Training course – EU AI Act & AI Compliance – Controlling

EU AI Act & AI Compliance for Controllers

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 Controllers” is a hands-on course for roles such as Controllers and finance business partners, Heads of controlling and FP&A analysts. 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 Controlling.

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.

Controlling depends on reliable figures, fast analysis and clear communication with management. Generative AI supports controllers at exactly these points: AI assistants explain variances in the monthly report, suggest formulas and pivot structures, sanity-check planning assumptions and turn findings into plain-language management commentary. AI agents and automation pull data from the ERP, BI tools and spreadsheets, prepare forecasts and generate standard reports. This accelerates the shift from number cruncher to business partner who explains root causes and prepares decisions. A clean data foundation, clearly defined KPIs and expert review of every AI result remain essential before anything reaches a report or a board paper.

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?

  • Controllers and finance business partners
  • Heads of controlling
  • FP&A analysts
  • Cost centre and project controllers
  • Sales and manufacturing controllers

Typical challenges we address

  • Commenting on monthly reports and explaining variances under time pressure
  • Consolidating plans and forecasts from many spreadsheets and departments
  • Defining KPIs consistently and presenting them for different audiences
  • Answering ad-hoc management questions quickly and reliably

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 variance analysis, forecasting and management commentary with traceable results.
  • Have AI build formulas, queries and small reporting automations and validate them confidently.
  • Establish rules for quality assurance and confidential use of controlling data.

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: Controlling
  • Variance commentary
  • Formulas and queries
  • Challenging forecast assumptions
  • Management reporting
  • Reporting automation
  • KPI glossary
Module 7 Data protection, quality & transfer to daily work
  • Controlling data contains trade secrets and often personal data such as payroll costs per employee; only use approved AI environments and pseudonymise data in line with GDPR principles. Listed companies must also protect inside information under MAR.
  • 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

Variance commentary

An AI assistant analyses budget-to-actual and prior-year comparisons, identifies the biggest drivers by cost type, product or region and drafts commentary for the monthly report for controllers to review.

Formulas and queries

Describe the analysis you need in plain words and receive suggested spreadsheet formulas, pivot logic, Power Query steps or SQL queries with explanations that you can test straight away.

Challenging forecast assumptions

AI questions planning assumptions on volumes, prices and costs, highlights inconsistencies between departmental plans and builds best, base and worst-case scenarios as a basis for discussion.

Management reporting

KPIs and raw data are turned into concise executive summaries, slide outlines and traffic-light commentary tailored to executives, divisional heads or cost centre owners.

Reporting automation

A workflow pulls ERP and BI exports, checks completeness, refreshes standard reports and sends drafts to cost centre owners, who add their comments before the pack is finalised.

KPI glossary

An AI assistant helps document KPI definitions, calculation logic and data sources consistently, so that business units and management speak the same language and discussions about figures become more objective.

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 work in controlling or FP&A and are comfortable with spreadsheets and core cost accounting metrics.

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

Controlling data contains trade secrets and often personal data such as payroll costs per employee; only use approved AI environments and pseudonymise data in line with GDPR principles. Listed companies must also protect inside information under MAR.

Dates & locations

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

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

Will AI replace our BI system?

No. BI systems and data warehouses remain the reliable data foundation. AI adds a layer for interpretation, commentary and fast ad-hoc analysis. In the course we show how to pass exports to AI assistants sensibly, check results against the source and automate recurring steps without creating shadow IT.

How reliable are figures calculated by AI?

Language models can miscalculate or mismatch data. Prefer having calculations run through generated, reviewable code or formulas, and reconcile totals with the source. We practise checking routines that let you confirm plausibility quickly before any number makes it into a report.

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