AI Hallucination Risk refers to large language models confidently generating false information, citations to nonexistent sources, or fabricated details that appear plausible but are incorrect. This phenomenon occurs because models predict probable text sequences rather than retrieving verified facts. A legal brief citing fictitious court cases generated by ChatGPT exemplifies this risk, resulting in sanctions for the attorney. Organizations deploying generative AI must implement human review, fact-checking processes, and appropriate use case restrictions. The risk is particularly acute in high-stakes domains like healthcare, legal, or financial advice where incorrect information causes significant harm. Hybrid approaches combining retrieval-augmented generation with verified knowledge bases help mitigate hallucination risks.