Training course · ChatGPT · Logistics & Supply Chain

ChatGPT for Logistics and Supply Chain Teams

Use ChatGPT safely and productively at work: projects, custom GPTs, data analysis, Canvas and privacy settings in team workspaces.

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

“ChatGPT for Logistics and Supply Chain Teams” is designed for roles such as Supply chain managers and planners, Logistics and warehouse managers and Transport dispatchers and freight forwarders and shows step by step how to use ChatGPT productively, safely and transparently in Logistics & Supply Chain – from the fundamentals to advanced workflows.

For many business teams, ChatGPT is the first AI tool they use every day – yet there is a methodical gap between asking the odd question and achieving real productivity gains. In this hands-on day you learn to apply ChatGPT deliberately to recurring work: drafting and editing text, summarising documents, analysing spreadsheets and structuring decision papers. You work with Projects that keep files and instructions together, with Canvas for reworking longer documents, and with data analysis for Excel and CSV files. Every exercise is based on genuine tasks from your own function.

The second focus is scale and responsibility. You build a custom GPT that knows your templates, tone of voice and review rules, and that colleagues across the workspace can use. We also clarify which data belongs in ChatGPT and which does not, how Team and Enterprise workspaces differ from personal accounts, and which settings matter for model training, memory and sharing. You leave with a personal prompt library, a working GPT and clear ground rules for using ChatGPT responsibly across your organisation.

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 write structured prompts that reliably produce usable results for your day-to-day tasks.
  • You organise your work in Projects and revise longer documents efficiently with Canvas.
  • You analyse spreadsheets and files with data analysis and critically verify the results.
  • You build a custom GPT for a recurring task and share it with your team.
  • 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 Foundations and effective prompting
  • How language models work: strengths, limitations and hallucinations
  • Building effective prompts with role, context, task and output format
  • Refining iteratively instead of starting over: follow-ups and correction loops
  • Choosing models and using web search and deep research appropriately
Module 2 Projects, Canvas and document work
  • Setting up Projects to group files, instructions and chats by topic
  • Summarising, comparing and interrogating long documents
  • Using Canvas to revise text and drafts section by section
  • Templates for emails, reports, minutes and presentation outlines
Module 3 Data analysis with spreadsheets and files
  • Uploading, cleaning and analysing Excel and CSV files
  • Calculating KPIs, replicating pivot logic and explaining variances
  • Generating charts and preparing them for presentations
  • Verifying results: checking calculation steps and sanity checks
Module 4 Custom GPTs for recurring tasks
  • Identifying and scoping good use cases for GPTs
  • Configuring instructions, knowledge files and conversation starters
  • Testing, improving and sharing a GPT within the workspace
  • Maintenance, change tracking for instructions and ownership in the team
Module 5 Privacy, workspaces and governance
  • Personal accounts versus Team and Enterprise workspaces
  • Settings for model training, memory, temporary chats and sharing
  • Handling personal and confidential data in line with GDPR
  • Internal usage policy and quality assurance for AI output
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

Confident use of office applications and a web browser; no prior AI knowledge is required. Feel free to bring your own non-confidential sample tasks from your daily work. You work in logistics, supply chain management or dispatch and know the processes and systems in your area.

Technical requirements

A laptop with an up-to-date browser and a ChatGPT account; a paid plan or access to your organisation's Team or Enterprise workspace is recommended for custom GPTs, Projects and data analysis.

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.

  • Wed, 25 November 2026 Online Request
  • Thu, 10 December 2026 Bremen Request
  • Mon, 11 January 2027 Salzburg Request
  • Wed, 27 January 2027 Online Request
  • Wed, 3 February 2027 Kaiserslautern Request
  • Mon, 8 February 2027 Online Request

Frequently asked questions

Do I need a paid ChatGPT licence for the course?

You can follow the fundamentals with a free account. However, features such as custom GPTs, Projects with larger files and advanced data analysis are tied to paid plans or come with far more generous limits there. Ideally you join with access to your organisation's Team or Enterprise workspace, so you practise under real conditions.

May I enter confidential company data into ChatGPT?

That depends on your plan, your contractual terms and your internal policy. In Team and Enterprise workspaces, content is not used for training by default, but GDPR and confidentiality obligations still apply. In the course you learn how to classify and anonymise data and how to choose the right settings.

How is a custom GPT different from a saved prompt?

A GPT bundles persistent instructions, knowledge files and optional tools such as web search or data analysis into a dedicated assistant. Colleagues can use it without any prompting skills and get consistent results. A saved prompt, by contrast, has to be copied and supplemented with context every time, which is far more error-prone.

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 “ChatGPT 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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