Approx read time: 4 mins🕒
Post-editing is becoming one of the most important steps in managing high-volume content.
From translations to AI-generated articles, the human layer of review ensures accuracy, consistency and credibility.
We’ve been supporting clients with Machine Translation Post-Editing (MTPE) since 2019, and today we’re also helping clients refine AI content outputs to protect brand trust.
What this blog covers:
- What Machine Translation Post-Editing (MTPE) is and why it matters
- The role of post-editing in high-volume content environments
- How AI-generated content creates new challenges
- Real-world insights from Wolfestone
- Final tips on when to use post-editing
What is MT post-editing and why it matters
Machine Translation Post-Editing (MTPE) is the process of reviewing and correcting machine-translated content to bring it up to a publishable standard.
It allows organisations to produce large volumes of multilingual content efficiently, without sacrificing quality.
High-volume environments, like e-learning, product pages, documentation or online articles, benefit from MTPE because it balances speed with human accuracy. Instead of starting from scratch, linguists refine existing translations, making projects faster and often more cost-effective.
Post-editing in translation
While machine translation (MT) can generate content quickly, it often lacks the nuance, cultural relevance and tone needed for professional use.
Post-editing steps in here, with human linguists reviewing and refining the output. They check for accuracy, correct any mistranslations, and adjust for tone, style and context.
It shouldn’t come as much surprise that the average MTPE adoption by language service providers in projects has risen from more than one in four (26.1%) to almost one in two (45.8%) in 2024, according to Nimdzi’s 2025 survey.
The MTPE process guarantees that the translation is not only accurate but also culturally appropriate and aligned with the brand's voice.
Post-editing is especially important in legal, marketing and technical translations, where precision and attention to detail are critical.
Post-editing beyond translation
AI is now used to generate more than just translations. Articles, product descriptions and training guides can be created automatically at scale by generative AI to support budget savings.
However, this technology is far from perfect:
- AI outputs can contain factual errors or ‘hallucinations’
- They may not follow brand style or tone
- Most default to American English, which may not fit UK audiences
Much like MTPE, it shouldn’t be seen as completely accurate. Post-editing
(which we can offer as a standalone service) bridges the gap, ensuring that AI-generated content is accurate, natural and aligned with business needs.
“AI-generated content is changing the way organisations produce material at scale. However, unchecked AI outputs carry risks of inaccuracy and reputational damage. At Wolfestone, we offer machine translation and recommend AI, but we openly don't suggest it for a lot of projects. Post-editing means you aren’t blindly trusting and provides the safeguard to strike a nice balance of speed and reliability.”
Real-life example: Wolfestone
We thought it would be helpful to share an example using our own work and insights, as we have toyed with post-editing blogs recently.
What we will say is that we aren’t just getting AI to write anything and gently post-editing it. We are providing it with our style guide, our mission statement, a focus keyword, our unique selling points, a comment that we want it to avoid overuse of AI-sounding phrases and information we specifically want the blog to include.
There are also multiple safety nets in place. For example, the post-editing is done by an experienced marketer every time.
We thoroughly check all content, adapt it and add or check relevant stats (as we don’t want to be victims of hallucinations). We also add our own hooks as well as internal and external links.
Results: We saw more views in the last month from post-edited content than we did for all of our content from the month before that.
And out of our blog views since using post-editing, 31.54% accounted for post-edited content.
The data, from Google Analytics, counts our blog views from the start of AI content (22nd June) for a one month-period in comparison to the previous one month period.
From an SEO perspective, it has only impacted us positively. Looking at position tracking analytics and our visibility showing our website’s progress in search engines, that figure has risen consistently and by 14.15% (as of 28 August 2025).
We’d advise marketers to stick to their core topics, like we have. You don’t need AI to put up hundreds of unrelated blogs and gain irrelevant traffic.
For what it's worth, we don’t think there is always a place for post-edited AI content.
When we’re crafting original content, using new examples or diving deep into topics as only humans do, it won’t be needed. But it’s helpful to know that if time is against you, when prompted with detail, it can provide a good outline for a piece to build on.
Common mistakes to avoid
- Relying solely on raw machine output – it may save time upfront but risks poor quality and lost trust.
- Skipping localisation – style, tone and regional language (such as UK English) matter.
- Overestimating AI accuracy – proofreading and review should always follow AI-generated content.
Conclusion
Post-editing is not a replacement for translation or content creation, but it enhances both when volumes are high and deadlines are tight. It makes machine and AI outputs safe, credible and fit for purpose.
Wolfestone offers MTPE, proofreading, and review as standalone services, ensuring your content delivers clarity and confidence in every language.
Get in touch with our team today to explore how post-editing can support your business.
𝘑𝘢𝘤𝘬 𝘸𝘳𝘪𝘵𝘦𝘴 𝘢𝘣𝘰𝘶𝘵 𝘵𝘳𝘢𝘯𝘴𝘭𝘢𝘵𝘪𝘰𝘯, 𝘭𝘰𝘤𝘢𝘭𝘪𝘴𝘢𝘵𝘪𝘰𝘯 𝘢𝘯𝘥 𝘮𝘰𝘳𝘦 𝘭𝘢𝘯𝘨𝘶𝘢𝘨𝘦 𝘴𝘰𝘭𝘶𝘵𝘪𝘰𝘯𝘴 𝘧𝘰𝘳 𝘞𝘰𝘭𝘧𝘦𝘴𝘵𝘰𝘯𝘦. 𝘏𝘦 𝘭𝘰𝘷𝘦𝘴 𝘵𝘰 𝘧𝘪𝘯𝘥 𝘳𝘦𝘢𝘭-𝘭𝘪𝘧𝘦 𝘦𝘹𝘢𝘮𝘱𝘭𝘦𝘴 𝘰𝘧 𝘸𝘩𝘦𝘯 𝘴𝘰𝘭𝘶𝘵𝘪𝘰𝘯𝘴 𝘩𝘢𝘷𝘦 𝘢𝘯𝘥 𝘩𝘢𝘷𝘦𝘯'𝘵 𝘸𝘰𝘳𝘬𝘦𝘥 𝘵𝘰 𝘱𝘳𝘰𝘷𝘪𝘥𝘦 𝘢𝘴 𝘮𝘶𝘤𝘩 𝘳𝘦𝘭𝘢𝘵𝘢𝘣𝘭𝘦, 𝘰𝘳𝘪𝘨𝘪𝘯𝘢𝘭 𝘤𝘰𝘯𝘵𝘦𝘯𝘵 𝘵𝘰 𝘵𝘩𝘦 𝘢𝘶𝘥𝘪𝘦𝘯𝘤𝘦 𝘢𝘴 𝘱𝘰𝘴𝘴𝘪𝘣𝘭𝘦.
