Language RPA: A New Era in Language Technologies

Robots appear to be everywhere these days, from operating life-saving surgery to delivering fast food. But I’m sure you’ve never considered language robots or noticed “Language RPA” before. And, while you’ve most likely heard of automated translation, text analytics, translation productivity, or translation management, you’ve probably never heard of it in the context of Robotic Process Automation. In a nutshell, RPA is a robotic process automation.

Despite technologies that comprise what we now refer to as RPA not being novel, the impact of this business process automation framework has been bolstered by the rise of specialized artificial intelligence (AI) and its affiliation with the expected Fourth Industrial Revolution. RPA was primarily a “screen scraping” process that could only automate very particular jobs, a decade ago. RPA now encompasses almost any human process that can be automated using software. RPA may imply intelligent routing of customer support emails or digitization and storage of physical invoices for one company, while it may mean interfacing legacy software systems or converting content throughout its lifecycle in the company for another.

As RPA becomes more skilled and pervasive, it helps to absorb business areas of application where the significance of automation was previously obvious only to a specific market segment but is now related to entire industries. And working with content is one area where RPA is beginning to have a significant impact, albeit not through innovation in and of itself, but rather through repurposing and demonstrating new investment return to processes that already have a history in certain areas.

This is precisely the case with Language RPA, that you’ve not noticed until now because… it wasn’t a phrase that had been invented yet. If you worked in a multinational corporation’s localization branch, you may have been familiar with language-specific automation software areas such as translation management or translation productivity, which replaced by automation project management and content process transformation and aided in the translation and delivery of content. If you worked in data analytics, you would have used a mixture of text analytics and machine translation to perform case management on multi-language content, As most translation companies in Dubai do for instance. However, this sort of content-centric (or language-centric) automation was never referred to as RPA in the industry.

Commercial automation has already cropped up with the help of major RPA players like UiPath, BluePrims, PegaSystems, NICE, and Kofax. The general rule of thumb for all RPA-based digital transformation attempts is to identify non-strategic actions that can be automated, ranging from sales, R&D, and finance to employee management and customer service. As a result, efficiency, cost savings, process improvement, and reusing employees for more exciting projects.

 Language RPA, a subcategory of Content RPA, is not a new invention, but it is just as essential as automating accounts payable, claim processing, contact center, HR, or Finance and Accounting. Content can be produced, handled, converted, and shared for usage with a high degree of automation thanks to recent advances in AI and processing capabilities.

Natural Language Generation (NLG) has known to be an efficient method for creating content from previously human=created structured and unstructured content sources.

For certain use cases, content can then be completely automated with Neural MT, or it can be managed by human translation workgroups in a highly automated manner by depending on translation management systems that can automate the majority of project management tasks. At the same time, most redundant human workflow steps are eliminated, and content is transformed using file filters, translation memories, or machine translation.

Finally, using Text Analytics, content can be automatically understood and intelligently delivered to its audience in the desired format, language, and writing style, resulting in an end-to-end approach to the content lifecycle that includes the greatest amount of automation possible.

Language RPA situates current and novel approaches to handling language-specific tasks within the context of the Fourth Industrial Revolution, providing an indisputably unique method to workforce repurposing and full utilization of content in all its types.