In the last 18 months, large language models (LLMs) have fueled a raft of startups and been rapidly injected into language technology platforms. But how have professional linguists responded to this pivotal moment in AI?
A survey of more than 750 translators — conducted in April 2024 for the 2024 Slator Language Industry Market Report — found that AI adoption by professional linguists is now widespread. Two-thirds of translators have used AI in their translation work in the past 12 months.
Whether via AI models (e.g., ChatGPT, Gemini), translation management systems, or standalone AI platforms, linguists are actively leveraging AI in new and creative ways to enhance quality and efficiency.
Here, we present the top 10 applications of AI by translators, based on results from Slator’s 2024 linguist survey.
Translate Source Text
The top use case for AI in translation is, unsurprisingly, to perform the core task of converting source into target text.
Generate Alternative Target Text Options
More than 30% of translators use AI to generate alternative target text options. This may include making text more concise, or identifying alternative terminology or phrasing.
Adjust Tone, Register, or Style
Around one in six translators uses AI to adjust the tone, register, or style of target text. The ability of LLMs to adapt text to different audiences, contexts, and purposes, is one of AI’s most promising applications, both in translation and in monolingual text generation.
Proofread for Spelling, Grammar, and Punctuation
Approximately one in six translators uses AI to proofread target text in order to identify and correct spelling, grammar, and punctuation.
Revise or Improve Fuzzy Matches
LLMs offer new options for enhancing and utilizing linguistic assets. Linguists are taking advantage of these capabilities; 15% of translators use AI to revise or improve fuzzy matches.
Slator 2024 Language Industry Market Report — Language AI Edition
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Check Terminology or Style Consistency
Just over one in ten linguists use AI to assess and maintain terminology and style consistency. LLMs are able to both identify inconsistencies and suggest corrections.
Create and Maintain Glossaries
AI’s terminology extraction and review capabilities are utilized by around one in ten linguists, who apply AI in the creation and maintenance of glossaries.
Generate Text Summaries
LLM’s can generate concise summaries of text by identifying and extracting key points. Just under 10% of translators are now leveraging this AI capability.
Translation Quality Estimation
Quality estimation may turn out to be one of the most impactful capabilities of LLMs. New workflows are now possible based on triaging content depending on the degree of human intervention required. Adoption among professional linguists is currently low, however, with just 7% of translators using this capability in the last 12 months.
Analyze Source Text
Around 7% of linguists use AI to analyze source text. Potential applications include identifying subject matter, key terminology, and linguistic characteristics that pose a challenge to translation.
For more translation AI use cases, along with in-depth analysis of AI adoption across the language industry, get a copy of Slator’s 2024 Language Industry Market Report — Language AI Edition.
The report also includes results from Slator’s 2024 surveys with hundreds of language service providers, localization buyers, and TMS and MT providers.