A possible workflow would keep an untouched original, show the exact requested wording beside the candidate, and ask the user to check spelling plus nearby details before downloading. A separate caption could identify the result as an edited example when readers might otherwise treat it as an original record. I would avoid a default label implying that a realistic-looking result is verified evidence.

For context, AI Image Text Editor lets users edit screenshot wording in JPG, PNG or WebP images by selecting text and describing a replacement. The public homepage describes files up to 10 MB and up to eight selections in one task. New users can start with free credits; edits consume credits. Generated text and surrounding pixels still need review. This is a project-associated, AI-assisted discussion, not an independent benchmark or report of an implemented feature.

For a shop owner updating a date in a promotional graphic, a short before/after check may be enough. For a support tutorial, the reviewer may need to check whether the current interface actually uses that label. Sensitive information calls for a separate privacy process: visual text replacement should not be presented as secure redaction. Only authorized or synthetic example images should be used.

Would you put the change note in the editing screen, the download dialog, or both? How would you preserve that context when the image is forwarded without its surrounding page? I would appreciate examples of a low-friction review pattern that encourages clear disclosure without claiming that every output has been independently checked.