CQ | AI Omnibus: What Risks Does Simplifying Artificial Intelligence Regulation Bring to Europe?

Europe is preparing to adopt a new legislative framework for artificial intelligence, but the rush to simplify regulations may create breaches that are hard to repair. What happens when transparency and accountability become optional, and citizens’ rights are pushed into the background?

AI Omnibus, the legislative package under discussion at the European level, promises to accelerate innovation and AI implementation, but the relaxation of some protective measures raises serious questions. For professionals and managers in the field, it is essential to understand the risks this simplification brings and how they can contribute to maintaining ethics and safety in the AI era.

Context and Current Affairs: AI Omnibus and the Motivations for Simplification

Amid intense global competition for supremacy in the field of artificial intelligence, the European Union has accelerated the process of adopting a dedicated legislative framework: AI Omnibus. This package comes as a response to the pressure not to fall behind the United States or China in the race for innovation, as well as the need to provide a predictable framework for companies developing or implementing AI technologies.

However, during negotiations, some of the strictest protective measures initially proposed—such as mandatory independent auditing of high-risk AI systems, clear requirements for algorithmic transparency, or extended developer responsibility—were either eliminated or significantly relaxed. The main motivation: reducing bureaucracy and stimulating rapid innovation.

Practical Implications: Risks for Transparency, Auditing, and Accountability

Algorithmic Transparency – Between Ideal and Reality

One of the biggest challenges of AI Omnibus is the lack of firm requirements regarding algorithmic transparency. Without clear obligations to explain how AI systems work, users—whether companies or citizens—are often left in the dark about automated decisions that affect them.

• Lack of transparency can hide algorithmic biases or arbitrary decisions.
• Without access to explanations, challenging automated decisions becomes nearly impossible.

Independent Auditing: A Weak Link

Independent auditing of AI systems was initially a key component for preventing abuses and identifying ethical risks. The relaxation of this requirement in AI Omnibus means that many companies will be able to self-assess, which significantly reduces external oversight and impartiality.

Corporate Responsibility – Between Regulation and Self-Regulation

AI Omnibus tends to shift part of the responsibility to companies, relying on good internal practices and self-regulation. However, in the absence of clear standards and effective sanctions, there is a risk that some organizations may treat aspects such as data protection, ethical testing, or user information superficially.

• Companies may be tempted to prioritize rapid market launch over safety and ethics.
• Diffuse responsibility makes it difficult to hold anyone accountable in the case of serious incidents.

Risks to Citizens’ Rights and Social Safety

In the absence of robust regulations, fundamental rights—such as access to justice, non-discrimination, or privacy protection—can be seriously affected. AI systems used in sensitive areas (human resources, healthcare, justice, credit) can amplify existing inequities if not subjected to rigorous oversight.

• The risk of algorithmic discrimination increases in the absence of auditing and transparency.
• Social safety can be compromised if AI systems escape public oversight.

Conclusion: How Can Professionals and Decision-Makers Protect Ethics and Rights in the AI Era?

Although AI Omnibus represents an important step toward AI regulation at the European level, excessive simplification may create more problems than it solves. Professionals and managers involved in developing or implementing AI have the responsibility to demand strong standards, independent auditing, and real transparency.

• Support self-regulation initiatives based on clear ethical principles.
• Request external audits for AI systems with major impact.
• Promote transparency and proper information for users and beneficiaries.

(This material was assisted by an AI tool and reviewed by our team before publishing).