AI workflows outperform human translators in China localization study

VERA Brief

AI-generated. Grounded in the article and its cited sources.

A recent study in China found that AI workflows produced better translations than human translators for four out of six content types. The research suggests that selecting the appropriate AI model is more important than human post-editing for localization.

Key facts

• A benchmark study in China involved 774 outputs.
• AI workflows outperformed human translators in four of six tested content types.
• The study suggests that AI model selection may be more critical than post-editing in localization.
• Performance varied across different content categories.
• AI systems have the potential to accurately represent content across languages.