Training course · AI Agents · E-Commerce

AI Agents for E-Commerce 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 E-Commerce Teams” is a hands-on course for roles such as E-commerce managers and shop owners, Marketplace and category managers and Product data and PIM managers. Rather than learning AI Agents in the abstract, you work on tasks from your daily routine – with examples, exercises and templates from E-Commerce.

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.

In e-commerce, every product page, search query and customer enquiry counts. Generative AI opens up new possibilities for online retailers and brands: AI assistants create and optimise product descriptions, translate catalogues, structure product attributes, analyse customer reviews and support marketplace listings. Automation and AI agents maintain product data, monitor prices and stock, answer routine questions and prepare campaigns for sales events. Shop analytics also become more accessible, because questions about conversion, baskets and returns can be asked in natural language. Success requires clean product data, clear quality rules for generated copy and compliance with the many information obligations in online retail. Then AI becomes a lever for visibility, conversion and efficient operations.

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?

  • E-commerce managers and shop owners
  • Marketplace and category managers
  • Product data and PIM managers
  • Digital marketing and SEO specialists
  • Founders and owners of online shops

Typical challenges we address

  • Keeping thousands of product records complete, consistent and multilingual
  • Increasing visibility in search engines and on marketplaces
  • Analysing and handling returns, reviews and customer enquiries efficiently
  • Delivering sales events and range changes with limited resources

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.
  • Create and maintain product content efficiently, in several languages and at consistent quality with AI.
  • Analyse shop, review and returns data with AI and derive concrete actions.
  • Design AI-supported shop processes in compliance with consumer protection and data protection law.

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: E-Commerce
  • Product description generation
  • Product data enrichment
  • Catalogue translation
  • Reviews and return reasons
  • Marketplace listing optimisation
  • Natural language shop analytics
Module 7 Data protection, quality & transfer to daily work
  • Online retail is subject to extensive consumer information duties, price indication rules, unfair competition law for product claims and the Digital Services Act for platforms; AI-generated copy must not contain misleading statements. Customer data from orders and reviews must be processed in line with the GDPR.
  • 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

Product description generation

Using manufacturer data, attributes and brand guidelines, AI creates search-friendly product copy, bullet points and meta descriptions, which the team spot-checks and approves.

Product data enrichment

AI extracts attributes such as material, dimensions or compatibility from data sheets, normalises spelling and assigns products to the right category to improve filters and on-site search.

Catalogue translation

Product copy is translated and localised for new markets using a glossary for brand terms and units, with native-speaker review for key pages.

Reviews and return reasons

Customer reviews and return reasons are clustered by topics such as fit, quality or delivery, so buying, product development and content teams can make targeted improvements.

Marketplace listing optimisation

AI adapts titles, bullet points and keywords to the requirements of individual marketplaces and checks listings for missing mandatory information or policy violations.

Natural language shop analytics

Exports from the shop system and web analytics are analysed with AI, for example conversion rate by category, basket abandonment or best-sellers, including hypotheses for optimisation tests.

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 an online shop, on marketplaces or in digital retail and have a basic understanding of your shop system.

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

Online retail is subject to extensive consumer information duties, price indication rules, unfair competition law for product claims and the Digital Services Act for platforms; AI-generated copy must not contain misleading statements. Customer data from orders and reviews must be processed in line with the GDPR.

Suggested dates

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

  • Tue, 24 November 2026 – Wed, 25 November 2026 Online Request
  • Thu, 3 December 2026 – Fri, 4 December 2026 Munich Request
  • Thu, 10 December 2026 – Fri, 11 December 2026 Online Request
  • Mon, 14 December 2026 – Tue, 15 December 2026 Stuttgart Request
  • Mon, 18 January 2027 – Tue, 19 January 2027 Online Request
  • Tue, 26 January 2027 – Wed, 27 January 2027 Berlin 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.

Does AI-generated product copy hurt SEO?

Not if it is helpful and unique. The problem is interchangeable copy that merely rephrases manufacturer information. Precise attributes, usage examples, answers to frequent customer questions and a quality check produce copy that convinces search engines and shoppers alike. We practise exactly these prompting and review routines.

Who is liable for errors in AI-generated copy?

The retailer is liable for all product information, regardless of how it was created. Incorrect dimensions, materials or efficacy claims can lead to legal warnings. AI copy should therefore be based only on verified product data, and sensitive claims such as health or environmental statements should be approved separately.

How much does “AI Agents for E-Commerce 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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