How to use generative AI for translation as a business

Generative AI is an AI system that generates translations, rewrites, adaptations… basically what you need for localization. Its outputs feel natural and context-aware. This technology does feel different from the traditional machine translation (not that you should ditch other methods of translation). Bonus: it can also generate multiple alternatives for the same text, so you can pick the option that’s most suitable.

If you’re a business, you’ll appreciate how generative AI for translation can speed up the process and improve consistency. And if you’re working with a translation management system like POEditor, you’re probably already wondering how to actually use AI in your day-to-day.

How to integrate generative AI into your workflow

If you already use a translation management system like POEditor, it’s easy to integrate generative AI into your workflow. You start by feeding your source content to the AI to clean up or simplify ambiguous strings. Generative AI can be used to clarify wording, normalize terminology, and ensure instructions are clear before translation even begins. This step alone can save hours of manual editing down the line.

Next, you can generate AI-powered drafts. They are a starting point for human translators or reviewers, because you still need humans to check on the output. Generative AI understands context, tone, and brand voice, so the drafts are usually closer to final quality than traditional machine translation. Now, your team can review, edit, and approve the content.

Let’s recap:

1. Feed your source content into the AI.
2. Use it to clean up text, clarify ambiguities.
3. Generate drafts.
4. Review the output with human linguists.
5. Final approval.

But did you know that generative AI can help with other tasks beyond translation? You can use it for quality assurance, spotting inconsistencies, missing placeholders, or segments that don’t match your style guide. Some even use it to create localization briefs, glossaries, and supporting documentation automatically. All in all, generative AI can handle many repetitive or time-consuming tasks in localization.

How to make the most of generative AI for translation

Now it’s time to learn how to get the most out of AI. It can be a new member of your team, a fast and talented one, but also unpredictable. So let’s look over some best practices to help you use GenAI effectively.

Firstly, whatever you do, keep humans in the loop. Seriously, you still need them. Generative AI is great at producing polished and natural-sounding text, but it can also occasionally drift into overconfidence or invent details (you’ve probably heard the term “hallucination”). You need a human to check its outputs and verify that the information is actually true.

And the best results come from detailed instructions, because that’s what generative AI responds best to. You need to be explicit and give examples. Don’t be vague in your prompt! Generative AI is great at improvisation… that’s not what you want in this case. Pull out your glossaries, translation memories, and style guides, because this is when they matter more than ever.

It’s best to start small and learn as you go with AI. In fact, you shouldn’t. Use it on a specific part of your workflow like marketing copy for a region where you have strong in-house reviewers. It gives you space to learn how the system works, where it delivers and where it struggles. Once you understand it, you’ll see that scaling becomes easier.

Know the risks

I mentioned earlier about AI hallucinations. This is probably the biggest risk when it comes to generative AI, which sometimes fails by being convincingly wrong. A hallucination is basically a response that contains false or misleading information presented as fact. Because LLMs are essentially sophisticated “word predictors,” they prioritize flow and grammar over factual truth.

Then there’s the privacy aspect. If your team is copy-pasting sensitive strings or internal documents into a free, public version of an AI tool, that data might be used to train future models. Your confidential information could theoretically pop up as a suggestion for a competitor using the same AI tool months later.

Unlike humans, AI doesn’t know culture; it just reflects the data it was fed. If that data contains gender stereotypes or Western-centric biases, the AI will repeat them. It’s very important to provide clear personas in your prompts and use human reviewers to perform a “vibe check” for cultural sensitivity.

Using generative AI with POEditor

POEditor is integrated with Claude, Gemini, and OpenAI, some of the most well-known examples of generative AI in use today. Since we support multiple LLM providers, you can choose the model that best fits your content type or business needs. Alternatively, you can integrate your custom AI model.

With these options, you can easily bring AI-assisted translation and rewriting (yes, you can ask for rewrites) directly into your localization process. It can be your everyday tool that works alongside your translators and reviewers.

You can generate AI-powered translations directly inside your projects. Whether you’re localizing product UI, marketing content, or documentation, AI suggestions are available in a structured environment where they can be reviewed, edited, and approved just like any other translation.

Wrapping up

AI is still evolving; it’s not perfect and you shouldn’t treat it as such. Of course it’s a great idea to use generative AI for translation, but it doesn’t always do a fantastic job so you need to keep a human eye on it. When you put humans and AI together, you get the best of both worlds: speed and scale + accuracy and authenticity.