Training course – EU AI Act & AI Compliance – Product Management

EU AI Act & AI Compliance for Product Managers

Putting the EU AI Act into practice: risk categories, deployer obligations, AI literacy under Art. 4, AI policy and GDPR interfaces.

Duration
6 hours, one session
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 EU AI Act & AI Compliance with the everyday processes of Product Management. Participants work on realistic scenarios and leave with prompts, workflows and checklists they can use straight away.

The EU AI Act is the first comprehensive legal framework for artificial intelligence, and it applies not only to providers but also to organisations that use AI systems in their daily work. In this compact course you will learn how the regulation is structured: prohibited practices, high-risk systems, transparency obligations and general-purpose AI models. You will find out which role your organisation plays as a deployer, which obligations follow and how to record and classify the AI applications you use in a structured way.

The practical part turns the requirements into manageable steps. You clarify what the AI literacy obligation under Article 4 means in concrete terms, how to organise training in a verifiable way and what an internal AI policy should cover. You also examine the interfaces with the GDPR, such as legal bases, data protection impact assessments and automated decision-making. You leave with an AI inventory template, a draft policy and a clear compliance roadmap for your area of work.

Product managers connect customer needs, business goals and technical delivery. Their day revolves around discovery, prioritisation, specification and alignment with engineering, design, sales and leadership. Generative AI speeds up almost every one of these steps: it analyses customer feedback, interviews and support tickets, helps write product requirements and user stories, structures competitor analyses and prepares roadmap communication for different stakeholders. With vibe coding, product managers can build clickable prototypes themselves and test ideas before committing engineering capacity. AI agents bring together signals from analytics, CRM and feedback tools. That leaves more time for product vision, decisions and conversations with customers.

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?

  • Product managers
  • Product Owners in agile teams
  • Heads of Product and product directors
  • Product marketing teams
  • UX researchers and product designers

Typical challenges we address

  • Large amounts of unstructured feedback from many channels
  • Heavy effort for specifications and stakeholder alignment
  • Prioritising under uncertainty and competing interests
  • Long lead times from idea to testable prototype

What you will be able to do

  • You can explain how the EU AI Act is structured and assign your organisation to the correct roles.
  • You can classify the AI applications in use by risk category and maintain an AI inventory.
  • You can name the specific obligations of deployers and derive appropriate measures.
  • You can develop an AI literacy concept under Article 4 and a draft internal AI policy.
  • Synthesise customer feedback and market information with AI into well-founded product decisions.
  • Produce specifications, user stories and roadmap communication faster and more precisely with AI.
  • Build clickable prototypes through vibe coding to validate ideas early with users.

Course outline

Module 1 Structure and logic of the EU AI Act
  • Objectives, scope and phased application of the regulation
  • Roles at a glance: provider, deployer, importer and distributor
  • The risk-based approach: prohibited practices, high risk, limited risk and minimal risk
  • Specific rules for general-purpose AI models
Module 2 Classifying risk in practice
  • Prohibited practices such as social scoring or emotion recognition in the workplace
  • High-risk areas under Annex III, including recruitment, creditworthiness and education
  • Transparency obligations for chatbots, synthetic content and deepfakes
  • Recording and classifying your own AI applications in an AI inventory
Module 3 Obligations for deployers of AI systems
  • Use in line with instructions and human oversight by competent staff
  • Input data quality, monitoring of operation and retention of logs
  • Informing employees and affected persons and reporting serious incidents
  • Fundamental rights impact assessment: when it is required and how it works
Module 4 AI literacy under Art. 4 and internal AI policy
  • What sufficient AI literacy means for different roles
  • Designing training concepts and documenting measures verifiably
  • Components of an AI policy: approved tools, data classes, approvals and labelling
  • Responsibilities, AI officers and involving the works council and IT
Module 5 GDPR interfaces and governance
  • Legal bases, purpose limitation and data minimisation when using AI
  • Data protection impact assessment and its relationship to the fundamental rights assessment
  • Automated individual decisions, data subject rights and data processing agreements
  • Compliance roadmap: priorities, ownership and regular review
Module 6 Practice lab: Product Management
  • Synthesising customer feedback
  • PRDs and user stories
  • Preparing prioritisation
  • Competitor and market analysis
  • Prototypes via vibe coding
  • Roadmap and release communication
Module 7 Data protection, quality & transfer to daily work
  • Customer feedback and usage data often contain personal information and are subject to the GDPR; they should be pseudonymised before being processed in AI tools. Roadmaps and unreleased product information are trade secrets, and AI features in your own product must be assessed against the requirements of the EU AI Act.
  • 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

Synthesising customer feedback

Interviews, support tickets, app reviews and surveys are grouped by theme, problem and request and turned into an opportunity overview with supporting quotes for discovery.

