As the world becomes increasingly global, language continues to grow in importance for many companies to help them communicate with their customers around the world. The problem is that existing language efforts are fragmented and there’s usually a lack of centralized resources to streamline multilingualism at most organizations.
In this post, we’ll discuss the ways that the translation field is evolving and how organizations can tap into the benefits of this change by forming a dedicated Language Operations (LangOps) function.
The evolving translation landscape
AI is changing the way nearly every industry operates, and translation is no exception. As machine translation tools continue to improve, translators will take on more of an editor and facilitator role when translating content. In fact, we’re already seeing the role of translators evolve with computer-aided translation (CAT) tools, which reduce the amount of work human translators need to do from scratch through memorized phrases, terminology banks, and more.
CAT tools enable machine-assisted translation, but in the near future, it’s likely that companies will flip the script and humans will assist machines with translation instead. Since machine translations are far from perfect, especially with more subjective content that requires additional contextual understanding and linguistic nuance, human translators will still be a necessity. By keeping “humans in the loop” when using these new AI and machine learning solutions, companies can deliver high-quality translations at scale.
Besides the use of machine learning, the way language is handled is likely to change as well. Many companies currently have a disjointed approach to who owns language throughout the organization, where different teams and departments have various processes for completing language translation projects. This limits the company’s ability to operate as a multilingual business and communicate with customers around the world in their native language.
Rather than treating language as one-off translation projects, however, companies could form a dedicated LangOps team that drives effective language use across the entire business. Let’s take a closer look at what that team may look like.
Defining the LangOps team
As AI and machine translation continue to transform the role of human translators, the LangOps field could be a future career opportunity as well. Translators already have the linguistic ability, but learning the skills necessary to work with machine learning tools and implement business processes could position these individuals to become LangOps professionals. As part of a LangOps team, translators can turn their skills into a strategic asset to the business.
The LangOps team would be responsible for managing the people, processes, and technologies that enable multilingual communication. This would involve building out strategies to leverage language for existing and future markets, which includes implementing the right technologies and machine learning solutions, localizing products and messaging, putting efficient language processes in place, measuring translation quality, and more.
Rather than separate roles and departments for localization and multilingual customer service, the LangOps team should be an organization-wide effort. That means the head of LangOps should report directly to the chief operations officer in order to break down operational silos and ensure language solutions are closely aligned with business objectives.
On a daily basis, LangOps professionals would focus on scaling the language layer of an organization. This would include onboarding new machine translation solutions, optimizing existing models for domain knowledge and company-specific terminology, and ensuring language solutions are accessible throughout the organization.
Consider the LangOps approach
Hiring for LangOps skills or building out a LangOps function can enable global businesses to communicate better with their customers and stakeholders in their native language. A dedicated language team can break down silos that exist within current translation processes and encourage the use of language as a strategic asset.
Machine translation is set to disrupt the translation industry, but that doesn’t mean humans will be replaced. Instead, organizations must look to hire individuals with linguistic talents that can ensure the quality of machine translations and implement effective language processes throughout the organization. LangOps isn’t just about the technology; it’s about the people too.
Want to learn more about LangOps? Download our recent ebook: Going Global with Customer Support: How and When to Build and Execute a Language Operations Strategy.
