The 5 things a professional translator really needs from translation AI

Key Takeaways

• Professionals need AI that delivers near-instant translations without complex prompting or manual rework.
• Accuracy must always outrank fluency; sounding natural can’t come at the cost of changing the original meaning.
• Enterprise-ready translation AI must guarantee strict data privacy, security and protection from misuse or prompt injection risks.
• Deep integrations with TMS, CAT tools, CMSs and terminology databases turn fragmented workflows into a connected, efficient ecosystem.
• Customization features like glossaries, style rules and brand voice controls make translations consistent, on-brand and business-specific.
• The best AI platforms don’t just translate text; they transform your workflows so you can focus on high-value tasks.

It’s been a busy couple of weeks for anyone interested in AI for translation, with some new interfaces and models launching from the likes of ChatGPT and Google. As a localization expert, I’ve seen my social media feeds filling up with users and reviewers racing to compare them. 

As always, there’s a lot of urgency to declare this option a game-changer, or that option a clear winner. As anyone who works in translation and localization can tell you, it’s never that straightforward.

At DeepL, we run a lot of blind tests with independent language experts, to check how we perform on quality. It won’t surprise you to hear that we’ve run a lot of these tests in the last week. And it won’t surprise you to hear me say that DeepL came out top unanimously across the languages we tested.

Our models perform better on accuracy, sounding natural and grasping the idioms of local language, with translations that felt right straightaway. That’s reassuring for our AI research teams of course, but it’s not why I’m writing this post. After all, you’d expect me to tell you that, wouldn’t you?

Beyond the hype: what matters in translation AI at scale 

As a professional translator, a more important question to ask is: which features and aspects of quality really matter? When it comes to translation for business, at scale, what do you need an AI translator to be the best at?

I took some time to distill my thoughts on this, and I came up with five essential elements that I believe define a truly exceptional AI translator. It’s a list that’s shaped not by the fact that I work at DeepL, but the fact that I work in localization. 

Yes, there’s probably some unconscious bias at work, but I think that other people working in my profession will recognize these criteria and agree with them.

1. Speed: Real-time translation that keeps up with professional workflows

Let's cut to the chase: nobody has time to wait. In an era where we expect instant results, latency isn't just an inconvenience, it's a total dealbreaker. A professional-grade AI translator should deliver results in fractions of a second, keeping pace with your workflow rather than hindering it.

A key part of this requirement is that the quality of the initial translation needs to measure up to your requirements, without extensive input from you. If I have to write complex prompts to specify what type of translation I need, or spend time asking an AI to adjust it, I’m adding delays to my workflow and creating a process that doesn’t scale.

"DeepL users reported a 90% reduction in internal document translation time."

2. Accuracy and fluency: Translation quality that never sacrifices meaning

Quality is the holy grail of translation, yet it's so difficult to pin down. There's no universal definition that works across all content types and use cases. As a professional translator, I focus on two key pillars: accuracy and fluency. They’re both important, but it’s also important that an AI translator grasps how they need to work together.

I want a translator that leverages specialized language models for the best possible accuracy and precision in translation. I also want a translator that intelligently recognizes the genre and context of the source material and adapts to this context automatically, without my having to prompt it to specify what I want. 

An AI translator that does this preserves the original's style and tone while ensuring the target language reads naturally and idiomatically, and it can do this without me getting involved. 

Finally, I want a translator that always understands the relationship between these two pillars. When AI tries too hard to sound natural it can often result in hallucinations and translations that veer away from the meaning of the original. Fluency matters, but it can never come at the expense of accuracy.

3. Security: Enterprise-grade data privacy for translation AI

Data privacy isn't negotiable. In a world where information is currency, I need absolute assurance that my content won't be harvested to train models or exploited in any way. 

Rigorous standards on data privacy and security are an absolute first requirement for a professional-grade AI translator. I would expect clarity and transparency on how my data is handled, and kept secure. I need to keep an eye on other elements of security too. 

When translations use general-purpose, generative AI LLMs, for example, they become more vulnerable to prompt injection attacks that hackers can use to expose users’ sensitive information.

4. Integrations: An AI translator that fits your localization tech stack

As a translator, I'm orchestrating a symphony of interconnected tools: TMS, project management platforms, terminology databases, CMS tools. It’s not just the interface of each particular tool that matters to me. It’s also the ease with which those tools can be integrated with one another to create a workflow that works. 

An AI translator that plays well with others gives me fluidity, speeds up work and helps cut out errors and inconsistencies. When I need to cut and paste between different tools, everything gets fragmented.

5. Customization: Terminology, style and brand voice tailored to your business

The real killer app in translation AI is the ability to customize your translations so that they’re absolutely right for your business: your terminology, your style rules, your brand voice, your preferences on tone and language. 

Advanced customization features are the real game-changer. Within DeepL, they’ve enabled us to automate entire translation workflows so that tasks that once took weeks happen in minutes. When it comes to translation, one size fits none. You need predictable, consistent results that don’t require constant human review.

The verdict: The best translation AI transforms how professional translators work

The best AI translators don’t just translate. They transform how you work and ramp up your productivity.

They enable you to focus your expertise on high-value tasks rather than constant corrections and adjustments. They are customized to your business so that you don’t need to keep policing what they produce. Just as importantly, they are secure, accountable, and work with your tech stack, not apart from it. 

In a rapidly evolving field, these five elements are the real non-negotiables. They elevate what translators are capable of. And at the end of the day, that’s what the role of AI should be all about.

Put DeepL Language AI to the test

If any of this resonates, don’t just take my word for it. Feed your trickiest texts into DeepL. Turn on your terminology and style settings, and see how it behaves in your real workflow.

Compare it against your own five criteria: speed, accuracy, security, integrations and customization.

The “best” AI translator isn’t the loudest launch. It’s the one that actually makes your day easier.

Contact Sales to explore how DeepL AI tools fit your processes. And we now offer more than translation excellence; DeepL Agent automates routine tasks and workflows so your teams can stay focused on high-impact work.