Faulty AI translations: how to deal with quality defects

DeepL or ChatGPT promise fast translations at the touch of a button – but what if the result is disappointing? Many companies are facing precisely this challenge: although the translation by artificial intelligence sounds fluent, a closer look reveals errors in the technical terminology and inaccuracies in the content. We explain how to deal with faulty AI translations and when professional translation processes are essential.

Faulty AI translations: how to deal with quality defects2025-10-06T11:59:46+02:00

AI translation needs expertise: how translators ensure quality today

Professional translation is in a state of flux. Machine translation and AI are changing the requirements. For companies that rely on professional translation, this poses the question: what role do translators play in this new world? The answer may come as a surprise: their importance is growing – only the tasks they do are changing fundamentally.

AI translation needs expertise: how translators ensure quality today2025-10-06T11:19:18+02:00

Use AI translation correctly: five steps to measurable savings

Many companies are already relying on machine or AI-generated translation solutions to speed up processes and reduce costs. In practice, however, the savings are often not as large as expected. Just because AI is being used does not mean that optimal results or significant cost reductions are guaranteed. Realising the full potential requires a well thought-out strategy, targeted adjustments at various points in the translation process and human interventions in exactly the right places. With our five-step plan, we show you how you can sustainably and noticeably reduce your translation costs with AI support, without compromising on quality.

Use AI translation correctly: five steps to measurable savings2025-07-17T15:54:18+02:00

The future of AI in translation: MTPE and LLMs in the spotlight

The rapid change brought about by the integration of artificial intelligence is affecting almost all industries and is also revolutionising the translation industry. The industry is used to drastic changes, as the breakthrough of neural machine translation (MT) caused disruption just a few years ago. Since then, MTPE – the combination of MT and post-editing (PE) – has established itself as a method for bringing machine translations to a professional level. The emergence of Generative Artificial Intelligence (GenAI) in the form of Large Language Models (LLMs) such as GPT, Mistral and Llama again begs the question of whether and how translation processes will continue to evolve and change.

The future of AI in translation: MTPE and LLMs in the spotlight2025-05-28T12:39:23+02:00
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