Hallucination Liability

Hallucination liability hit the mainstream after high-profile legal defeats, like the landmark Moffatt v. Air Canada ruling. In that case, an airline chatbot confidently invented a retroactive refund policy, and when the consumer sued to enforce it, the airline remarkably argued the chatbot was a “separate legal entity” responsible for its own actions. The courts rejected that outright, cementing the precedent that automated tools are an extension of your brand—if your bot signs a bad contract or gives negligent advice, you own it. For B2B startups and enterprise AI vendors, this creates a massive financial exposure. If a customer integrates your AI agent and it hallucinates bad medical advice, inaccurate financial forecasting, or flawed structural engineering specs, you aren’t just looking at a customer churn problem; you are looking at a catastrophic professional liability lawsuit.
This exposure may refer to a critical gap in traditional insurance portfolios. Many founders assume their standard Cyber Liability or Technology Errors and Omissions (E&O) policy will automatically cover these incidents. However, standard E&O language was written for software that either works or crashes—not software that creatively invents false data while pretending everything is normal. Underwriters are rapidly tightening policies, adding specific “generative AI” exclusions, or demanding proof of rigorous guardrails, retrieval-augmented generation (RAG) validation, and human-in-the-loop oversight before extending coverage. Ultimately, hallucination liability means that “the algorithm did it” is no longer a viable legal defense, forcing startups to treat AI outputs with the exact same risk management rigor as human-generated advice.