A failure mode of large generative models (text, image, audio) where the system confidently invents details - facts, quotes, references - that sound coherent yet are false. Hallucinations arise from the model’s probabilistic sampling and lack of grounding. Governance approaches include grounding on trusted knowledge sources, retrieval-augmented generation, calibrated confidence scores, and post-generation fact-checking layers to catch fabrications before release.