AI vs. TMS-based translation: advantages, limitations and what has proven itself in practice

Translation processes are absolutely critical for export-oriented companies. Linguistic adaptation to international target markets must not only be fast, but also very good, which makes technical support essential.

Two of the most prominent technologies in this area are AI translation and TMS-based translation. The former can be fully automated, while the latter is human-driven and based on a "learning" translation memory system (TMS). Both have strengths and weaknesses, which are discussed in more detail below.

An overview of the respective strengths:

Advantages and limitations of AI translation

AI is "quick and dirty"? That used to be the case. With the help of glossaries, fully automatic AI translation can be significantly improved - even if only up to a certain point. Many texts can be translated perfectly without further ado. But there's still no getting around a check.

As fast and efficient as a machine translation may be, it will still fail due to certain stumbling blocks: missing context, synonyms and homonyms, an unrecognizable number ("items" are how many?), etc.

Advantages and limitations of TMS-based translation

A translation memory makes translations better and better over time because all "known" translations are used to support new translation jobs. To get started, it makes sense to train the TMS, for example by specifying the most important terms. Many companies shy away from this effort.

The translations suggested by the TMS basically struggle with the same stumbling blocks as an AI, but you can use "guard rails" by making default settings in the TMS system. And last but not least, the translation is semi-automatic, with continuous human control. You have to buy this qualitative advantage: with more time and more money.

Either AI or TMS? Why not both?

The idea is obvious: why not combine the advantages of both worlds? In fact, AI has long since been integrated into professional TMS systems. If the TMS cannot contribute anything useful, an AI service connected via API steps in and makes the best possible suggestion. Integrating AI into a TMS system is child's play - but it doesn't work the other way around. And this is also the biggest weakness of a pure AI translation: no translation memory! Texts that enter the AI translation process multiple times with identical content are translated from scratch each time, and this can result in differences.

Incidentally, crossbase has long supported both worlds. Read more about how our translation management with online translation is designed.

In practice: What has proven successful?

Both purely AI-driven translations and the AI/TMS combination make sense depending on the situation. However, I would no longer recommend a TMS without AI. Why would I?

Ultimately, you have to decide in which situations AI translations are good enough to either keep control to a minimum or even reduce it to zero. If you look at the multilingual texts in your company, you will find both sensitive and non-critical texts. I wouldn't blindly trust any AI with an offer or contract - ever. It's a completely different story with "decorative texts" for marketing.