Generative AI produces new text, images or other outputs from learned patterns and the input it receives. The output may be useful, but its fluency or visual quality does not establish factual accuracy or suitability for a business decision.
Define the intended task and provide relevant, permitted context. Separate creative drafting from factual work that requires source checking. For example, a generated report narrative should use verified calculations rather than invent the data it describes.
Evaluate representative outputs for accuracy, relevance and harmful failures. Check citations and claims against their sources. Decide which results need human approval and which can be checked through deterministic rules before they enter another process.
Record the model and workflow configuration used for important outputs. Review data-handling terms and access controls before sending sensitive information. Adoption should be based on measured usefulness in a particular task rather than a general claim that generation is reliable.
Open Sources Used
This page uses open and institutional references as a frame; the final decision still belongs to the company record, threshold and owner.
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Reading adjacent decision areas keeps the topic from becoming an isolated note.