How Big Is the Machine Translation Market in 2024?

It’s a big question because it has so many far-reaching and long-lasting impacts: Just how big is the machine translation (MT) market in 2024? 

The answer can influence professionals considering joining the industry; tech experts thinking up their next big invention; and investors doing their due diligence and looking into ROI. 

Anecdotally, MT has only gained more ground in the first half of 2024, thanks in large part to the hype surrounding AI-enabled solutions that also offer translation, such as ChatGPT. The release of foundation models (i.e., those for more general use, versus specific disciplines or tasks) has piqued interest among observers in a variety of fields. 

As laid out in the 2024 Slator Language Industry Market Report, Slator estimated that the size of the MT market increased by 31% in 2023 to USD 1.55bn.

There are two major factors behind the significant boost. On the one hand, more users than ever are finding raw MT as “acceptable” for their use cases — that is, a growth in demand for MT at the lower end of the market has supercharged pure pay-for-play MT providers. 

On the other hand, Big Tech’s tighter budgets throughout 2023 had a negative impact on growth at the higher end of the market. That said, demand from enterprises across sectors has continued to grow overall.

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So, who currently stands to gain from the growing MT market? A handful of household names in Big Tech, such as IBM and Microsoft, offer APIs for generic and domain-specific models, plus options for self-serve customization. Some, such as Amazon AWS and Google, offer MT as one of many language AI applications within a comprehensive cloud computing platform. Other companies in this category include Chinese heavyweights Alibaba, Baidu, and Tencent, as well as Russia’s Yandex.

Specialized MT providers often also offer language AI models or platforms for speech-to-text, speech synthesis, text generation, and AI transcription, among others. 

Some companies market themselves with tongue-in-cheek names, such as PROMPT and XL8, or those that make clear their offerings (e.g., Tilde MT and ModernMT). Other companies in this category include Omniscien Technologies, Pangeanic, Mirai, CrossLang, DeepL, SYSTRAN, and Textshuttle (which recently merged with services provider Supertext).

Of course, language services providers (LSPs), often colloquially called translation agencies, have increasingly expanded their offerings to include AI-enabled jobs. Today these LSPs, such as Rozetta Translate, Lilt, and Welocalize, typically provide proprietary models, model pre-training, customization, and a fully managed menu of MT services. 

And some of the most established LSPs have adapted their platforms and portals to integrate AI capabilities. These include TransPerfect’s GlobalLink AI; RWS’ Language Weaver; Keywords’ Kantan; and the eponymous LanguageWire Translate.

In an increasingly crowded landscape, with more at stake than ever, MT providers can differentiate themselves based on the language pairs they cover; the quality of their baseline models; their domain specificity; data security measures; and integration into other platforms.