Crawl, Walk, Run: A Practical Approach to AI Translation

Embracing AI in translation may sound promising. But figuring out how and where to begin can feel overwhelming. If your team is curious but unsure how to move forward, you’re not alone.

The good news? You don’t need to overhaul everything at once. There’s a clear path to easing in, building confidence, and seeing results without disrupting your current workflow just yet.

By taking a “crawl, walk, run” approach, you can start small, learn what works, and scale your AI translation efforts in a way that fits your goals and your team.

First, audit what’s slowing you down

Before you introduce anything new, it helps to get clear on what’s not working. If your current translation process is starting to feel sluggish or stretched thin, that may be your signal that it’s time to explore AI.

Here are a few common signs:

• Turnaround times are too slow: If content is sitting in the queue or missing deadlines, it may be time to rethink your approach.
• Costs are climbing: As your translation needs grow, human-only workflows can quickly become unsustainable.
• Your content backlog is becoming an issue: If untranslated content is piling up, your localization program may be holding your global strategy back.

Auditing your existing process is the first step toward identifying where AI can add the most value, whether that’s by accelerating delivery, reducing costs, or helping you scale without compromising quality.

Test the waters with low-stakes content

Once you’ve identified the areas where you need to boost efficiency, the next step is to experiment. Start small by testing AI on content that matters but isn’t high-risk. Using low-stakes content at first gives you a chance to see how AI performs in your environment without putting your brand voice or mission-critical messaging on the line.

Good candidates for early testing include:

• Help center articles
• Product FAQs
• Internal documentation
• Support content or user guides

Then, pause to assess performance. You’ll want to evaluate the quality of the output and how much human editing is required, as well as ease of use and any efficiency gains. Did the process save time or feel easier to manage? Compare the results to your current process. Were turnaround times faster? Did your content require fewer edits? This will help you evaluate whether you’re ready to go further.

Put guardrails in place with LQA

If you’re new to AI translation, language quality assurance (LQA) is your secret weapon. It’s the process of reviewing and refining translations to ensure they are accurate and meet your quality standards — and it’s especially valuable when AI is part of the workflow.

With human reviewers checking AI output early and often, you can spot issues fast, maintain quality, and gain confidence in how AI performs in your workflow.

It’s not just about quality control, either. The feedback from LQA helps train your models over time, making AI translation more accurate and more aligned with your brand voice.

For teams just starting out with AI, LQA isn’t just helpful — it’s how you build confidence and set yourself up for long-term success.

Ready to scale? Here’s the trick to smart growth

Once your team is seeing consistent results, the next step is to gradually increase AI coverage, starting with the types of content where it can deliver the most impact.

High-volume, low-visibility content is often a good place to start. Product descriptions, technical documentation, and support articles typically don’t require heavy creative input, but they can still demand significant time and resources. This is where AI can help you move faster while delivering accuracy.

Therabody, a wellness-focused technology company, partnered with Smartling to scale its localization program more efficiently. After introducing AI-powered human translation (AIHT) for technical content like their user manuals and packaging, they expanded AI use across more long-tail materials while continuing to rely on human translators for creative projects and final quality control. The result: a 60% reduction in translation costs and a 99.7% on-time delivery rate.

As you scale, continue to apply the translation mix strategically. AI isn’t there to replace human translators; it’s there to enhance your team’s capacity and help you focus resources where they matter most.

Still feeling cautious? Try MT first

Not quite ready to dive into fully AI-powered translation? That’s okay — machine translation (MT) is a solid first step.

MT is especially useful for long-tail content like help center articles, user guides, and internal resources. It’s low-risk, easy to scale, and can help you start clearing backlogs while maintaining budget. You’ll get a feel for what automation can handle and where human involvement still adds value.

Once you’re comfortable using MT, you can reassess. If the process is working, it may be time to explore AI-powered translation workflows that build on that foundation — with added intelligence, customization, and speed.

Take the first step toward AI translation with Smartling

Whether you’re exploring AI for the first time, testing a new workflow, or starting to scale, the most important thing is to take that first step. You don’t need to overhaul your program overnight. Start where it makes sense, build confidence along the way, and let the results guide your next move.

The payoff? Smartling customers increase translation speed by 50% and can translate 8x more content — all without sacrificing quality.

And you don’t have to figure it out alone. With the right partner, you can move forward with confidence and build a strategy that actually works for your team.

Want help identifying the right starting point for AI translation? Let’s talk. Book a meeting with Smartling today.