The challenge of being a translator – and a client – in the age of AI

The arrival of Neural Machine Translation has turned the translation industry on its head. Time for companies to reap the opportunities; time for translators to find their place in this new landscape.

Text by Sara Grizzo


The challenge of being a translator – and a client – in the age of AI

Image: © cybrain/

Before Artificial Intelligence (AI) and Neural Machine Translation (NMT) materialized in the localization and translation world, the landscape of our industry was pretty straightforward. When it came to translating content written in language A into language B, two scenarios would open up:

In the first scenario, clients required spot-on translations that needed to be perfect in terms of terminology consistency, style adequacy, punctuation, grammar and spelling. In this case clients cooperated with professional linguists who relied on the different functions of CAT tools (translation memories, glossaries and QA options) in order to provide the necessary quality.

In the second scenario, clients chose to use machine translation (MT) – rule-based at first, followed by statistical engines in the early 2010s – for handling translation assignments that either involved highly standardized ...