| This article was first published by Slator Tool Box in August 2025. As a linguist with a background in localizing sensitive and technologically advanced content for years, I’ve had a front-row seat to the dizzying evolution of many technologies. At the same time, I have seen my own professional transformation go at a slower pace, at least until AI came into the picture. Like many, I’ve built up my skills with AI as a tool as the transformation picks up speed, but I have also found myself wondering about our profession’s future. Are we effectively being replaced by AI or are we simply being redefined? To me, the answer is a matter of capabilities and relevance for both humans and machines. Some of my first big projects in edtech, for example, involved localizing cybersecurity training content for corporations and, more recently, foundational courses for a multinational tech giant, covering topics such as AI, cloud, data analysis, and visual story telling. Materials for cybersecurity training were aimed at companies of all sizes and covered a wide range of subtopics, from phishing and smishing to insider threats and social media dangers. You could say this is high risk, high stakes content. When it’s well translated, it’s the kind of content that can prevent a company from being hacked or worse. What’s interesting is that this sort of content is still incredibly relevant today, more than a decade after I first began working on these topics. The threats are still there, the terms part of the vernacular now, and cybersecurity a very big business. I’ve also focused on other specialized business training materials for corporations, including courses on compliance, ethics, and sales techniques. All those are also still very relevant subjects all over the globe. That’s not all. I have also been involved in some unusual projects, such as a recent one that is ongoing, localizing product training materials for a company that specializes in whisky. Now, this is actually a complex task that requires a deep understanding of a very specific product line, one subject to all kinds of special handling. So one thing that is different, in my experience, is that more specialized content like that is being localized as the process and timeline to get the final target version keep shrinking. Another change is that my role in some of this work is mostly as a validator, participating as such in the localization process at different stages. Sometimes I will be validating terminology. Other times I will be validating AI translations, and sometimes I will be the final language QA expert. |
| Another shift is that I’m no longer asked to perform final QA tests of user interfaces as frequently as before. My hunch is that companies are embracing AI-focused localization platforms with built-in automated checks and are trusting that the chain of both automated and human QA stages along the way is sufficient. |
Developing a new skill set
| So to me, the role of the linguist is simply being repositioned. If the content is sensitive — say, a medical or financial document — there will always be a need for experts-in-the-loop to do multiple checks, because even a small mistake can have serious consequences for the end user. As a tool, AI may be helping my clients to be more productive and shorten their time to market, but I’m still the ultimate validator they trust before they publish localized materials. Frankly, I consider all of the work I do as very precise. That includes subjects that might not be seen as sensitive as medicais or cybersecurity training modules. In fact, as a validator, my job is to ensure that the end user has a seamless experience with any localized materials, regardless of where in the process the validation happened or what the subject matter is. An evolving localization workflow implies that as linguists we need to adapt our skillsets to remain as relevant as the subjects we help validate. Besides a high level of target language competency and an ability to apply the correct context and nuance, we must now have a solid knowledge of general technology trends, especially AI. Back to my example of cybersecurity, even hackers are now using AI in increasingly sophisticated ways, so of course I need to understand things like these to effectively remain both relevant and accurate as the language expert. My daily tasks have also changed dramatically with AI, for the better: I use it to assist me with research, which it can do in a third of the time it used to take. I find it particularly useful for cultural consultancy projects. For example, I have used it to help me generate ideas for a specific sport, a field in which my expertise is not as deep, as well as for learning the stages of creating memes using video content. I’d say that, as a research tool, AI has at times been invaluable in helping me meet a tight deadline and come up with specific, relevant transcreation ideas that would have been difficult to produce on my own in the same amount of time. |
| AI is also helping me navigate a frustrating trend: the proliferation of poorly written source text, often created by non-native speakers or even unchecked AI-generated content. With the pressure of ever shorter deadlines — sometimes less than 24 hours — there is often not enough time to raise a query with a project manager who in turn has to reach out to an end client. It’s in those moments that I find myself using AI as a quick consult for clarification of terminology, ensuring that I can move forward without compromising quality. |
| I see a potential trajectory for our profession that, in the short term, is mostly about post-editing. In the long run, I see our role transitioning more into that of validator or approver at different stages of a project, as in the examples I mentioned. We are the ones whose expertise is trusted to ensure the AI hasn’t made any mistakes or missed any critical nuance. I believe we are still very relevant and, in the loop, but the most important skill we can have is that of being able to adapt to new ways of working. The future of language services isn’t about being replaced by AI, but about adapting to a new, collaborative landscape. As AI translation takes on the initial workload for a wide range of domains, the role of linguists will keep evolving, but our unique blend of cultural knowledge, subject matter expertise, and creative flair will be more crucial than ever to ensure that global communication remains accurate, nuanced, and genuinely human. |
