The Legal Tech Blog

Smarter Than Legal? AI, Ethics & the New Rules of the Game  

Written by STP Group | Dec 2, 2025 8:00:00 AM

Why the EU AI Act Alone Is Not Enough 

Is following the law enough to keep your AI out of trouble—or do ethics and public perception matter even more? Since August 1, 2024, the EU AI Act has been the world’s first comprehensive legal framework for artificial intelligence. It sets binding requirements to protect fundamental rights, safety, and democratic values. But is mere legal compliance really sufficient? How do companies handle ethical challenges, contractual risks, and public pressure? And how can AI be used responsibly and future-proof? 

Beyond Compliance: Where Real AI Risks Begin 

Could your AI be legally compliant but still fail with customers, employees, or the public? The EU AI Act defines clear minimum standards. However, the biggest risks—such as ethical issues and contractual risks—often lie beyond the law. Even if an AI system complies with all regulations, it can fail in the market if customers, employees, or other stakeholders perceive it as unfair, opaque, or irresponsible. Companies are increasingly under public scrutiny, and reputational damage cannot be fixed with fines alone. Compliance forms the foundation, but ethics and clear contracts provide stability and resilience for the entire system. 

The Legal Pitfalls Behind AI Decisions 

Are your AI systems unintentionally creating bias that could spark lawsuits or reputational damage? Bias (systematic distortions in data or models) often unintentionally leads to discriminatory decisions, favoring or disadvantaging certain groups or outcomes. For example, a recruitment algorithm trained on biased historical data can systematically disadvantage certain groups. Such biases can trigger not only regulatory sanctions but also discrimination lawsuits. There is also the risk that affected individuals or interest groups publicly oppose the use of AI, causing significant reputational damage. The EU AI Act therefore requires: 

  • Strict documentation 
  • Bias testing 
  • Explainability of decisions 

For legal departments, this means systems must be not only technically traceable but also plausibly explainable to non-technical stakeholders. Transparency obligations and ethical fairness must go hand in hand. Close collaboration with data and technical teams is essential to identify risks early, assess them legally, and secure them contractually. 

AI Clauses in Contracts: Warranties, Audit Rights & Accountability 

Do your contracts protect you if AI decisions go wrong—or are you leaving liability on the table? Anyone buying, developing, or distributing AI technology should no longer sign contracts without AI-specific provisions. Key points include: 

  • Warranties: Assurance that the AI is operated in compliance with the EU AI Act (data quality and security standards) 
  • Audit Rights: Ability to regularly review systems and data processing (especially for third parties) to verify compliance and technical security 
  • Accountability: Clear liability rules when AI decisions cause damage or legal violations 

The “Model AI Clauses Sheet” helps with proven wording for SaaS and procurement contracts or data transfer agreements, including risk scoring (low – medium – high) for each clause. 

Companies should ensure that clauses not only meet current regulatory requirements but also cover future legal changes and technological developments. Audit rights must be practically enforceable, and responsibilities clearly assigned to avoid disputes in case of damage. 

Cross-Border Data Flows, Third Parties & Black-Box Decisions 

How much risk are you taking when your AI relies on third parties and opaque algorithms abroad? Many AI systems access global data pools or cloud infrastructures outside the EU. This raises questions about international data protection, law enforcement, and contractual safeguards. Third parties are often the “invisible” weak link in the compliance chain. Especially when their algorithms operate as black boxes without disclosure of training data or decision logic. 

Recommendations for legal and compliance teams: 

  • Include contractual transparency obligations 
  • Secure technical control options 
  • Evaluate alternative providers offering more openness 
  • Ensure GDPR compliance even with cross-border data flows to avoid fines and legal risks 
  • Conduct regular risk assessments of external service providers to identify weaknesses early and take preventive action 

Conclusion: Ethics, Contracts & Control as Success Factors 

Are you just meeting minimum standards—or shaping AI governance that truly drives responsible, resilient success? While the EU AI Act lays the legal foundation, sustainable success with AI requires going beyond. Ethics, clear contract design, and technical control are essential to avoid liability risks, reputational damage, and operational disruptions. Now is the time to set your own standards that exceed minimum requirements and to proactively shape your AI governance instead of merely reacting to regulation. 

 

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More about the implications of the EU AI Act: An overview of our blog series for you (coming soon):


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