Directly using large language models like ChatGPT for authorization enforcement in distributed systems is strongly discouraged due to inherent non-determinism, potential for hallucinations, and critical security risks. Instead, best practices dictate leveraging ChatGPT solely as a development aid for tasks such as generating initial policy drafts, translating high-level requirements into formal authorization languages like Rego, or explaining complex rule sets. Any LLM-generated content must undergo rigorous human review, validation, and extensive testing by security experts before deployment. The actual authorization logic should reside within deterministic, purpose-built authorization engines designed for reliability, auditability, and precise control. ChatGPT can further assist in identifying potential policy gaps or improving documentation clarity, but its role must always be that of a human-supervised assistant. Ultimately, integrate LLMs to augment human expertise in authorization design and analysis, never to replace critical security decision-making directly. More details: https://www.impdesigns.com/?URL=https://abcname.com.ua/