Is AI Translation Really as Good as It Looks?

AI has come a long way in translation. And we are very excited about it!

It delivers results that are fast, fluent, and grammatically polished. No typos. Smooth phrasing. It even “feels” human.

But here’s the question: Does it actually say what it's supposed to say?

We’ve all seen translations that look great on the surface—until you dig a little deeper. That’s where the real issues often hide: Inconsistent terminology, Misinterpreted phrases, Broken tags or structure, Subtle shifts in meaning that impact usability

These aren’t just minor flaws. They can affect the clarity, trustworthiness, and even the functionality of the final content. Fluency isn't the same as accuracy.

We’re now seeing a trend: companies that tried to manage AI translation in-house are coming back. They’ve realized that without the right linguistic expertise and quality assurance, AI alone doesn’t cut it. Managing multilingual content isn’t just about automation—it’s about getting it right.