We just wrapped up our exciting LangOps Universe event, which was full of thoughtful conversations with localization and customer support leaders from around the world. During this two-day event we hosted and participated in discussions about everything from ethics in AI, to tackling surges in customer support demands, facing fears to spur success, and everything in between.
Below, some of the biggest takeaways from this year’s event.
Language blocks your ability to scale
It’s no secret that global organizations need to translate product information, training materials, customer support systems, and more to connect with customers around the world. Research released during LangOps Universe unveiled that two-thirds of customers surveyed will switch to a brand that provides them with native language support, making it clear that companies can’t afford not to prioritize language.
But language is a tough nut to crack. It’s impossible to (affordably) employ native language speakers within every department of your business to cater to each customer’s unique needs. And it’s especially complex to deal with this issue when you account for surges in demand that occur throughout the year. This is a major roadblock to success for many organizations. But, there’s hope. AI-based innovations are leading the charge to solve this problem.
AI is powerful but imperfect
AI is changing the way organizations approach translating and localizing content. As Unbabel’s VP of Product Innovation Paulo Dimas put it, “AI is equivalent to electricity” in terms of its ability to disrupt the way our world operates. AI tools allow customer support teams to rapidly analyze keywords and triage urgent customer requests, and instantly translate customer support conversations into a variety of different languages.
AI is also supplementing the role of humans — empowering them to take on more complex roles to improve the quality of AI itself. Unbabel CEO Vasco Pedro compared the role of humans to that of a musician. Right now, humans are able to master a single instrument, but with AI supplementing their abilities humans can become the entire symphony. This is especially important as we deal with issues related to bias in AI. Machines aren’t perfect, but humans can teach them to be better.
Centralizing Language Operations is key
AI also holds the power to centralize the way in which organizations approach translating content across various departments and projects. This centralized approach is called Language Operations (LangOps) and relies on an AI-powered data layer to break down silos and store glossaries, translation memories, and custom machine learnings specific to a brand, that can then be used across an organization. The benefits are clear — it’s a simplified and more cost-effective approach to translations. As Associate Professor of Translation & Localization Management at Middlebury Institute of International Studies Adam Wooten said, “Centralized LangOps should be much more common than it already is.”
Careers are changing to accommodate this shift
Many of our LangOps Universe attendees were curious how a move toward centralized Language Operations would change the role of translation and localization experts in the future. The biggest takeaway from many of our speakers was that language pros will need to expand their expertise from language to language and technology. The success of Language Operations programs depends on the application of technological tools to power the function of translations across a company. Language experts will take on the role of editor and facilitator, guiding AI tools to properly translate content, accounting for context and cultural nuance.
Seeking executive buy-in on Language Operations
Many attendees were also curious about how to gain executive buy-in on Language Operations. The consensus from our speakers? Prove its value. The data is already out there. Companies are losing money by supporting multiple department-specific approaches to language translations. Money is wasted on multiple tools that serve duplicate functions. Translation and localization can’t be treated as something that’s attached after the fact to product teams or marketing departments — it must become a centralized function that lives across departments.
Thank you to all who attended and participated in LangOps Universe. Keep an eye on our blog for more recaps and takeaways breaking down all of the interesting conversations that took place.
