Qanooni AI: Legal AI vendors must prove how they prevent hallucinated citations

The proliferation of Artificial Intelligence (AI) in legal practice has introduced unprecedented efficiencies but also significant risks, particularly the phenomenon of "hallucinated" citations and fabricated legal analysis. This article examines the increasing pressure on legal AI vendors to demonstrate robust mechanisms for preventing such errors, focusing on the UK regulatory landscape. Recent High Court judgments, such as *Ayinde v London Borough of Haringey* and *Re an Office-Holder; Cork v Smith*, underscore that legal professionals bear ultimate responsibility for the accuracy of their submissions, regardless of AI assistance. The article highlights the imperative for vendors to provide transparent, verifiable solutions and for practitioners to exercise rigorous human oversight to mitigate professional negligence risks and uphold the integrity of the justice system.

The rapid integration of Artificial Intelligence (AI) into legal workflows is transforming the delivery of legal services, promising enhanced efficiency and access to justice. However, this technological advancement is not without its perils. A critical concern that has emerged is the propensity of generative AI models to "hallucinate" – to confidently present fabricated case law, non-existent statutory provisions, or unsupported legal analysis as fact. This phenomenon poses a direct threat to the foundational principles of legal practice, including accuracy, integrity, and the proper administration of justice.

The legal profession, particularly in the UK, is grappling with the implications of these AI-generated errors. Law firms are now demanding that legal AI suppliers provide concrete proof of how their systems actively reduce the risk of such hallucinations. This article will delve into the regulatory and professional duties that underpin this demand, explore recent judicial pronouncements on the matter, and outline the critical need for transparency and verifiable safeguards from AI vendors to ensure the responsible and ethical adoption of legal AI.

The UK's approach to AI regulation is currently principles-based and sector-specific, rather than relying on a single overarching AI law like the EU AI Act. Instead, existing regulatory bodies, primarily the Solicitors Regulation Authority (SRA) and the Bar Standards Board (BSB), interpret and apply their established professional standards to the use of AI. Both regulators have issued guidance emphasising that core professional duties remain paramount, irrespective of the technology employed.

For solicitors, the SRA Principles (2019 Standards and Regulations) mandate acting in a way that upholds the rule of law and the proper administration of justice, maintaining public trust, acting with honesty and integrity, and serving clients' best interests. Similarly, barristers are bound by the BSB Handbook's Core Duties, which include acting with honesty and integrity (CD3), not misleading the court (rC3), and providing a competent standard of work (CD7). These duties inherently require legal professionals to ensure the accuracy and veracity of all information presented to clients or courts. The emergence of AI hallucination directly challenges these fundamental obligations, creating a clear nexus between technological risk and professional liability.

The risk of AI hallucination has moved from theoretical concern to tangible judicial scrutiny. Two prominent UK High Court decisions, *Ayinde v London Borough of Haringey* [2025] EWHC 1383 (Admin) and *Re an Office-Holder; Cork v Smith* [2026] EWHC 1199 (Ch), serve as stark warnings. In *Ayinde*, a barrister submitted grounds for judicial review containing fabricated case citations and inaccurate statutory provisions, which were found to be products of unverified generative AI outputs. The High Court unequivocally stated that lawyers remain responsible for material placed before the court, irrespective of AI involvement, and that uncritical reliance on AI-generated content could amount to gross negligence.

Similarly, in *Cork v Smith*, a junior associate relied on an AI platform that hallucinated a non-existent Insolvency Rule. Despite the AI's own warnings to verify, the information was not checked and was approved by senior associates and a partner before being submitted to the court. The judge publicly admonished the firm, underscoring that legal professionals cannot outsource legal research or reasoning to AI and remain ultimately responsible for their work. These cases reinforce the long-standing professional negligence principles derived from *Bolam v Friern Hospital Management Committee* [1957] 1 WLR 582 and *Bolitho v City & Hackney Health Authority* [1998] AC 232, which dictate that a professional's conduct must align with a responsible and logically defensible body of professional opinion.

In response to these escalating risks, the focus has shifted to the accountability of AI vendors. Firms are increasingly demanding transparency regarding how AI systems are trained, how they generate outputs, and crucially, how they prevent or flag hallucinations. Companies like Qanooni, for instance, promote their systems as being "wired directly into more than 5,000 legal authority sources" and citing "every one, instead of trusting the language model to remember the law," thereby aiming to prevent invented cases. This direct grounding in verifiable sources, coupled with clear audit trails of AI prompts and outputs, is becoming a critical differentiator. The BSB's May 2026 guidance explicitly covers "documented verification procedures" as a requirement for barristers and chambers. The SRA also highlights the importance of due diligence on AI vendors and ensuring that client confidentiality and data protection obligations are met.

The absence of specific AI-centric legislation in the UK places a greater burden on legal professionals to exercise due diligence and on AI vendors to build trustworthy systems. While the UK government has adopted a pro-innovation, principles-based approach, the existing regulatory frameworks and common law principles of professional negligence are proving robust enough to address the liabilities arising from AI misuse. The emphasis is firmly on human oversight, verification, and the inability to delegate professional responsibility to a machine.

The challenge of AI hallucination in legal research and drafting is a critical issue demanding immediate and sustained attention from both legal practitioners and technology providers. The UK's regulatory bodies and courts have made it unequivocally clear that the ultimate responsibility for accuracy and integrity rests with the human legal professional. The cases of *Ayinde* and *Cork v Smith* serve as potent reminders that unverified AI outputs can lead to severe professional consequences, including findings of professional negligence and disciplinary action.

For practising attorneys, the implications are clear: AI tools must be treated as assistants, not substitutes for professional judgment. Rigorous verification of all AI-generated legal content, especially citations and substantive legal analysis, is non-negotiable. Firms must implement robust internal policies, provide adequate training, and conduct thorough due diligence on AI vendors, scrutinising their methods for preventing hallucinations and ensuring data security. For legal AI vendors, the market demand is now for demonstrable proof of reliability and transparency. Those who can clearly articulate and prove how their systems prevent fabricated citations and provide verifiable audit trails will gain a significant competitive advantage and foster the trust essential for widespread adoption. The future of legal AI hinges not just on its capabilities, but on its trustworthiness and accountability.