The 5 stages of translation quality maturity + tips for maintaining quality in the AI era

First thing's first: Where does your quality program stand?

Maintaining quality in the era of AI translation

AI-powered translation has made it easier to produce more content in more languages than ever before. Today's businesses are localizing across multiple channels in near real time. Translation projects that once took weeks can be completed in just a few minutes with the click of a button.

But just because a translation happens fast doesn't necessarily mean it's accurate. Many localization teams are relying on artificial intelligence (AI) translations with little to no quality assurance. That's where linguistic quality assurance (LQA) programs come in. LQA is the process of monitoring translations to ensure they meet quality standards for linguistic accuracy, consistency, usability, and cultural nuances.

Up until recently, LQA usually required a team of linguistic experts to manually review translations. While this method works well for smaller volumes, human-only LQA workflows can only get you so far. They simply can't keep up as volume increases. Organizations that don't (or won't) adopt AI-driven LQA risk falling behind. On the flip side, organizations that invest in scalable, data-driven quality systems are strongly positioned to expand globally — without sacrificing speed or quality.

That's why Smartling launched LQA Agent, an AI-powered translation quality monitoring tool. It automatically evaluates translation quality using the multidimensional quality metrics (MQM) framework, scoring translated strings and generating an overall quality score to track trends over time. LQA Agent has three operating modes ranging from fully autonomous to AI-assisted human evaluation, so you can run the mode that works best for your translation quality program's maturity level.

The five translation quality maturity levels

Not sure how your LQA is performing or what stage you're in? Every organization starts somewhere. Whether you're just beginning to dabble in AI translation or you've been localizing for years, take our LQA Maturity Quiz to see where your organization falls on the scale — and then read on for tangible steps on how you can level up.

We developed a translation quality maturity scale to help you determine if your AI translation quality is at risk — and understand what it takes to move from one stage to the next.

1. Just Getting Started

You're still early in your LQA journey. You probably have a high-level idea of what good translations should look like, but there's no shared error framework, no consistent way to measure translation quality, and no real LQA process in place.

This means you don't have a consistent way to catch problems before they go out the door. Your quality is reactive, and often, invisible. Problems tend to find you, not the other way around. In most cases, you're only aware of an issue if a customer flags it or a stakeholder catches it late in review.

The good news is that since you're still early in the process, you have the opportunity to build a strong foundation right from the start. At this stage, focus on establishing a basic set of quality dimensions around accuracy, fluency, terminology, and tone. From here, you can add tools like the Smartling LQA Agent so you don't have to build everything from scratch.

Where to start

• Assign ownership: Without clear ownership, translation quality belongs to everyone — and no one. Assigning a person or a team signals that translation quality is a priority.
• Spot-review content: You don't need to review everything, but you should start doing structured sampling on your most high-stakes or high-visibility content.
• Document errors: Start recording errors as you find them so you can track trends over time.

2. Emerging Capability

You have some important pieces in place, but you still have some major gaps, too. You've started reviewing key content and you may have some translation quality reporting in place. The process is there, it's just not consistent — yet.

This is the stage where many organizations tend to get stuck. Manual LQA used to be manageable, but as the AI output increases, your review process can't scale.

Where to focus

• Expand LQA coverage: Now that you have your most important content covered, it's time to review the rest. A structured sampling approach for all content types will give you a much broader idea of performance.
• Establish a roadmap: Think about how your LQA program will scale over time. Creating a clear, structured roadmap helps keep you aligned on next steps.
• Shorten the feedback loop: AI-powered LQA like the Smartling LQA Agent gives you instantaneous quality scores, including Pass/Fail grading, so you can improve reporting and take action faster.

3. Operational

You're in a solid place. You've already established a structured review process, defined frameworks, and developed some quality dashboards. LQA is part of your workflow — you just need more efficiency and consistency.

While LQA covers the majority of your content, you still have trouble keeping up with volume spikes and fast-paced reporting. Taking translation quality further is next to impossible with human translators alone. It requires automation. This is where a solution like Smartling's LQA Agent closes the gaps.

Where to push next

• Automate scoring: Using tools like Smartling's LQA Agent to automatically evaluate translation quality using MQM takes the burden off human reviewers.
• Monitor continuously: Periodic reports make your LQA workflow reactive. Shift from static reporting to continuous quality monitoring. With live quality dashboards, you can spot and act on quality trends before they become an issue.

4. High Performing

You're in the mature translation quality stage. You're established — with structured LQA with a full MQM framework, quality KPIs, and real-time, scalable coverage. You have a strong foundation, but there's always room to improve. From here, targeted optimizations in efficiency can take you from High Performing to Optimized.

Getting to best in class

• Move to full AI LQA: Smartling's LQA Agent automates LQA so you can keep up with high AI translation volume. With broad coverage and instant scoring on every job, it gives your team real-time visibility into quality so you can focus on improving outcomes instead of addressing issues.
• Leverage your data: Now that you've set up continuous monitoring, it's time to use your translation quality data to drive smarter decisions. With LQA Agent, you can identify patterns and gain new insights to sharpen performance over time.

5. Optimized

You're running best-in-class LQA (but you probably already knew that). You have a quality translation process that scales with your output and basically runs itself. For your organization, multilingual content quality isn't a risk or a bottleneck, it's a competitive advantage.

Now it's all about staying ahead. AI translation is constantly evolving, so maintaining your edge is going to take intentional investment and ongoing refinement.

Continuous improvement

• Stay calibrated: Even mature programs can drift. As AI translation models, content types, and market expectations evolve, it's important to periodically audit and recalibrate your established LQA framework.

An agent for change

How do you scale without sacrificing quality? By expanding your existing capabilities. With AI-powered translation and Smartling's new LQA Agent, human judgement isn't going away — but it is getting more leverage.

About Smartling's LQA Agent

AI translation is scaling fast. Smartling's intelligent LQA Agent scales with it — delivering human-level evaluation accuracy in minutes, not weeks. Learn more about the LQA Agent here.