AI x Dispute Resolution: AI and negligence – quick guide

Following the fourth session in our AI x Dispute Resolution webinar series, our team has prepared a quick guide to the key issues arising when AI is used in professional services and decision-making.

Why does AI create professional negligence risk?

AI can increase professional negligence risk because it changes how professionals think, work and make decisions. Used well, it can improve efficiency and support judgment. Used badly, it can encourage over-reliance, narrow critical thinking and create a false sense of confidence in the output.The central point is that responsibility still rests with the professional: liability will usually arise from human error, not computer error. 

How does AI challenge the standard of care?

The legal standard remains that of a reasonably competent practitioner, but AI may shift what that standard requires in practice. As adoption becomes more common, some professionals may be expected to use AI tools in appropriate contexts. At the same time, courts and regulators are likely to expect particular caution, including proper verification, supervision and escalation where output appears questionable.Compliance with common market practice may not be enough if the practice itself is careless. Professionals must also consider related risks, including confidentiality, privilege, professional conduct obligations and compliance with sector-specific AI rules. 

What should professionals disclose about AI use?

Where AI is used in delivering professional services, disclosure may be important to manage legal and regulatory risk. Clients may need to understand whether AI is being used, the extent of its involvement, any material limitations, and what human oversight is in place. In many cases, the safest approach will be early, clear and written disclosure in plain language.Failing to disclose AI use may increase the risk of breach of duty, evidential difficulty, regulatory scrutiny, loss of contractual protections and reputational damage. 

What does the recent case law tell us? 

The recent High Court decision in Cork & Or v Smith illustrates the risks clearly. In that case, lawyers relied on a non-existent Insolvency Rule generated by AI. The AI output was not properly verified, despite warnings from the tool itself, and AI was then used again to try to justify the original mistake. The supervising solicitors were unaware AI had been used. The judge's warning was clear: "Legal professionals bear ultimate responsibility for their work and cannot outsource the process of legal research or of legal reasoning to an AI." 

How might these issues arise beyond legal services?

The same issues are not confined to legal practice. In construction and design, for example, duties to know and apply published standards may be treated as non-delegable, meaning AI cannot shield a professional from liability. In dispute resolution, undisclosed use of AI in drafting awards or decision-making could create grounds for challenge, including procedural unfairness, excess of jurisdiction, irregularity and breach of confidentiality. The broader lesson is that AI can create negligence exposure wherever professional judgment must still be exercised personally. 

What should organisations consider on insurance?

Professional indemnity issues are also beginning to emerge. If AI replaces human analysis too extensively, insurers may question whether the work still amounts to the provision of professional services in the ordinary sense. Policies may also contain exclusions relating to unsupervised or unmanaged AI use, while underwriters are increasingly scrutinising firms' AI governance, controls and training when assessing risk.Organisations should not assume that existing cover will respond cleanly to AI-related claims. 

Practical steps for organisations

• Verify AI output against authoritative sources and ensure that professionals understand when independent judgment is required. 

• Strengthen governance, supervision and training, particularly for junior staff and higher-risk use cases. 

• Review disclosure practices, engagement terms and internal policies so that AI use is transparent and properly controlled. 

• Review professional indemnity cover and incident response plans to ensure they reflect AI-related risks and regulatory scrutiny. 

This session forms part four of an eight-part AI x Dispute Resolution webinar series running from February to December 2026, covering: 

• Overview of AI disputes 

• Regulatory enforcement 

• Collective and consumer actions 

• Negligence 

• Intellectual property 

• Product liability 

• AI incident response 

• Evidentiary issues 

• Future proofing against AI risk 

Join us for the rest of the series.