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Artificial Intelligence – Who Is Accountable For Getting It Wrong?

05 November 2025

Artificial Intelligence (AI) is no longer a futuristic concept; it’s already shaping how we live and work.

From customer service chatbots and legal research tools to medical diagnostics and financial decision-making systems, AI is driving efficiency and innovation across industries.

But as AI becomes more powerful, a crucial legal and ethical question arises:
Who is responsible when AI makes a mistake?

Why AI Makes Mistakes

AI systems depend on the data they’re trained on. If that data is incomplete, biased, or inaccurate, the results will often reflect those flaws. Even when trained on high-quality data, AI can misinterpret complex contexts or miss nuances that a human professional would spot instantly.

These errors can range from harmless misunderstandings to serious consequences, such as:

• A misdiagnosis in healthcare
• A wrongful loan rejection in finance
• Or flawed legal advice generated by an automated tool

In many cases, the danger lies not in an obvious error, but in one that goes unnoticed until it causes harm.

Accountability: Who Bears the Risk?

The law on AI accountability is still developing, in the UK and internationally. For now, liability usually depends on the specific circumstances. In broad terms:

• Organisations using AI may be held responsible if they fail to ensure the technology is properly tested, monitored, and fit for purpose.
• Developers or software suppliers might be liable if the issue stems from a defect in the system or inadequate safeguards.
• Human operators or professionals retain a duty to review AI outputs and apply judgment, especially in regulated sectors such as law, finance, and healthcare.

Ultimately, relying on AI without human oversight is risky. In most cases, responsibility rests with the person or organisation that made or acted upon the final decision.

The Dangers of Over-Reliance on AI

While AI can increase efficiency, there are real risks in trusting its outputs without scrutiny:

• Loss of critical thinking: Over-reliance on AI can cause professionals to stop questioning results.
• Bias amplification: AI may perpetuate existing inequalities if trained on biased data.
• Lack of transparency: Some AI systems operate as “black boxes,” making it difficult to understand how they reach conclusions.
• Data protection breaches: AI tools can raise UK GDPR compliance concerns if they process personal data improperly.

The safest approach is to treat AI as a supportive tool, not a substitute for human expertise.

Best Practices for Responsible AI Use

If your business or profession uses AI, there are practical steps you can take to manage legal and operational risks:

• Validate key outputs with human review.
• Maintain records of how decisions are made and where AI is involved.
• Train staff to understand the technology’s strengths and limitations.
•  Choose transparent suppliers who can explain their data sources and testing processes.
• Have a response plan for identifying and correcting AI errors promptly.

These measures can help build trust, compliance, and accountability in your use of artificial intelligence.

Looking Ahead: Law and Accountability in the Age of AI
AI is set to become even more integrated into professional life, including the legal, healthcare, and financial sectors. With this progress must come clear accountability frameworks and continued human oversight. Public trust in AI will depend on confidence that when technology fails, there is both a safety net and a clear route to redress.

We can help you navigate the legal and regulatory implications of AI in your business, ensuring accountability is clear and risks are managed. Get in touch today to discuss how to protect your organisation in the age of AI.

 

 

 

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