Training course · AI Agents · Logistics & Supply Chain

AI Agents for Logistics and Supply Chain Teams

Agentic AI for business teams: understand AI agents, automate workflows safely and keep control with human-in-the-loop and governance.

Duration
2 days (14 hrs)
Format
Online or on-site
Language
German or English
Participants
open dates or exclusive for your team
Certificate
Certificate of attendance

Overview

“AI Agents for Logistics and Supply Chain Teams” is a hands-on course for roles such as Supply chain managers and planners, Logistics and warehouse managers and Transport dispatchers and freight forwarders. Rather than learning AI Agents in the abstract, you work on tasks from your daily routine – with examples, exercises and templates from Logistics & Supply Chain.

AI agents go a step beyond conventional chat assistants: they plan sub-tasks, use tools such as search, files or business applications and complete multi-step work largely on their own. Over two days you will learn how agents are built, how they differ from chatbots and traditional automation, and which tasks genuinely justify their use. Widely used platforms serve as practical examples, including Microsoft Copilot Studio, custom GPTs and Claude with projects and tool connections.

In the hands-on sessions you design agent workflows for tasks from your own area of work, from triaging requests through research and drafting to handing results over to business systems. You decide where a person reviews and approves, which permissions an agent receives and how errors are detected. A dedicated block covers governance, data protection and accountability, so that your agents not only work but remain controllable, traceable and defensible within 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 can explain how AI agents are structured and clearly distinguish them from chatbots and classic automation.
  • You can select a suitable agent platform for your requirements using transparent criteria.
  • You can design an agent workflow for a real process in your area and build a working prototype.
  • You can define human-in-the-loop checkpoints, test cases and escalation rules.
  • 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

Day 1

Module 1 What makes an AI agent
  • Agent building blocks: language model, instructions, knowledge, tools and memory
  • How agents differ from chatbots, macros and classic workflow automation
  • Levels of autonomy: from suggestion-making assistants to agents that act independently
  • Realistically judging which tasks suit agents and which do not
Module 2 Platform overview: Copilot Studio, GPTs and Claude
  • Microsoft Copilot Studio: agents grounded in company data and connected to Microsoft 365
  • Custom GPTs: configuring instructions, knowledge files and actions
  • Claude with projects, knowledge bases and tool access via the Model Context Protocol
  • Selection criteria: data access, integrations, administration and licensing
Module 3 Designing and building agent workflows
  • Breaking tasks into steps and defining hand-offs between agent and human
  • Writing system instructions, examples and knowledge sources for consistent output
  • Connecting tools: search, documents, email, spreadsheets and business applications
  • Building a prototype agent for a real process from your own area
Module 4 Human-in-the-loop, quality and error handling
  • Setting approval steps, escalation rules and thresholds for human review
  • Test cases, evaluation criteria and spot checks for quality assurance
  • Common failure modes: wrong tool choice, endless loops and fabricated facts
  • Using structured user feedback to improve the agent over time

Day 2

Module 5 Governance, security and roll-out
  • Roles and responsibilities across business units, IT, data protection and works council
  • Least-privilege permissions, logging and protection against prompt injection
  • Positioning under the EU AI Act and GDPR: transparency, documentation and data flows
  • From pilot agent to production: operation, maintenance and measuring success
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

You should already use an AI assistant such as ChatGPT, Copilot or Claude on a regular basis. No programming skills are required. 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. Ideally you have access to at least one agent platform such as Copilot Studio, ChatGPT with GPTs or Claude; practice accounts can be provided if needed.

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 – Thu, 26 November 2026 Online Request
  • Tue, 8 December 2026 – Wed, 9 December 2026 Bremen Request
  • Tue, 19 January 2027 – Wed, 20 January 2027 Salzburg Request
  • Wed, 3 February 2027 – Thu, 4 February 2027 Online Request
  • Wed, 10 February 2027 – Thu, 11 February 2027 Kaiserslautern Request
  • Wed, 17 February 2027 – Thu, 18 February 2027 Online Request

Frequently asked questions

Do I need programming skills to build AI agents?

No. The platforms used on the course rely on visual interfaces, plain-language instructions and ready-made connectors. You learn to specify agents precisely from a business perspective, connect tools and test workflows. Where deeper technical integration would be needed, you will know which requirements to put to your IT team.

Which platform will we use during the course?

The course is vendor-neutral and uses Microsoft Copilot Studio, custom GPTs and Claude as examples. You build your prototype on the platform that is available or planned in your organisation. The principles of workflow design, control and governance you learn carry over to other agent solutions as well.

How do I stop an agent from acting without control?

Through deliberate design: agents receive only the minimum permissions they need, critical actions such as sending, booking or deleting require human approval, and every step is logged. In addition, you define test cases and escalation rules. These are exactly the control mechanisms you develop for your own use case during the course.

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 “AI Agents for Logistics and Supply Chain Teams” cost?

The course costs a flat €949 plus VAT per participant – whether online or on-site. This includes 2 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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