Who’s Liable When AI Goes Wrong? A Legal Perspective
- Partner
- Jun 11, 2024
- 3 min read
Updated: Aug 13, 2025
Understanding how modern legal systems handle damage caused by autonomous technologies
As artificial intelligence becomes increasingly embedded in industries like healthcare, finance, transportation, and law enforcement, a critical question arises: who is responsible when AI systems cause harm? From self-driving vehicles causing accidents to biased facial recognition tools misidentifying individuals, AI-related incidents are no longer theoretical — they are real and growing. The legal world is now racing to catch up, trying to define responsibility in a space where technology moves faster than regulation.
Why AI Breaks the Legal Mold
AI presents two major challenges to traditional legal systems. The first is opacity.
Many AI systems operate as “black boxes,” making decisions that even their creators cannot fully explain. This lack of transparency makes it difficult to determine if negligence or design flaws are to blame when things go wrong.
The second issue is autonomy and adaptation. Unlike traditional software, many AI systems learn and evolve over time. A system that functions safely on day one may later produce unintended outcomes after being exposed to new data. These two characteristics—lack of transparency and evolving behavior—make assigning liability particularly difficult under existing legal frameworks.
Current Legal Approaches to AI Liability
Courts and lawyers are adapting established legal doctrines to the AI context.
Product liability treats AI as a product, making developers and manufacturers responsible for system defects.
Negligence focuses on whether the AI system was tested, maintained, or monitored with sufficient care.
Vicarious liability assigns responsibility to companies for the actions of AI systems operating under their control, similar to employer-employee relationships.
Contractual allocation allows companies to define liability in advance through commercial agreements.
While each of these approaches provides partial answers, none fully address the complexity of modern AI systems. Judges and lawmakers are often left stretching existing rules to fit situations those laws were never designed to handle.
Who Might Be Held Responsible?
Responsibility may lie with different parties depending on how and why the AI caused harm. Developers can be liable for flawed or unsafe design. Companies that deploy AI systems might be responsible for failing to monitor performance or train staff properly. Data providers could share fault if biased or inaccurate data led to harmful outcomes. Even third-party auditors or certifiers, who vouch for the safety of AI, could face legal consequences if their evaluations prove faulty.
In some cases, end users themselves may bear responsibility, particularly if they misuse AI despite clear warnings.
Although AI systems cannot currently be sued or held directly liable, legal theorists continue to debate whether certain forms of “electronic personhood” could be created in the future. For now, however, liability lies with the people and organizations behind the AI.
What’s Next: Toward New Legal Frameworks
Because traditional liability models don’t fully account for the risks of autonomous systems, several new legal frameworks are being explored. Some lawmakers propose strict liability for high-risk AI, holding developers or users automatically responsible for harm, regardless of fault. Others suggest shifting the burden of proof to AI operators, requiring them to demonstrate they took reasonable precautions.
Additional ideas include no-fault compensation systems, which would allow victims to be compensated without the need to prove liability, and adaptive liability, where responsibility shifts depending on how autonomous the AI system is.
Although the EU AI Act is a significant regulatory step, it doesn’t yet cover liability. However, a proposed AI Liability Directive aims to fill this gap by simplifying the path to compensation for individuals harmed by AI.
Conclusion
As AI technologies become more powerful and autonomous, the legal landscape must evolve to meet new risks. Liability is no longer a simple matter of user error or product malfunction—it now involves a complex web of developers, operators, data sources, and decision-making algorithms.
If your company develops or uses AI systems and wants to reduce legal risks or ensure compliance, contact us for a consultation. We help tech businesses navigate AI liability and regulation with confidence, clarity, and a practical mindset.