PRDs and user stories

Problem statement, target users and goals become drafts of product requirement documents, user stories with acceptance criteria and edge cases, refined with engineering and design.

Preparing prioritisation

AI helps score initiatives using frameworks such as RICE or Kano, surface assumptions and prepare arguments for and against options ahead of prioritisation discussions. Disagreements become easier to resolve.

Competitor and market analysis

Feature comparisons, positioning and pricing models of competitors are structured and updated regularly; claims are backed by sources and checked critically. You keep track of market moves without lengthy manual research.

Prototypes via vibe coding

Product managers use AI coding tools to build clickable prototypes and simple functional demos to test concepts with users and make requirements tangible for the team.

Roadmap and release communication

Roadmaps, release notes, internal enablement material and customer communication are tailored to the audience – technical for engineering, benefit-led for sales and customers. Every audience gets exactly what it needs.

Prerequisites

No legal background is required. A basic knowledge of the GDPR and an overview of the AI applications used or planned in your area are helpful. Experience in product management or as a Product Owner; no programming skills required.

Technical requirements

All you need is a laptop with an up-to-date browser and an office suite for working with templates. No special AI licences are necessary.

Data protection & compliance

Customer feedback and usage data often contain personal information and are subject to the GDPR; they should be pseudonymised before being processed in AI tools. Roadmaps and unreleased product information are trade secrets, and AI features in your own product must be assessed against the requirements of the EU AI Act.

Dates & locations

For every location we suggest a date roughly four weeks ahead. Your preferred date is always possible.

  • Munich Wed, 16 December 2026 6 hrs Request
  • Salzburg Wed, 16 December 2026 6 hrs Request
  • Berlin Tue, 15 December 2026 6 hrs Request
  • Augsburg Fri, 11 December 2026 6 hrs Request
  • Hanover Mon, 14 December 2026 6 hrs Request
  • Bremen Wed, 16 December 2026 6 hrs Request
  • Stuttgart Wed, 16 December 2026 6 hrs Request
  • Kaiserslautern Thu, 10 December 2026 6 hrs Request
  • Online Mon, 14 December 2026 6 hrs Request

Frequently asked questions

Does the EU AI Act apply to companies that only use AI tools?

Yes. Anyone using AI systems under their own authority in a professional context is a deployer. All deployers must, in particular, ensure that their staff have sufficient AI literacy. Where high-risk systems are used, for example in recruitment, further obligations apply, such as human oversight, logging and informing the people affected.

Does this course satisfy the training obligation under Article 4?

The course covers core AI literacy content and you receive a certificate of attendance that you can add to your documentation. However, Article 4 requires measures tailored to role, prior knowledge and context of use. That is why you also learn how to set up and maintain your own AI literacy concept for your organisation.

Does the course replace legal advice?

No. The training provides practical knowledge for specialists and managers so they can interpret requirements, ask precise questions and implement first measures. For binding assessments of individual systems, especially in high-risk areas, you should involve your legal department, your data protection officer or external specialist lawyers.

Can AI make product decisions?

No, but it improves the basis for them. AI condenses feedback, surfaces assumptions and prepares options. Product vision, weighing trade-offs and accountability for decisions remain with product management. In the course you use AI deliberately as an analysis and sparring partner without giving up critical judgement.

How far can I get with vibe-coded prototypes?

Very far for clickable interfaces, simple logic and user testing – often within a few hours. Production-ready software with security, scalability and maintainability remains engineering's job. The course shows how prototypes improve collaboration with the team rather than replacing it.

How much does “EU AI Act & AI Compliance for Product Managers” cost?

The course costs a flat €949 plus VAT per participant – whether online or on-site. This includes 6 hours of live training with a trainer, course materials, a lab environment and a certificate of attendance.

Can I suggest my own date?

Yes. For every location we suggest a date roughly four weeks ahead. In the request form you can always describe your preferred date or period in free text – we check availability and get back to you 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 and Kaiserslautern. We can also run the course exclusively for your team.

Can the course be tailored to our team?

Yes. Tailor-made courses cost approx. €4,500 more, depending on the topic and by arrangement. We agree content, examples and exercises with you in advance.

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