A fluent-looking translated image can still contain a wrong product term, malformed glyph or altered visual detail. Human review should separate language approval from design and factual approval instead of relying on a quick visual impression.
What is human review for an AI-translated image?
It is a documented comparison of the source and localized result. The reviewer confirms meaning and natural language, while the content owner checks products, objects, claims and destination requirements.
Who should review the result?
Use a proficient target-language reviewer who understands the audience and subject matter. Add legal, medical, safety or regulatory specialists when the asset contains high-impact claims; AI output alone is not approval.
How should the review work?
- Provide the untouched source, target audience and approved terminology.
- Read every translated line for meaning, tone, names, numbers and units.
- Inspect glyphs, direction, line breaks, hierarchy and readable size.
- Compare products, faces, logos, UI controls, framing and dimensions.
- Record corrections and regenerate or return to the layered source when needed.
How is human review different from Quality mode?
Quality mode gives a complex image a higher-detail processing path. A reviewer evaluates the actual output from either mode and can catch errors a processing choice cannot certify. Neither mode guarantees linguistic correctness, exact typography or unchanged pixels.
What should you do next?
Generate one authorized image with Translate Text in Image, share source and result side by side, and use the broader translation quality checklist to document approval.