Structured outputs in Large Language Models (LLMs) refer to generating text in a well-defined format, such as tables, lists, or specific schema, rather than free-form prose. These outputs are useful for tasks requiring organization and precision, like generating reports, answering queries in structured formats (e.g., JSON or XML), or data extraction. By producing structured outputs, LLMs enhance their ability to automate complex workflows, integrate with databases, and assist in various industries like finance, healthcare, and law, where well-organized information is critical for decision-making and analysis.