As we have seen recently, things can change very quickly in business technology. AI has leaped into our lives and is now becoming a major part of most of the daily processes and systems in ways we could never have imagined a year ago.
Termbases, critical business tools for those who seek quality and consistency in the content, and their related science of terminology management will be no different.
Peering into our crystal ball let’s see if we can catch a glimpse of a few of the future trends that will be impacting on our termbase management systems over the next year.
Cloud network storage
Long gone are the days when termbases were confined to a single desktop, accessible only by the one who created it. With cloud computing becoming much more ubiquitous in business, we can expect to see termbases becoming not just about storage but about accessibility, availability, and real-time updates. As businesses become increasingly global, the need for language experts to access these linguistic assets from anywhere, be it a bustling office in London or a quiet cafe in Kyoto, becomes imperative.
Cloud platforms don’t just facilitate this global reach; they also ensure that backup, security, and updates are managed centrally, reducing the nitty-gritty tasks for businesses, and freeing them to focus on their core operations. It also allows for greater levels of integration with more applications ensuring that you can apply your business language to your content, at anytime and anywhere.
Imagine a world where the process of updating a termbase doesn’t require manual intervention but is instead a seamless, automatic process. That’s where automation steps in.
Instead of combing vast amounts of content to identify and add new terms, automation tools, driven by AI, can detect, classify, and even suggest terms for inclusion. This not only streamlines the process saving you time and money, but also reduces the chances of error that manual processes can introduce therefore producing a much higher-quality final product.
AI data enhancement
Large Language Models thrive on data. The richer and more diverse the data, the more adept these models become by training the model with your specific business language. Termbases, teeming with linguistic intricacies, provide a golden opportunity here. By integrating termbases into AI training data, businesses can ensure that their AI tools are not just linguistically aware but are also culturally and contextually astute.
For businesses aiming for global resonance, this is a game-changer. A chatbot trained with a comprehensive termbase, for instance, would not just communicate; it would connect, understand nuances, and deliver a richer customer experience. Generative AI models would be able to produce content in your business voice using correct product names and ensuring consistency across the board.
The beauty of collaboration is that it captures a myriad of perspectives. In the context of termbases, this means a more robust and diverse linguistic database. Collaborative platforms are set to revolutionise termbase management by enabling teams, irrespective of their geographical location, to contribute to, refine, and leverage a centralised termbase.
This collective approach ensures that the linguistic spectrum captured is broad, nuanced, and immensely valuable and specific to your business needs.
Looking forward in termbase management
The great news is that many of these exciting changes to greater improve and simplify termbase management are already here and improving day by day. You just need to understand and take advantage of them.