Márta Lesznyák: A longitudinal investigation of translation trainees’ translation and post-editing competence development I
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1 Literature review
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1.5 Machine translation, post-editing, and post-editing competence
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1.5.2 The status of post-editing in the language industry

1.5.2 The status of post-editing in the language industry

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As the output of MT was becoming better, agencies and professionals started to use it in their everyday work, together with post-editing. With some language pairs, this already happened with the emergence of SMT, but other languages had to wait for the arrival of NMT. Already, the TAUS MT Market Report in 2014 indicated that 38.63% of the respondents used MT in the translation workflow (Van der Meer & Ruopp, 2014, cited by Cid et al., 2020). About 10 years later, The European Language Industry Survey 2023 suggested that MT is used in more than 30% of professional translation businesses (ELIS Research, 2023). This proportion grew to 40% in 2024 (ELIS Research, 2024) and then to above 50% in 2025 (ELIS Research, 2025). Obviously, the TAUS and the ELIS results cannot be directly compared because of differences in samples. Nevertheless, authors of the European Survey in 2023 and 2024 note that the reported use of machine translation remains far below popular and academic estimations, which were above 50% in 2023, 60% in 2024 and 63% in 2025. These data are in line with a research finding from the academic domain (Nitzke et al., 2024), where interviews with translation experts from the high-end sector showed that far less MT and PE was employed than what had been expected by the researchers.

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At the same time, the results of the ELIS Surveys show that the spread of MT continues to be one of the leading trends in the industry, although it causes concerns because of dangers of low quality, pricing problems and the possible lack of human intervention (i.e., post-editing) (ELIS Research, 2023, 2025). Generally, there seems to be the sentiment of an “impending doom” in the industry, 43% of the respondents thinking that AI may eventually replace translators (ELIS Research, 2025).

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Surprisingly, the initial integration of AI into the language industry was not particularly successful. The 2023 report suggested that AI was evaluated negatively by language service professionals. This may have been due to the unfavourable media coverage of ChatGPT. The 2024 report confirmed this negative attitude, together with the fact that AI had come to be seen as the dominant trend in the language industry. In other words, by 2024, most participants in the industry were aware that the intrusion of AI was the most important ongoing process in the field, but they were not very happy about it. At the same time, the actual use of AI was still relatively low (around 10%) according to the 2024 report, but it increased to 43% in the work of independent professionals and to 34% in language service companies.

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In most cases, AI is used as an alternative to MT or as a consultant to discuss translation-related problems (ELIS Research, 2025). The quality of AI-produced translations is rated to be similar to, or slightly worse than, premium MT (ELIS Research, 2024). In addition, ethical dilemmas related to the use of AI are often discussed in the literature. It is, therefore, worth noting that 16% of independent professionals reported that they had ethical issues when using AI because of infringing intellectual property rights (ELIS Research, 2024).

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As for the type of service requested from companies, standard human translation still takes the lead, although a loss of 10% could be observed between 2021 (41%) and 2022 (31%), but a surprising 1% growth between 2022 and 2023 (ELIS Research, 2023, 2024). Unexpectedly, however, the 10 per cent loss between 2021 and 2022 was not taken up by post-editing, but by other language-related services like technical writing, global marketing or voice and multimedia. That said, post-editing was still the second most frequently offered service by LSPs (12% – 2022, 16% – 2023) (ELIS Research, 2023, 2024). To sum up, the clear trend is that human translation is in recession, whereas AI, MT and post-editing are growth areas together with some other language services. Nevertheless, there is a considerable amount of uncertainty in the system, although it is certain that human intervention is still required in the translation process (ELIS Research, 2025).

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In the Hungarian context, the translation agency Hunnect carried out a survey, in which they asked 150 professional translators about their experiences with using MT (Hunnect, 2021). The results showed that 69% of the respondents had used MT before, 28% of whom did so regularly. 78% of those who had already post-edited MT output did so because the translation agency they worked for instructed them to use MT. Another 14% of the translators claimed that it was their own decision to utilise MT while producing the target text. The findings on clients’ attitudes were somewhat surprising as they revealed that 29% of them avoid the issue and do not talk about it. Another 21% of the clients are firmly against using MT; they “forbid” its use. Nevertheless, 25% support MT and post-editing (Hunnect, 2021).

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All the surveys reviewed here highlight the growing importance of post-editing, even if the future is unforeseeable and attitudes to post-editing are sometimes controversial. It is, however, beyond question that post-editing is one task that human translators will have in the near future; in consequence, it is of prime importance to learn as much about it as possible through research.

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In the next sections, the notion of post-editing competence will be discussed, and two post-editing competence models will be described. This will be followed by a brief summary of some major research projects on post-editing competence and performance.
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