Key opportunities to help organizations translate more for less

Alina Bojescu 30 Jan 2024 6 mins read
An introduction to translation collaboration
If you’ve seen demand for localization support surge within your organization recently, you’re not alone. Our industry-wide survey tells us that translation work demands on corporate translation departments have intensified in the last 12 months, with 48% experiencing an increase in the number of project files, 37% in the number of departments requesting work, and 37% in the number of words per project. 
But handling an increased volume of localization work – and more varied, larger localization projects – can be an operational nightmare. You need to translate more, with the same resources, all while maintaining the expected quality.  
It’s a tough balance to strike. But, if your organization can step up with more efficient ways to deliver localized content, the potential rewards are substantial. By doing so, you not only meet the demands but also reach and connect with a wider audience in more engaging ways than ever before. As shown by numerous studies, people engage more with content in their own language.  
Fortunately, alongside the steep rise in localization demand, we’ve also seen the emergence of some incredibly powerful new technologies and digital capabilities accelerating – and fundamentally transforming – localization processes.
If your organization is looking to take steps toward translating everything, here are three opportunities you can’t afford to overlook: 

1) Generative AI and Large Language Models (LLMs) 

It wasn’t long ago that the translation industry first grappled with the rise of neural machine translation (NMT), which quickly became the most important application of linguistic AI in the industry. Now, a new technology is sweeping through – generative AI, specifically large language models (LLMs), sparking discussions about its impact and raising a whole new world of possibilities. 
While not primarily designed for translation, LLMs hold potential due to their fluency and adaptability. Consequently, organizations are actively exploring ways to integrate them into their translation processes. For instance, to harness their strengths while avoiding weaknesses like hallucination and bias, LLMs can be used as supplementary tools for translation professionals. When used in conjunction with translation memory (TM), terminology, or machine translation (MT), LLMs can enhance translations without introducing errors or biases. 
In Trados, through this approach, our generative translation capability can direct LLMs to retranslate MT-translated segments or translate untranslated segments. This process can incorporate approved terminology and adhere to prompts such as specified style, length restrictions, and gender. 
There are other examples of how AI is already being used or explored, where the LLM:  
  • Uses data about prior completed projects and, based on similarities with the presented files, responds with (for example) a recommended workflow, project template or settings, or suggested people to work on the project. 
  • Takes on a linguistic reviewer persona to identify issues in translation segments, returning a simple quality score with a brief explanation. 
  • Provides help or support for the translation technology being used by returning an answer based on existing help and support materials for the solution when the user asks a natural language query. 
These examples show that the right use of AI capabilities in translation technology can speed up translation tasks for linguists and streamline repetitive project management duties. However, just like with NMT, it's important to recognize that AI isn’t here to replace your human translators and project managers. It’s at its most powerful when embedded into human workflows, used to augment human expertise, and helps experts spend less time on routine localization tasks. As a result, more translated content can be created with the same resources and funds previously earmarked for tasks that can now be automated can be reallocated and spent elsewhere. 

2) Cloud-first working 

The cloud has fundamentally transformed the localization industry. It has democratized access to powerful translation technology and changed how work is managed and completed. Cloud-based translation platforms offer a single place where your teams can access leading localization technology capabilities, collaborate seamlessly, and share requests and documents with others in the supply chain.  
As the industry has continued to move from on-premises/desktop towards cloud, we have seen that cloud-first (but not cloud-only) working has really taken root, especially for functions that benefit most from the easy accessibility of centralized, cloud-stored linguistic assets and cloud-managed processes. The most common combination is cloud-based translation management with a desktop-based translation tool.  
This shift towards cloud-first working is also opening new opportunities for organizations. As cloud solutions are easy to roll out and access, coupled with the enhanced adaptability of cloud-based editing tools for different audiences, and the marked improvement in machine translation (MT) quality, we’ve recently seen a growing focus on cloud-based translation review by subject matter experts (SMEs) who are not themselves translation professionals. We’re seeing this mostly in subject areas that require specialized knowledge and specific use of terminology.  
Many organizations see an opportunity to rely on MT, with their SMEs editing it as necessary without the direct help of a translation professional. The idea behind this ‘SME as post-editor’ model is that the quality is good enough that it’s more a terminology review than a post-editing job – with the fluency of LLMs probably accelerating this trend. 
For your corporate translation team, cloud-first working can help boost productivity, especially if adapted to make it as easy as possible for SMEs to contribute their expertise. Empowered with cloud localization tools, you can achieve more in-house, and ensure that any spending on external localization support delivers maximum value for your business. 

3) Language Operations 

As organizations struggle with the volume, velocity, and variety of their localization requirements, many are realizing that the ad hoc approach they’ve been using can’t keep up. ‘Language operations’, or LangOps, is a term increasingly used within the industry for the approach that organizations need to take to move localization from ad hoc activity to strategic business enabler, applied consistently across the business as a natural, embedded business process.  
‘Strategic’ is key here. Reorganizing a business for LangOps means making it a C-suite issue, with direction coming from the top down. LangOps is about breaking down organizational silos to make localization cross-functional and scalable. 
Technology, and especially AI, is a key enabler of LangOps because of its ability to support scalable end-to-end processes, automate previously manual processes, and help organizations localize more consistently across organizational boundaries. LangOps will typically take an AI-first approach but recognize the importance of ‘the human in the loop’ for quality assurance and governance. 
In addition to AI, as well as the cloud-first working mentioned above, organizations will also need to be leaders in the use of translation ecosystems. This has led to a growing emphasis on creating technology ecosystems with seamlessly integrated elements and systems that facilitate smooth workflow as a LangOps enabler. Recognizing that no single solution can fulfil every need, it becomes crucial to choose a solution with integration capabilities. This includes assessing the availability of APIs, out-of-the-box connectors, and evaluating whether there is an active community of developers building integrations and extensions for the platform. 
For corporate translation teams, it’s good news if organizations pursue a more strategic approach to localization. There is an opportunity to step up, to position themselves as strategic advisers (in-house or as a partner) on LangOps initiatives and deliver considerably greater value to the organization. And, by embedding localization practices into workflows in a defined, consistent, and repeatable way, LangOps opens doors to translate more, more consistently, for more people. So, you can make your content inclusive by default.  

Translate everything with the right technology  

Localization is both more important, and more challenging than ever. Your organization needs to translate more, in less time, often with the same resource. Without the right technology, that’s simply not possible. But, with the right tools, and support on your side, you can move towards a position where you can respond to the opportunities presented by emerging trends.  
If you're interested in exploring how translation technology can turn your challenges into opportunities, please reach out for a discussion with our experts. 

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Alina Bojescu

Alina Bojescu

Marketing Manager
Alina is a Marketing Manager at RWS, focused on promoting Trados to Corporations. She has a bachelor’s degree in Publishing Media and over seven years of marketing experience.
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