AI Translation: Revolution or Dead End?

AI translations, often referred to as neural machine translation (NMT), are among the fastest-growing tools in the language services industry. They can translate massive volumes of text in just seconds, with output that appears comparable to human translators – at least at first glance.

The results can be surprisingly good, especially for common language pairs and straightforward content. But beware – behind the convenience and low price may lurk inaccuracies, inconsistent terminology, or lack of coherence. And that can lead to costly consequences for companies.

Advantages of AI Translation

Speed: Machine translation is nearly instant – ideal for large data volumes or tight deadlines.

Low costs: AI translation is much cheaper than human translation – especially for informal or internal content.

Easy scalability: Need to translate thousands of product descriptions into 10 languages? No problem for AI.

But Beware the Limitations

Inconsistency: NMT models often translate the same terms differently. In technical or brand-specific texts, this can be confusing.

Terminology issues: AI doesn’t work with approved glossaries and often invents creative but incorrect phrases.

Lack of context awareness: AI doesn’t know who the audience is, the purpose of the text, or the target group. The result can be inappropriate tone, unclear wording, or cultural blunders.

AI or CAT? When to Use Which?

CAT tools (Computer-Assisted Translation)  

rely on translation memories and glossaries built from previous human work. They’re ideal for companies that invest in consistent terminology and need uniformity across documents. The advantage is that the output is always reviewed by a human translator and/or proofreader.

AI translation (NMT)

works independently, without access to a company’s translation memory. It’s better suited for rough drafts, large volumes, or internal use. But when accuracy, tone, and brand consistency are key, AI alone won’t suffice – post-editing is needed, i.e. professional linguistic review of the AI output.

How to Use AI Translation Effectively

Always plan for proofreading. Even if the AI output is good, minimal language review is essential.

Define the purpose clearly. A text for an internal team is very different from one aimed at customers.

Save high-quality outputs. AI translations can still serve as a useful base for further work with CAT tools.

Conclusion: Technology Helps – but Human Input Makes the Difference

AI translation offers speed and savings, but also brings risks. If you need a text that’s not just grammatically correct but also clear, compelling, and accurate, human input is a must. The best strategy? Combine the best of both worlds: the speed of AI and the quality of professional translators.

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Marek Šauer | 11.07.2025

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