Scaling Quality Through
Human–AI Collaboration

H

ead of Quality Helen Corfield explains how Translated is addressing the growing challenges localization managers face, going beyond TMs and glossaries to safeguard accuracy, consistency, and brand voice.

What are the biggest quality challenges in localization today?

As Translated anticipated, the new wave of AI has unleashed latent demand for translation. For global brands, this means rising volumes and new content types, which put enormous pressure on quality standards. The challenge is no longer just producing more content faster, but ensuring that accuracy, consistency, and brand voice are preserved at scale. Translators are asked to absorb style guides, terminology bases, playbooks, and quality frameworks across multiple accounts, which creates cognitive overload and increases the risk of inconsistency. For localization teams, the real issue is not speed or cost alone, but maintaining a coherent standard of quality across a much more complex and accelerated process.

How does Translated use AI to redefine quality frameworks?

Most MT systems have only partially integrated translation memories and glossaries, and have entirely left out assets like style guides and instructions due to their complexity. Yet these materials are essential for upholding quality and brand voice. The challenge has been converting these assets from something only translators could use to a new format that works effectively with AI. Our QM team has worked closely with the research team at Lara, our latest translation AI, to transform quality assets into machine-readable prompts: lengthy style guides are flattened into clear rules focused on voice and purpose, generic rules already captured by memories are removed, and termbases are split into domain-specific sets to manage ambiguity. By converting style guides, instructions, and terminology into prompts, we make brand voice not only visible to the AI but also consistently enforceable at scale. From a quality management perspective, this approach ensures translators can trust Lara as a reliable partner that consistently upholds standards, delivering outputs that are brand-adapted and high-quality.

What are the benefits for translators, PMs, and global brands?

The most important benefit is consistently higher quality outcomes, together with reduced turnaround times by introducing AI across the process. By aligning Lara with professional translators, we ensure that brand voice, accuracy, and terminology are preserved even as volumes and content types expand. Translators immediately receive context-aware suggestions, which reduce cognitive load and allow them to focus on higher-level decisions as guardians of quality rather than repetitive editors. Project managers gain tools to apply style rules and client instructions systematically, acting as quality enablers who scale consistency across accounts. For global brands, this means that quality no longer erodes under pressure: audiences receive content that is accurate, culturally adapted, and consistent with brand voice, even at scale.

About Helen

Helen is Head of Quality Management at Translated and brings 12 years of experience in localization with a background in linguistics. For the past seven years, she has led quality programs for enterprise clients across human and machine translation, focusing on scalable, human-centric solutions. Her recent work centers on refining Quality Estimation models and integrating LLMs into quality workflows, pairing expert linguist review with model improvement. Helen is recognized for empowering translators to thrive alongside AI by enhancing training, optimizing the use of tools, and enhancing outcomes through continuous feedback and collaboration.