Written on 10 February, 2022

The total size of the global translation market is expected to grow from $23.8 billion in 2021 to $26.2 billion in 2022 and $28.6 billion by 2023[1] and while growth in demand for human translation has only increased by an average of 5–8% in recent years, there has been near exponential growth in demand for automated translation.


But where does this shift towards ever-increasing automation leave language professionals? Despite these seismic shifts in the industry, linguists will remain vital cogs in the automation machine.

We’ve all heard the (quite valid) concerns that linguists will be phased out with the shift towards automation, however, in the future, linguists will continue to play a key role as humans in the automation loop. Human-in-the-loop is a term that has been around in the field of artificial intelligence for a number of years and refers to the process of combining machine and human intelligence to leverage the most efficient outcomes. In the translation world, this approach has opened up significant new opportunities for linguists and enables us to leverage the power of machines to enhance our work, rather than replace us.

Despite the massive improvements in machine translation output over recent years, anyone that has worked with this output will tell you that, for most genres, the quality of raw machine output is still not fit for most purposes.

What roles will humans play in the translation loop in the future?

On the macro level, linguists will play a key role as linguistic consultants to their clients. Linguists will be able to use their linguistic experience and knowledge to provide clients with vital insights on the kind of projects that will be suitable for MT use. It’s in your hands to explain to your client why it probably isn’t the best idea to translate all their marketing copy in their fancy new MT engine and advise that the human touch will continue to be integral for these types of texts, among other.

The feedback loop

All machine translated content is generated from previous human translations so linguists are also the key players in training these machines, both through the translated input that is fed into the machines and the vital feedback they provide on all projects. This feedback on machine translation output is key because it allows machine trainers to tweak their machines to provide the best possible output.

Even now, linguists can leverage their position as language experts and upsell clients with consultation services on training their machines, a potential revenue stream that would not exist without this increase in automation.


Now, on the micro level, linguists are always being told to specialise in certain genres that interest them but specialisation can also involve being open to new automation opportunities and post-editing. The more you specialise as a linguist, the more you are seen as an expert and the more in-demand you will be. By taking the time to get to know the post-editing process and showing an interest in new translation technologies, linguists will be able to position themselves as experts in this emerging service level.

If you have absolutely zero interest in taking part in post-editing or automation then the other facet of specialisation is equally important. Become an expert on high-quality services. It’s clear that, as far as quality is concerned, machines will never be able to fully replace humans for the kind of high-quality publishable materials that businesses rely on. Specialising in these kinds of texts will make you a reliable partner for clients that will continue to rely on humans on well into the future, while allowing the machines to relieve us of the less important, and often less exciting and impactful projects.


The fact of the matter is that increased automation has opened the doors to translation for countless sectors that may not have seen a need for translation in the past. As linguists, this exponential growth for translation services is something we should embrace and we shouldn’t regard machines as the enemy, but a tool that we can leverage to increase speed and consistency, while also allowing us to focus on the sectors we find most interesting.

Written by Greg Hyne

[1] Slator 2021 Language Industry Market Report