Training course – EU AI Act & AI Compliance – Engineering

EU AI Act & AI Compliance for Engineers

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

“EU AI Act & AI Compliance for Engineers” is a hands-on course for roles such as Design and development engineers, Project engineers in plant and machine building and Test and validation engineers. Rather than learning EU AI Act & AI Compliance in the abstract, you work on tasks from your daily routine – with examples, exercises and templates from Engineering.

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.

Engineers in design, development, plant engineering and technical planning spend much of their time on research, documentation, coordination and calculations. Generative AI can reduce that share considerably: AI assistants summarise standards and technical literature, structure requirement and design specifications, support requirements analysis, generate calculation scripts in Python or spreadsheets and produce technical documentation and reports. Automation helps with change management, comparing document revisions and analysing test and measurement data. Creative problem-solving, plausibility checks and responsibility for technical safety remain with the experts. Using AI for routine work and as a sparring partner frees time for real engineering: developing concepts, evaluating variants and delivering robust solutions.

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?

  • Design and development engineers
  • Project engineers in plant and machine building
  • Test and validation engineers
  • Technical writers
  • Engineers in planning and engineering consultancies

Typical challenges we address

  • Evaluating extensive standards, guidelines and requirements efficiently
  • Producing technical documentation and reports alongside development work
  • Analysing and interpreting test and measurement data quickly
  • Managing changes traceably across many documents and stakeholders

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.
  • Use AI for requirements analysis, standards research and technical documentation.
  • Have AI create calculation and analysis scripts and validate them systematically.
  • Protect engineering know-how and observe product safety and liability requirements when using AI.

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: Engineering
  • Structuring requirements
  • Standards and literature review
  • Calculation scripts
  • Test data analysis
  • Technical documentation
  • Change management support
Module 7 Data protection, quality & transfer to daily work
  • Design data, drawings and development results are trade secrets and may be subject to export control; they belong only in approved AI environments. Product safety and liability law apply unchanged to safety-related designs, so AI output must be verified and documented traceably.
  • 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

Structuring requirements

An AI assistant analyses customer requirements and specifications, spots contradictions, gaps and vague wording and turns them into a structured, verifiable requirements list for the design specification.

Standards and literature review

AI summarises relevant sections of standards, guidelines and technical papers, creates comparison tables and checklists and references the passages, which engineers check in the original.

Calculation scripts

Instead of coding formulas by hand, describe the calculation and receive a commented Python script or spreadsheet, for example for sizing, tolerance stack-ups or unit conversions, ready for testing and validation.

Test data analysis

Test bench data is cleaned, statistically analysed and visualised using AI-generated analysis code, anomalies are flagged and a draft test report is created.

Technical documentation

Design data, notes and previous documents are turned into drafts of operating manuals, maintenance handbooks, specifications and project reports with consistent terminology.

Change management support

AI compares document revisions, summarises technical changes clearly, identifies affected documents and interfaces and prepares change requests for the change board.

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. You have an engineering or technical background and work in development, design, planning or testing.

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

Design data, drawings and development results are trade secrets and may be subject to export control; they belong only in approved AI environments. Product safety and liability law apply unchanged to safety-related designs, so AI output must be verified and documented traceably.

Dates & locations

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

  • Munich Mon, 14 December 2026 6 hrs Request
  • Salzburg Thu, 10 December 2026 6 hrs Request
  • Berlin Tue, 15 December 2026 6 hrs Request
  • Augsburg Thu, 10 December 2026 6 hrs Request
  • Hanover Fri, 11 December 2026 6 hrs Request
  • Bremen Tue, 15 December 2026 6 hrs Request
  • Stuttgart Fri, 11 December 2026 6 hrs Request
  • Kaiserslautern Thu, 10 December 2026 6 hrs Request
  • Online Fri, 11 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 I use AI calculations for safety-related designs?

Only as support with full verification. Language models can get formulas, units or standard values wrong. Have calculation steps output as traceable code or formulas, check them against standards, hand calculations or validated software and document the check. Responsibility remains with you.

How do we protect design data?

Use only approved enterprise environments where inputs are not used for training. Also observe export control rules, for example for dual-use technologies, and agree with IT and export control which information may go into which tools. We discuss practical rules in the course.

How much does “EU AI Act & AI Compliance for Engineers” 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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