Prompt Engineering in Logistics

Course overview

The training course on Prompt Engineering in Logistics demonstrates how generative AI can be specifically applied to logistical processes. Participants will learn how to use Prompt Engineering to support and automate planning, information, and decision-making processes in logistics. Practical application cases from transport, warehousing, and supply chain management will be covered. !Introduction to Prompt Engineering and Logistics *Importance of Prompt Engineering for logistics *Overview of core logistical processes: procurement, warehousing, transport, distribution *Role of generative AI systems in modern logistics *Opportunities, limitations, and risk assessment !Fundamentals of Prompt Engineering *Structure of effective prompts for logistical tasks *Role and context definition in Prompt Engineering *Error analysis and iterative improvement of prompts *Handling incomplete or contradictory data !Application Cases of Prompt Engineering in Logistics *Support for tour and route planning *Creation of warehousing and picking instructions through Prompt Engineering *Automated documentation, email, and report generation *Use of AI-supported assistants in logistics customer service !Integration into Processes and Systems *Incorporation of Prompt Engineering into existing IT and logistics systems *Interfaces to transport management, warehouse management, and ERP systems *Automation of recurring tasks along the supply chain *Data protection, information security, and compliance in logistics Upon completion of the training, participants will understand how to specifically apply Prompt Engineering in logistics. They will be able to develop prompts for logistical application cases, evaluate results, and integrate AI-supported solutions into processes. This will contribute to increased efficiency, reduced errors, and better decision-making in logistics practice.

Upcoming dates

• 2026-08-09T22:00:00.000Z · 2026-10-17T22:00:00.000Z · München · Hybrid Learning
• 2026-08-09T22:00:00.000Z · 2026-10-17T22:00:00.000Z · Aachen · Hybrid Learning
• 2026-08-09T22:00:00.000Z · 2026-10-17T22:00:00.000Z · Berlin · Hybrid Learning
• 2026-08-09T22:00:00.000Z · 2026-10-17T22:00:00.000Z · Berlin · Hybrid Learning
• 2026-08-09T22:00:00.000Z · 2026-10-17T22:00:00.000Z · Berlin · Hybrid Learning