Training course · Generative AI · Logistics & Supply Chain

Generative AI for Logistics and Supply Chain Teams

Vendor-neutral, hands-on day: how language models work, where they go wrong and how to roll out AI successfully in your team.

Duration
1 day (7 hrs)
Format
Online or on-site
Language
German or English
Participants
open dates or exclusive for your team
Certificate
Certificate of attendance

Overview

This course connects Generative AI with the everyday processes of Logistics & Supply Chain. Participants work on realistic scenarios and leave with prompts, workflows and checklists they can use straight away.

Generative AI has reached most organisations, yet teams often lack a shared understanding of what language models can actually do and where their limits lie. In this vendor-neutral course you will learn how large language models generate text, why they hallucinate and how careful prompting, context and source checking lead to reliable results. Rather than relying on any provider's marketing claims, you will work with transparent criteria that help you compare tools and judge their fit for your own tasks.

The second focus is everyday implementation. You will identify concrete use cases in your area of work, weigh benefit, risk and effort, and draft a realistic roll-out plan for your team. This covers ground rules for handling confidential data, a practical prompt library and ways to build acceptance and make results measurable. Throughout the day you work with examples from your own field, so you leave with an actionable roadmap rather than a set of abstract ideas.

Logistics and supply chain management are under constant pressure: volatile demand, disrupted supply chains, rising freight costs, staff shortages and growing demands for transparency and sustainability. Generative AI offers new tools for planning and communication. AI assistants analyse inventory and shipment data, explain forecast deviations, create work instructions for warehouse and shipping, answer customer status enquiries and help clarify customs and Incoterms questions. AI agents and automation process delivery notifications, freight documents and order confirmations, monitor delays and suggest actions. This frees up time for exception management and optimisation. The prerequisites are clean master data, access to ERP, WMS and TMS data and clear ownership of decisions.

The course is delivered live – either online in a virtual classroom or on-site in our training rooms in Munich, Salzburg, Berlin, Augsburg, Hanover, Bremen, Stuttgart and Kaiserslautern. We can also run it exclusively for your team.

Who is this course for?

  • Supply chain managers and planners
  • Logistics and warehouse managers
  • Transport dispatchers and freight forwarders
  • Customs and foreign trade specialists
  • Demand and inventory planners

Typical challenges we address

  • Detecting and communicating delivery delays and disruptions early
  • Balancing inventory between service levels and working capital
  • Processing large volumes of freight documents and notifications manually
  • Onboarding new warehouse and dispatch staff quickly

What you will be able to do

  • You can explain clearly how language models generate text and why hallucinations occur.
  • You can write prompts that consistently deliver useful, verifiable results.
  • You can compare AI tools against transparent criteria covering data protection, features and cost.
  • You can identify and prioritise concrete use cases for your area of work.
  • Use AI for inventory, forecast and disruption analysis in the supply chain.
  • Automate document processing and status communication with clear review steps.
  • Design AI-supported logistics processes that are secure, traceable and respect employee co-determination.

Course outline

Module 1 How large language models work
  • Tokens, context windows and probabilities: what happens when a model generates text
  • Training knowledge versus web search versus your own documents (RAG)
  • Text, images, audio and code: what multimodal models can do today
  • Realistically assessing typical strengths and weaknesses in office work
Module 2 Spotting hallucinations and getting reliable output
  • Why models produce plausible-sounding errors and when the risk increases
  • Prompting techniques: role, context, examples, output format and step-by-step instructions
  • Requesting sources, cross-checking facts and introducing a four-eyes principle
  • Scoping tasks so that AI assists rather than decides
Module 3 Choosing tools without vendor bias
  • Overview of chat assistants, AI built into office suites and specialist tools
  • Criteria: data processing, hosting location, admin features, integrations and pricing model
  • Enterprise licences, API access and locally hosted open-source models compared
  • Building a simple scoring matrix for your own tool selection
Module 4 Identifying use cases in your field
  • Systematically capturing recurring writing, research and analysis tasks
  • Rating benefit, risk and implementation effort for each use case
  • Distinguishing quick wins from strategic initiatives
  • Creating a prioritised use-case backlog for your team
Module 5 Rolling out generative AI in your team
  • Usage rules: which data may go into which tool and who signs off results
  • Building and maintaining a shared prompt library and templates
  • AI champions, training formats and peer exchanges to embed new habits
  • Measuring success: documenting time saved, quality and user satisfaction
Module 6 Practice lab: Logistics & Supply Chain
  • Managing disruptions and delays
  • Freight document processing
  • Inventory and forecast analysis
  • Work instructions and training
  • Customs and trade questions
  • Shipment status enquiries
Module 7 Data protection, quality & transfer to daily work
  • Logistics data contains personal information, for example about drivers and recipients, which must be processed in line with the GDPR; AI-based analysis of employee performance or location requires works council involvement in Germany. Customs and export control decisions remain governed by applicable trade regulations, and AI output must be checked by experts.
  • Ground rules for safe AI use in your team
  • Checking results: facts, sources, tests and the four-eyes principle
  • Personal action plan for the next 30 days
  • Open questions, outlook and resources for further learning

