fundamentals in Logistics and Supply

• Exploring Artificial Intelligence: key concepts and uses
• AI in logistics and fuel distribution: potential benefits and effects
• Overview of no-code AI solutions: Excel AI, ChatGPT, Power BI, and others
• Real-world examples from the transport and fuel sectors

Module 2: Organizing and Interpreting Operational Data

• Pinpointing crucial logistics and supply datasets (routes, tanks, deliveries)
• Preparing volumetric and inventory data for AI processing
• Data hygiene, formatting, and validation using Excel
• Building dynamic tables and pivot charts to derive insights

Module 3: AI-Driven Fuel Demand Forecasting

• Understanding demand prediction and its influencing factors
• Utilizing Excel’s AI capabilities and ChatGPT for predictive tasks
• Projecting short-term (1–2 week) fuel demand patterns
• Practical task: creating a simple forecast model with available data

Module 4: Route Planning and Resource Efficiency

• Core principles of route optimization and scheduling
• Using AI tools to recommend best routes and delivery orders
• Applying Excel and ChatGPT for planning with real-world constraints
• Activity: generating route alternatives for delivery vehicles

Module 5: Cost Analysis and Logistics Efficiency

• Recognizing cost factors: distance, tolls, fuel usage, freight
• Using AI models to project logistics expenses
• Contrasting manual planning with AI-assisted cost strategies
• Creating cost calculation templates with variable inputs

Module 6: Dashboards and KPI Visualisation

• Intro to Power BI and Excel dashboard design
• Designing visual reports for logistics and supply KPIs
• Connecting data from volumetric control systems
• Practical: building a live logistics performance dashboard

Module 7: Embedding AI in Logistics Processes

• Automating routine reporting and data aggregation
• Using Power Automate or Excel macros for task streamlining
• Setting up alerts for inventory or delivery limits
• Example: AI-triggered alerts for tank refill scheduling

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

• Developing a phased AI implementation roadmap
• Selecting pilot projects and defining success criteria
• Expanding AI-supported workflows across teams
• Establishing habits for continuous improvement and knowledge exchange

Wrap-up and Future Directions