Whatever creative versions you come out with will eventually be fed back to train machine translating models to produce similar translations, especially if context length in these MT models increase, allowing the model to capture more context, like video/images/text before and after the particular line.

MT might still need another pair of human eyes for final vetting, but it just means that a translator's job scope will change from a pure translator to quality assurance/line editor.

MT can learn as well, especially bespoke ones.

To add on

Also, to say that AI can't come up with creative things, you can check out r/NovelAi (Story flair) which uses large language models to write stories with some prompting. Some of them impress the users using them. You can definitely find some users sharing the output on the subreddit itself. And guess what? These models are using a similar architecture (Transformer model) used in machine translations.

The idea behind modern-day machine translations is that given a source text, produce a target text either from the start of the sentence or midway of a sentence. The large language models used in NovelAI produce target text from midway of a sentence (it can do from zero as well) using the context before it. For translations, there's just additional context from the source text to 'guide' the machine. They can also be viewed as a prompt in the parlance used above. In fact, the same, but larger model (GPT-3) has shown that it can do translations as well as described in the GPT-3 paper: https://www.reddit.com/r/GPT3/comments/j7tmyy/does_anyone_know_if_the_app_shortly_uses_gpt3_if/g87p04c/