Practical scenarios from your field

Managing disruptions and delays

Automations compare shipment status with planned dates; AI summarises critical delays, assesses affected orders and drafts customer notifications and options for action.

Freight document processing

AI reads delivery notes, consignment notes, packing lists and customs documents, checks them for completeness and consistency with the order and passes structured data to the ERP or WMS.

Inventory and forecast analysis

Exports from planning and ERP systems are analysed, slow movers and stock-out risks identified and forecast deviations explained clearly as input for S&OP meetings.

Work instructions and training

Process descriptions become clear, multilingual work instructions for goods receipt, picking and shipping, including checklists and quiz questions for onboarding.

Customs and trade questions

An AI assistant explains Incoterms, rules of origin or tariff classification as a starting point for research and prepares questions for customs experts, who verify results against official sources.

Shipment status enquiries

An assistant answers status enquiries based on tracking data, explains delays transparently and routes complaints with complete information to the responsible team.

Prerequisites

No technical background is required. It helps to bring along typical tasks from your day-to-day work that you would like to support with AI. You work in logistics, supply chain management or dispatch and know the processes and systems in your area.

Technical requirements

You will need a laptop with an up-to-date browser and internet access. A free account with a common AI assistant is sufficient; company licences are welcome.

Data protection & compliance

Logistics data contains personal information, for example about drivers and recipients, which must be processed in line with the GDPR; AI-based analysis of employee performance or location requires works council involvement in Germany. Customs and export control decisions remain governed by applicable trade regulations, and AI output must be checked by experts.

Suggested dates

All dates are suggestions – your preferred date is always possible.

  • Tue, 24 November 2026 Online Request
  • Thu, 3 December 2026 Kaiserslautern Request
  • Mon, 7 December 2026 Online Request
  • Wed, 13 January 2027 Augsburg Request
  • Wed, 27 January 2027 Online Request
  • Tue, 9 February 2027 Salzburg Request

Frequently asked questions

Is the course tied to a specific AI tool?

No. The training is deliberately vendor-neutral. You work with widely used chat assistants and learn principles that apply to all major language models. That way you can transfer your skills to whichever tool your organisation has approved and evaluate new offerings yourself using clear criteria instead of relying on marketing statements.

How is confidential company data handled during the course?

For the exercises you use anonymised or fictitious examples from your area of work. At the same time you learn which categories of data may be entered into which tools, what to look for regarding data processing agreements and use of inputs for training, and how to set out these rules clearly for your team.

Will we leave with something concrete to implement?

Yes. You leave with a prioritised use-case backlog, a scoring matrix for tool selection, tested prompt templates and a draft set of team usage rules. These materials are designed so you can take them straight into internal discussions with management, IT and your data protection officer.

Will generative AI replace our planning software?

No. Specialised planning, warehouse management and transport systems remain the backbone. Generative AI complements them with analysis, explanation, communication and document processing. In the course we show how to analyse exports from these systems with AI and automate recurring workflows.

Is AI reliable for customs questions?

AI is a good starting point for research and structure, but it can be wrong about tariff codes, preference rules or sanctions lists. Binding decisions require official sources and expertise, such as binding tariff information. We practise checking AI output systematically against official sources.

How much does “Generative AI for Logistics and Supply Chain Teams” cost?

The course costs a flat €949 plus VAT per participant – whether online or on-site. This includes 1 training day(s) with a live trainer, course materials, a lab environment and a certificate of attendance.

Can I suggest my own date?

Yes. Our suggested dates are just a guide. In the request form you can always describe your preferred date or period in free text – we check availability and confirm within one working day.

Is the course online or on-site?

Both are possible: live online in a virtual classroom or on-site in Munich, Salzburg, Berlin, Augsburg, Hanover, Bremen, Stuttgart or Kaiserslautern. We can also run the course exclusively for your team.

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