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What legal requirements apply to the use of AI?

Compliance with legal guidelines is a prerequisite for the safe and legally compliant use of Artificial Intelligence in the company. Since 2024/2025, binding rules have been in force in all EU countries with the European AI Act – regardless of whether you develop AI systems yourself or use market-ready solutions. Knowing the requirements early avoids legal risks and simultaneously strengthens the trust of customers and employees in the use of AI.

What role do law and regulation play in the context of AI?

Why are law and regulation important?

Law and regulation are useful if you ...

  • want to develop or train your own AI systems,

  • use AI tools in your professional daily routine – including market-ready solutions,

  • need to train employees in handling AI, as this has been mandatory since February 2, 2025, according to Article 4 of the EU AI Regulation,

  • work in a regulated industry like healthcare, financial services, or transportation,

  • work with personal data or copyrighted content.

The earlier you know the legal framework conditions, the more securely and quickly you can implement AI projects without having to make corrections later.

Labelling requirement for AI content

Since August 2, 2026, transparency regulations in Article 50 of the AI Act have been in effect. They aim to help EU citizens recognize when they are interacting with an AI system or are exposed to AI-generated content.

The European Commission has compiled the most important facts:

Our topic ambassadors

Portrait von Klaus Brisch, Grant Thornton Rechtsanwaltsgesellschaft mbH
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Klaus Brisch

Grant Thornton Rechtsanwaltsgesellschaft mbH
Lawyer, Partner and Head of IT/IP, Data Protection, Digital Innovation

"Regulation of Artificial Intelligence is crucial for innovation and risk minimization. “AI by (legal) design” reduces development costs, increases the marketability of AI products, and improves the competitiveness of companies.

Portrait von Philippe Coution, TÜV SÜD
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Philippe Coution

TÜV SÜD 
Head of Digital Interaction & Lead AI Quality

"A comprehensive understanding of AI quality is essential to ensure compliance with legal regulations and standards and to scale your own AI activities.

Portrait von Prof. Dr. Dr. Eric Hilgendorf, JMU Würzburg
Logo Julius-Maximilians-Universität Würzburg und robot recht forschungsstelle

Prof. Dr. Dr. Eric Hilgendorf

JMU Würzburg
Chair of Criminal Law, Criminal Procedure Law, Legal Theory, Information Law and Legal Informatics and Member of the Bavarian AI Council

"AI should become a technology that does not harm, that helps, that creates benefits, that one can accept and trust. Laws can significantly contribute to this trust having a safe foundation and thus being preserved in the long term.

Who is affected?

The regulation covers every company or organization that uses AI tools. Operators of AI systems are, according to the AI-VO, "natural or legal persons, authorities, institutions, or other bodies that use an AI system in their own responsibility." Thus, all professional applications are included – only private, non-professional uses are exempt.

How do I proceed?

The following approach has proven itself for many companies:

  1. Step 1 – Check involvement: Clarify whether your company qualifies as an operator of an AI system within the meaning of the AI Regulation. This affects every professional use of AI tools, regardless of company size or industry – only purely private use is excluded.

  2. Step 2 – Conduct a risk assessment: Assign your AI applications to the four risk levels of the AI Act, from harmless to unacceptable. This way, you will understand which obligations apply specifically to you.

  3. Step 3 – Ensure AI competence: Plan training measures for your employees according to Article 4 of the AI Regulation – as an online course, face-to-face training, or self-study, appropriate to the knowledge level and application field of your team.

  4. Step 4 – Obtain legal advice: Check, especially for self-developed AI systems and questions about data protection, copyright, and industry-specific requirements, whether you need legal support.

  5. Step 5 – Regularly review the legal situation: Regulation is evolving dynamically. Follow current developments and constantly adapt your processes to remain compliant long-term.

Why is AI training or education important?

Well-founded training or education not only ensures compliance with legal requirements but also brings numerous advantages to companies:

  • Risk minimization: Trained employees can reduce errors and misuse potentials.

  • Efficiency increase: A better understanding of AI technologies enables more effective use of the systems.

  • Competitive advantage: Companies that responsibly and competently use AI can implement innovations more quickly.

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The BAIOSPHERE AI COMPASS 

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KI-Kompass

STRATEGY

Strategic planning secures competitive advantages and includes setting goals, identifying use cases, and integrating AI into the company's overall strategy.

Data

Data is the foundation for every AI system. Their quality and integrity determine the possibilities and performance of AI applications.

ECOSYSTEM

Cooperations can bring many advantages in the use and implementation of AI. A strong ecosystem promotes innovations through the transfer of knowledge, resources, and technologies.

FINANCING AND FUNDING

The costs of implementing AI vary between free versions and significant investments for the development of own solutions. To alleviate the investment burden, there are various funding opportunities.

CULTURE AND MINDSET

An open and learning-oriented corporate culture is fundamental to implementing AI successfully. The focus is on reducing reservations and fears and involving the workforce in the transformation process.

Organization

The use of AI requires a well-thought-out organizational structure. This forms the foundation for the sustainable development of AI technologies as well as effective collaboration between different departments and interdisciplinary teams.

Technical Requirements

A robust and flexible infrastructure includes hardware and software components, network infrastructure, and development processes to successfully implement, train, test, and use AI models.

Talents and Competencies

Development and integration of AI require a qualified team and specific knowledge. This includes both technical skills and strategic and infrastructural understanding.

Law and Regulation

Compliance with legal requirements and standards is essential for the use of AI. Thus, with the EU AI Act, guidelines for AI solutions have been created that will apply in all EU states for the creation and use of AI.

Ethics

Ethics in AI includes the implementation of moral principles to realize the benefits of AI and reduce risks. Topics such as transparency, fairness, the avoidance of bias, explainability, and data protection are essential in this context.