AI in clinical negligence and personal injury claims – Where can it help?

Artificial intelligence (AI) is rapidly transforming the landscape of clinical negligence and personal injury claims in Great Britain. This article explores the multifaceted ways AI can assist legal practitioners, primarily by streamlining the arduous process of medical record review, enhancing the analysis of breach and causation, and aiding in quantum assessment. While offering significant benefits in efficiency and accuracy, the integration of AI also introduces complex challenges, particularly concerning liability when AI-driven errors occur, ethical considerations such as bias and data privacy, and the paramount need for continued human oversight. Practitioners must navigate these opportunities and risks, adhering to existing regulatory frameworks and evolving professional duties.

The legal profession in Great Britain is experiencing a profound technological shift, with Artificial Intelligence (AI) emerging as a powerful tool poised to redefine traditional legal practices. For claimant personal injury and clinical negligence solicitors, the potential benefits of AI are particularly compelling. These areas of law are inherently document-heavy, often involving vast quantities of medical records, correspondence, expert reports, and disclosure documents that demand meticulous and time-consuming review.

This article delves into the specific applications of AI within clinical negligence and personal injury claims, highlighting where this technology can offer substantial assistance to legal professionals. It will examine how AI can enhance efficiency, accuracy, and strategic insight throughout the claims process. However, the integration of AI is not without its complexities, and this analysis will also address the critical legal and ethical challenges that practitioners must navigate, including questions of liability, data protection, and the imperative of human oversight.

Clinical negligence and personal injury claims in the UK are characterised by their intricate factual matrices and the sheer volume of evidence that must be processed. A typical case can involve hundreds, if not thousands, of pages of medical records, which paralegals and solicitors traditionally review manually to construct chronologies, identify key events, and establish causation. This manual process is not only time-intensive and costly but also prone to human error, potentially leading to missed critical details or delays in case progression.

The legal framework governing disclosure in civil proceedings in England and Wales, primarily set out in Part 31 of the Civil Procedure Rules (CPR) and Practice Direction 57AD (PD 57AD) for Business and Property Courts, mandates parties to disclose all documents relevant to the issues in dispute. The definition of 'document' is broad, encompassing anything in which information is recorded, including electronic data. The duty extends to documents that support one's own case, adversely affect one's own case, or support/adversely affect another party's case. The increasing volume of electronically stored information (ESI) further exacerbates the challenges of traditional document review, making the need for more efficient solutions pressing.

Against this backdrop, legal technology, and specifically AI, has begun to offer solutions. The Solicitors Regulation Authority (SRA) has acknowledged the role of technology, stating that solicitors may use AI tools provided they uphold existing professional standards, including maintaining professional responsibility, verifying AI outputs, and protecting client confidentiality.

AI's utility in clinical negligence and personal injury claims primarily manifests in its capacity to manage and analyse large datasets. One of its most impactful applications is in **document review and analysis**. AI-powered platforms can rapidly process extensive medical records, including scanned and handwritten documents, to extract key dates, diagnoses, treatments, and findings. Tools leveraging Natural Language Processing (NLP) and Machine Learning (ML) can generate comprehensive medical chronologies, narrative summaries, and identify inconsistencies or gaps in treatment, significantly reducing the manual effort required. This allows legal teams to focus on strategic analysis rather than laborious page-by-page review, leading to faster case evaluation and more consistent analysis.

Beyond mere summarisation, AI can assist in identifying crucial elements for establishing **breach of duty and causation**. By training on large datasets, AI can help benchmark care standards in specific clinical situations and flag deviations from expected norms, thereby highlighting potential breaches. It can also perform hindsight analysis on patient records to reveal overlooked signs and assist in risk modelling to estimate how a delay or error might have increased the likelihood of harm. While AI cannot replace expert testimony, it can strengthen case preparation and expert analysis by providing a more robust evidential foundation. Furthermore, AI can aid in **quantum assessment** by speeding up background research and comparing the current case to similar past cases, helping solicitors assess prospects and strategy more quickly and cost-effectively.

However, the integration of AI introduces significant **challenges and limitations**. A primary concern revolves around **liability** when AI systems contribute to medical errors. Current government guidelines suggest that NHS organisations may still be liable for claims arising from AI use, as doctors retain a duty to critically assess AI guidance. The traditional position in clinical negligence has been clear: if a patient suffers avoidable harm due to a clinician's negligence, the clinician is liable. However, the increasing reliance on AI complicates this, raising questions about whether AI firms and technology companies should also be held accountable. The Medical Protection Society has warned that doctors could become the "liability sink" for AI mistakes unless the law is reformed, advocating for AI tools to be reclassified as products under the Consumer Protection Act 1987.

**Ethical considerations** are also paramount. AI systems are susceptible to **bias** if trained on unrepresentative or historically biased data, which can perpetuate inequalities and undermine fairness, a foundational principle in law. The "black box" problem, where AI's decision-making processes are not fully transparent, poses a challenge to the legal requirement for precision and explainability. **Data privacy** is another critical area, requiring strict adherence to the UK General Data Protection Regulation (UK GDPR) and the Data Protection Act 2018, especially when handling sensitive client and medical information. Solicitors must ensure secure data storage, encryption, and rigorous access controls.

Crucially, the SRA maintains that using AI tools does not dilute or transfer professional responsibility. Solicitors remain personally responsible for all work produced, regardless of AI involvement, and must verify AI outputs. The UK Jurisdiction Taskforce (UKJT) has even suggested that lawyers *could* be found negligent for *failing* to use AI where it would be reasonable to do so, or for failing to exercise reasonable care and skill in its use, such as neglecting proper due diligence on AI systems or failing to explain AI usage to clients. This underscores the evolving duty of competence in an AI-driven legal landscape.

The integration of AI into clinical negligence and personal injury claims presents a transformative opportunity for legal practitioners in Great Britain. By automating time-consuming tasks like medical record review and enhancing the analysis of complex factual scenarios, AI tools can significantly improve efficiency, accuracy, and ultimately, client service. Firms embracing this technology are likely to gain a competitive edge, allowing lawyers to dedicate more time to strategic thinking, negotiation, and client care.

However, the path forward requires careful navigation. Practitioners must remain acutely aware of the evolving legal and ethical landscape, particularly concerning liability for AI-generated errors and the stringent requirements of data protection. The SRA's stance is clear: AI is a tool, and human oversight, professional responsibility, and critical verification of AI outputs remain indispensable. As AI continues to advance, the legal profession must adapt, not just in adopting new technologies, but in developing robust internal policies, ensuring continuous professional development, and advocating for clearer regulatory frameworks that address the unique challenges posed by AI in sensitive areas like clinical negligence. The future of these claims will undoubtedly be shaped by AI, but human judgment, ethics, and accountability will remain at its core.