AI Hallucination Liability

AI hallucination liability is the third-party legal exposure a deployer faces when a generative AI system produces a false, fabricated, or unsupported output that a user, a customer, or another party relies on to their financial detriment. An AI hallucination is the underlying failure mode: a confidently-stated fact that is wrong, a citation to a source that does not exist, a piece of code that does not work, a fabricated product description, or a recommendation built on premises that are not true. Hallucinations are a known and persistent behavior of large language models and other generative systems. The deployer is the enterprise that put the AI into production for the user who relied on the output.

The liability theory is straightforward: the deployer made a representation to the user (through the AI output) that turned out to be false, the user reasonably relied on it, and the user suffered loss as a result. Two cases anchor the precedent set. Mata v. Avianca (Southern District of New York, 2023) sanctioned two attorneys who filed a brief with fabricated case citations produced by ChatGPT, establishing that AI hallucinations carry direct legal consequences for the professional who relied on them. Air Canada (2024) was ordered by a British Columbia tribunal to honor a bereavement fare refund policy its customer service chatbot had invented, on the holding that the airline is responsible for what its chatbot tells customers, disclaimer notwithstanding. Other claim shapes follow the same pattern: a customer-facing chatbot that misstates the terms of a sale, an AI triage system that misroutes a critical request, or an AI-generated marketing claim that turns out to be defamatory or infringing can all produce a third-party claim against the enterprise that deployed the system.

The financial scale of the exposure grows with deployment. A hallucination in a one-off customer chat is a small ticket; the same wrong answer produced for thousands of customers in production compounds quickly. Aggregated or class-scale claims on hallucination-driven harm are among the more closely watched near-term liability scenarios for enterprise AI deployers in 2025 and 2026. The exposure also does not fit cleanly inside the older liability forms. Commercial General Liability, Cyber, and Tech E&O wordings either exclude generative AI exposure or were not built to answer it, and Verisk and ISO have filed new general-liability exclusions for generative AI (CG 40 47 and CG 40 48, plus the products and completed operations form CG 35 08) attaching at U.S. renewals from January 1, 2026. Without affirmative coverage, the deployer's loss is uninsured.

Insurance for hallucination liability falls under Generative AI Liability policies, typically within the Generative AI Errors insuring agreement, with adjacent response under IP Infringement and Personal Injury, and Unauthorized Data Disclosure agreements where the hallucinated output infringes content or leaks protected information. Hallucination liability is not itself a separate insurance product; it is the practical name for the kind of claim a Generative AI Liability policy is built to answer.