AI turns translators into cultural experts

My professional localization journey began several years ago as machine translation and computer-assisted tools were transforming the industry. I remember vividly how thrilling and daunting it felt to see the first wave of technology roll into our world. I found myself stepping into the new role of a post-editor, exploring strange but exciting concepts like translation memory and fuzzy match.

These weren’t just buzzwords. They became part of the fabric of my work, revealing how human creativity could blend with technology to achieve results neither could accomplish alone.

As time went on, the pace of change only accelerated. Another technological surge arrived: AI. Seeing it enter our industry brought a mix of curiosity and unease. I often wondered with my colleagues what would happen to our craft and whether our careful, thoughtful work could ever be replaced by algorithms. The reality has been both more complex and more promising than I could have imagined.

Living and thriving with AI

AI is now an essential element of workflows in localization; in fact, at Centific, AI has become so essential that we refer to localization now as Multilingual AI, which integrates generative AI across the full spectrum of language work. This includes transcreation, machine translation quality estimation, automated post-editing, and AI-driven multimedia creation such as auto-captioning, voice-over, and subtitling.

AI’s ability to analyze text, highlight terminology, flag sensitive content, and detect possible errors has made quality checks more reliable. AI-generated translation offers a certain level of fluency that translators can reshape for a final and optimal translation. Still, human expertise remains necessary to shape translations for cultural, emotional, and contextual accuracy. Meaningful translation goes beyond accuracy; it conveys real intent and nuance in every scenario.

Recent innovations such as agentic translation rely on dedicated agents that specializes in elements like sentiment, terminology, culture, or tone. Agents collaborate, iteratively refining content so it is locally relevant and authentic for every audience.

The agentic approach not only manages language adaptation but also addresses value propositions and emotional resonance, allowing human experts to focus on refinement and creativity where it matters most.

AI as a partner in understanding culture

AI now plays a central role in Multilingual AI. It quickly identifies areas needing cultural sensitivity, analyzes terminology, and helps streamline routine quality checks. For instance, AI can flag phrases and references in source content that might not resonate with audiences in different markets. However, AI alone cannot reliably sense when an idiom carries unintended meaning, or when a slogan might come across as disrespectful or bland. This is where human expertise makes the difference. Translators creatively rework ideas by drawing on an understanding of local values, preferences, and humor to find alternatives that feel authentic and familiar.

Translators today go well beyond simple language conversion. The most effective localization draws on research into current social trends, consultation with local colleagues, and attention to emerging expressions.

For example, when adapting financial messaging for Asian markets, the translator may shift the focus from personal achievement—common in some cultures—to family prosperity and generational security, ensuring the text aligns with local cultural priorities and truly resonates with readers.

English does not use grammar to mark formality as widely as other languages do, relying more on the context and wording used, which the AI struggles to grasp. The Japanese language, in particular, presents a unique challenge due to its intricate system of honorifics and levels of formality that are deeply embedded in both language and culture.

To cite another example in my work: I’ve witnessed large language models translate “Find sales” (in a commercial context) as “Busca ofertas” in Spanish, switching the concept of “finding” (active, enthusiastic, reaching that one sale that is for you) with “searching” (which suggests a passive, possibly tedious and inconclusive action). In fact, the most suitable translation would be “Encuentra ofertas”, although “Busca ofertas” is a frequent automatic translation Spanish readers can find. A human is needed to manage AI. A human will understand the important nuance and correct the AI.

Agentic AI streamlines these transformations by analyzing target audience data, updating content in real time, and tailoring both tone and terminology to each platform. The result is translation that improves in scale and specificity, while human linguists remain responsible for ensuring creative and cultural depth in every project.

The human touch matters in an AI-empowered world

Language evolves at remarkable speed. Cultural attitudes, expressions, and specialized knowledge shift across demographics and time. Part of the modern translator’s job is staying attuned to these changes, continuously researching new trends and developments to ensure communication remains authentic. Human drives the choices that determine whether words carry the intended emotional and contextual weight.

AI can process information and automate tasks. But AI cannot empathize, make subjective interpretations, or anticipate subtle errors in sensitive content. Even as translation technology advances, human input is vital to shape content so that it is not only accurate, but also effective, nuanced, and appropriate for the target audience. 

My evolution continues

As I write this in 2025, I know the translator role will continue to evolve, as language, cultural and domain knowledge change too. Tools like agentic AI, contextual feedback, and advanced localization platforms such as Centific Flow deliver new features on a regular basis. These solutions automate repetitive tasks, provide quality assessment, and manage terminology, freeing up linguists to focus on strategy, creativity, and cultural authenticity.

Far from diminishing the translator’s role, these developments magnify the need for highly specialized human expertise. The translator of 2025 isn't just someone who knows multiple languages. We are cultural ambassadors in a hyperconnected world, ensuring that human understanding transcends linguistic boundaries.

A key part of my job as language quality manager is supporting translators with the tools, project knowledge, training, and channels they need to work with confidence. Now, we accompany them in discovering how AI fits into our workflows, not as a replacement, but as a complement to their expertise. Because in the end, it’s their human insight that makes global content stand out.

Learn more about Centific Flow

Flow automates core localization tasks such as machine translation quality evaluation, terminology extraction, source content analysis, and error categorization. Companies using Flow have reduced turnaround time by up to 77% and lowered localization costs by as much as 67%. These improvements make Flow a natural fit for agentic translation environments that rely on iteration, adaptation, and continuous refinement.

Flow includes integrated AI features for scoring translations, identifying sensitive content, extracting and managing terminology, and selecting models for retranslation. It also supports AI-driven video and audio localization to adapt multimedia content for global markets.

Flow connects directly with commercially available translation management services like Phrase and GlobalLink or operates as a standalone application. It gives localization teams the tools they need to support multiagent translation systems and to scale quality outcomes across channels and regions. Final review remains in human hands, preserving creativity, intent, and cultural authenticity.

Learn more about Centific Flow.