Machine translation engines keep getting better; these days, their output is often indistinguishable from translations made by human professionals. However, if you still hesitate about using MT, there is something you can do to further improve the quality of existing engines and minimize the risk of embarrassment. Go to one of those MT providers that offer engine customization, that is, fine-tuning with your own data.
Additionally training engines on data that’s similar to what you’ll be translating almost invariably produces more impressive results than any stock (pre-trained by provider) MT engine will output. Where the stock engine looks at unfamiliar phrasing and terminology and makes a guess, the custom engine goes, “I’ve seen this before, I got this” and gives you relevant translations with the correct vocabulary.
If we are talking about the data that stock engines are being trained on, we should take several things into account. Even though these engines are being trained on massive amounts of data, this data is not very specific in the most cases, these texts are mostly general and simple. Also, such things as tone, overall politeness and appropriateness of the translation are not really being guaranteed.
Whereas custom engines are being trained on your own custom data, which protects you from some silly mistakes that we’ve all seen engines make. Also, you can evaluate the quality of custom models using different metrics (BLEU, LEPOR, TER, BERTScore and many more).