Using the unmonitored output of a LLM-translation service for your commercial content, outputting in languages you can't read, represents a big reduction in quality assurance and greatly increases the risk of brand embarrassment and possibly even product misrepresentation, while leaving you with no recourse to blame or shift liability.
> If I was a vendor whose business was at all centered around language or data ETL or anything that involves taking text and doing something with it, I would be absolutely terrified at someone writing a 20-line python script with a good system prompt that would make my entire business's reason for being evaporate.
The more likely future is that existing translation houses will increasingly turn to LLM-assistance to raise the efficiency and lower the skill threshold for their staff, who still deliver the actual key values of quality assurance and accountability. This will likely drive prices down and greatly reduce how many people are working as translators in these firms, but it's an opportunity for them, not a threat.
LLM's don't seem to be on track to be the foolproof end-user tools that the earyl hype promised. They don't let us magically do everything ourselves and (like crypto being imcompatible with necessary regulations), they don't offer all the other assurances that orgs need when they hire vendors. But they can very likely accelerate trained people in certain cases and still have an impact on industry through specialty vendors that build internal workflows around them.