Most people would think about machine translation when discussing AI and the language industry. However, AI isn't only influencing translation services but also the localization sector through faster and more precise targeting and analytics.
Slator reported that in 2021, the global translation and localization sector's market value would be 26.6 billion USD, with a growth of 11.8%. Meanwhile, Data Intelo projected that the global localization software market would grow to 5.51 billion USD with a growth rate of 4.3% by 2030.
The increase in demand for localization and translation services may seem surprising, especially during the pandemic. But this steady rising demand for language solutions is due to globalization and digital advancements over the years.
We've listed a couple of data and trends as the reasons why there is a rise in demand for localization:
The data presented shows that as businesses become more present on the internet, through ecommerce sites and in digital marketing, the need for localization will continue to grow in the foreseeable future. With the advancement of technology, we will most likely see more multilingual integration in digital devices and software.
Machine translation (MT) has come a long way since it was first developed in the 1950s. In recent years, with the rise of AI, the language industry began developing neural technologies in MT that don't just accelerate the translation process but have the capability of analyzing large quantities of data. It is even speculated that MT and AI translation will be used in the coming years to document and preserve languages for future researchers.
Unlike other forms of MTs, neural machine translation (NMT) uses a neural network model that mimics how the nervous system operates that tries to predict the most probable sequences of words. NMT is considered the most powerful algorithm because of its deep learning capabilities in being trained to translate from one language to another.
Despite how advanced MT has become over the years, many are wary of the quality of translation it produces. But with how the global workforce is experiencing an industrial revolution 4.0 with the rise of AI and other advanced technology, it's not surprising that the language industry is undergoing a similar situation.
MT shouldn't be perceived as technology replacing linguists but rather as a way to aid translators in creating faster and more multilingual content. It's especially true when we look at how AI is being used to analyze and create a more personalized experience in content marketing.
Hyper-localization is defined as creating content that's based on data from a particular region or city. The information obtained is based on what shoppers are searching and purchasing online. It's not to be confused with hyper-personalization, which is somewhat similar due to their use of AI in data-driven and predictive nature to create content.
When it comes to hyper-localizing your digital marketing, AI adds a layer of personalization based on your target locale's cultural and linguistic preferences. In implementing hyper-localization, you will have to strategically think of ways of creating that have a local spin to it, like writing about local events or conducting geo-targeted research derived from the information and data gathered from its target region or city.
Customers are more receptive to hyper-localization than conventional localization because businesses can create offers and promotions depending on the local trends and demand that will then be recommended to them. In SEO, geo-targeted customers will have immediate access to the content you created, which helps your business's visibility in your target market.
Another reason hyper-localization is considered more effective is that it culturally and emotionally creates content that resonates with customers. Instead of presenting the brand as it is by just adding cultural and linguistic context, hyper-localization also seeks to combine the emotional and personal side of culture and language in marketing that is often overlooked, which in the end fails to capture the target audience's attention.
Relating it to AI's application in marketing and the language industry, it accelerates the creation of multilingual content and assists localization marketers in identifying potential trends and promotional opportunities that competitors haven't taken advantage of.
AI has drastically changed how the language and marketing industries operate and create content marketing. I have listed some key points that summarize the entirety of this article as follows: