AI and legal liability in Europe for coprorations

Artificial intelligence (AI) has become a core technology in the modern European economy. Companies increasingly integrate AI systems into their operations for automation, data analytics, recruitment, customer service, marketing optimisation, fraud detection, and software development. While these technologies deliver significant efficiency gains and innovation opportunities, they also introduce complex legal and regulatory challenges.

To address these developments, the European Union has adopted the AI Act, the first comprehensive legal framework dedicated to artificial intelligence. This regulation applies directly across all EU Member States, including Belgium, and establishes a harmonised approach aimed at promoting innovation while safeguarding fundamental rights, safety, and accountability.

1. The EU AI Act: a risk-based regulatory model

The AI Act is built on a risk-based classification system that categorises AI applications into four levels:

• minimal risk
• limited risk
• high risk
• unacceptable risk

Most AI systems fall into the minimal or limited risk categories and are subject to lighter obligations, mainly transparency requirements. However, high-risk systems are heavily regulated due to their potential impact on individuals’ rights and safety.

High-risk AI systems typically include:

• recruitment and HR management tools
• credit scoring and financial risk assessment systems
• insurance underwriting systems
• educational assessment tools
• critical infrastructure management systems
• certain healthcare applications

For these systems, companies must comply with strict legal obligations, including:

• technical documentation and record-keeping
• transparency regarding system design and logic
• human oversight mechanisms
• high-quality and non-biased datasets
• risk management and continuous monitoring systems
• conformity assessments before deployment

The AI Act also prohibits certain AI practices entirely, such as systems designed for manipulative behaviour, social scoring of individuals, or applications that pose unacceptable risks to fundamental rights.

2. Legal liability of companies using AI systems

One of the most critical legal questions is liability when AI systems cause harm. Under European law, responsibility generally lies with the company deploying the AI system, not the technology itself.

This means that businesses remain legally accountable for decisions made or influenced by AI systems within their operations.

Typical liability scenarios include:

• discriminatory outcomes in automated recruitment systems
• incorrect creditworthiness assessments
• faulty automated decisions affecting customers or employees
• financial losses caused by algorithmic errors
• reputational damage due to biased AI outputs

For example, an AI-powered hiring tool that systematically excludes certain candidates based on indirect discriminatory patterns may expose the company to employment discrimination claims and compensation liabilities.

In addition to the deploying company, AI providers and developers may also face liability under product liability principles, particularly when the system is defective, inadequately tested, or insufficiently documented.

The European Commission has also been working on modernising product liability rules to better address AI-related harms, further strengthening accountability across the AI value chain.

3. AI and data protection under GDPR

Most AI systems rely on large-scale processing of personal data, making the General Data Protection Regulation (GDPR) a central legal framework.

Companies must ensure full compliance with GDPR principles, including:

• lawful, fair, and transparent processing of data
• purpose limitation (data used only for specific purposes)
• data minimisation
• accuracy and data integrity
• storage limitation
• confidentiality and security measures

AI systems often involve automated decision-making that can significantly affect individuals. In such cases, GDPR provides additional safeguards, including:

• the right to human intervention
• the right to contest automated decisions
• the right to obtain meaningful information about the logic involved

Non-compliance can result in substantial administrative fines, reaching up to €20 million or 4% of global annual turnover, whichever is higher, in addition to reputational harm and potential civil claims.

4. Intellectual property challenges in AI systems

The rise of generative AI introduces significant legal uncertainty in the field of intellectual property (IP). AI systems can generate text, images, code, music, and other creative outputs based on training data that may include copyrighted works.

Key legal issues include:

• whether copyrighted content can be used for AI training
• who owns AI-generated outputs
• whether AI-generated works qualify for copyright protection
• potential infringement risks in generated content

European copyright law traditionally requires human authorship, which creates uncertainty regarding ownership of AI-generated materials.

Businesses must therefore implement clear contractual frameworks addressing IP ownership, licensing rights, and liability allocation between AI providers, developers, and users.

Failure to properly manage IP risks may expose companies to litigation and injunctions for copyright infringement.

5. AI governance and corporate compliance strategies

Given the complexity of the regulatory environment, companies must implement robust AI governance and compliance structures. This is no longer optional but a strategic necessity.

Effective compliance frameworks typically include:

• internal AI usage policies and governance rules
• AI system inventories and documentation
• regular legal and technical risk assessments
• compliance audits and monitoring mechanisms
• contractual safeguards with AI vendors and service providers
• employee training on responsible AI use

Regulators across the EU are increasingly active in enforcing digital and AI-related regulations. Companies that fail to comply risk not only financial penalties but also operational restrictions and reputational damage.

A proactive compliance strategy also offers competitive advantages, as it enhances trust among clients, partners, and regulators.

Conclusion

Artificial intelligence offers significant opportunities for businesses across Europe, but it also introduces a complex legal environment shaped by the AI Act, GDPR, product liability rules, and intellectual property law.

Companies deploying AI systems must adopt a proactive and structured legal approach to ensure compliance, mitigate risks, and secure sustainable innovation. Legal governance is no longer an administrative burden but a core component of responsible and competitive digital transformation.