AI Translation Not Working? Here’s the Fix Global Teams Actually Use

AI Machine Translation Post Editing (professionally known as Machine Translation Post-Editing or MTPE) is a translation process that the best global teams use to combine the speed of machine translation with human reviewers for accuracy. It helps companies reduce costs, accelerate timelines, and maintain high-quality multilingual content. This hybrid approach is ideal for scaling localization efforts using AI with standards for how to maintain accuracy. 

What Is AI Machine Translation Post Editing (MTPE)?

Definition: AI Machine Translation Post Editing (MTPE) is a hybrid workflow that feeds raw machine-translated text to a trained linguist who performs post-editing on MT output for the purpose of checking its accuracy and comprehensibility, improving the text, making the text more readable, and correcting errors. Post-editing differs from translation as it involves three texts: the source text, the MT output, and the final target text.

Don’t let the word “machine” in MTPE throw you off – the term actually came from what we know as AI translation actually started as machine translation in the 1980s.

An industry report from DeepL states:

“Though machine translation brings speed and accuracy benefits and frees up human reviewers for more meaningful tasks, there are valid concerns about its ability to translate industry-specific jargon. 

As per the findings, 82% of respondents report that product, company, or industry jargon is not translated accurately when only using machine translation. Yet 61% handle such vocabulary by training their own custom machine translation models… or using a glossary provided by a machine translation vendor.”

MTPE is how you ensure you have accurate translations while implementing AI and building your localization workflow. But it only works if it’s properly supported by a translation strategy and AI tools that are used intentionally with human review.

Why Modern Brands Choose AI Translation + Post-Editing

Many organizations that Interpro works with choose AI translation with MTPE for many reasons:

• Speed at Scale: AI automates much of the repetitive work. Tens of thousands of words processed per hour.
• Accurate Localization: Professional linguists accommodate cultural or technical nuances that AI can’t support.
• Cost Efficiency: Average savings of 30-60% versus human-only translation (Intel).
• Regulatory Compliance: Post-editors verify sensitive or legal content before release.
• Market Reach: Faster turnaround means simultaneous multi-market launches.
• Statistics: 80% of the survey’s respondents use machine translation, while 70% of respondents struggle to find linguists to edit machine-translated texts (Multilingual).
• Planning Strategy: Opens capacity for higher-creativity linguistic tasks (transcreation, consultation).
• Continuous Improvement: Enables continuous-learning loops, post-edit data trains better MT engines, which in turn hand translators cleaner drafts for less editing.

Ensure AI Translation Quality: Inside the ISO MTPE Standard

The global benchmark for MTPE quality is ISO 18587:2017. It defines:

• Post-editor competencies: linguistic expertise plus MT literacy.
• Process steps: from MT output evaluation to final client delivery.
• Quality metrics: accuracy, completeness, and stylistic adequacy.

Adhering to ISO 18587 gives buyers assurance that MTPE output meets professional-grade standards. Read the full text here.

From Source to Delivery: The MTPE Workflow

The AI plus MTPE workflow moves source content through a structured process where AI produces the first draft and linguists prepare inputs and refine outputs. This keeps cultural accuracy, technical precision, and final quality consistent from start to finish. Structuring the AI + MTPE workflow is critical to ensure success. It requires the standard cultural and technical localization process, while also understanding the technical requirements to prepare and edit AI output.

Step 1 – Pre-Processing & Glossaries

• Prepare the files for processing.
• Extract key terms to create a glossary.

Step 2 – Machine Translation Output

• Select the best-suited Machine Translation model based on the language pair and the subject domain.
• Process the prepared file and run the Machine Translation process to generate raw Machine Translated files for post-editing

Step 3 – Human Post-Editing Review

Post-editors will use as much of the MT output as possible and focus on the following to perform Post-editing:

• reading the MT output and evaluating whether a reformulation of the target language content is necessary.
• using the source language content as a reference in order to understand and, if necessary, correct the target language content.
• producing target language content either from existing elements in the MT output or by providing a new translation
• adhering to client and/or domain terminology
• ensuring that no information has been added or omitted
• restructuring sentences in the case of incorrect or unclear meaning
• editing any offensive, inappropriate, or culturally unacceptable content.
• producing grammatically, syntactically, and semantically correct target language content;
• applying standard spelling, grammar, punctuation, and hyphenation rules.
• ensuring that the style appropriate for the text type is used and that stylistic guidelines that may have been provided by the client are observed.
• applying formatting rules and ensuring that tags and codes are copied over from source to target segments.
• performing a final review to ensure the target language is accurate, usable, and appropriate for its intended audience and purpose.
• providing feedback on the performance of the MT system in order to allow for improvement of the MT system used and the processes followed.

Optional: Localization of the Edited AI Output

Interpro doesn’t only help clients edit AI translations. We also support organizations by localizing the translations for culture, brand consistency, and compliance. By adding this optional layer, your team gets translations that not only read correctly but perform correctly, protecting message integrity, reducing rework, and ensuring your content lands exactly as intended.

MTPE Quality Expectation

It’s critical to understand that MTPE is not going to be a fit for every project. Think about your content: Is it very technical and straightforward instructions? Or does it need to read like natural, conversational language with a storytelling tone?

If you are leaning towards the second option, MTPE may not be enough for your content. You may skip AI translation and choose to work with a completely human linguistic team.

When we deliver a translation, you can count on it to be accurate, clear, and grammatically correct. Machine-supported workflows handle the core meaning very well, and they help you move fast.

There are moments, though, when language carries more personality or cultural depth. While AI can do the minimum required localization, humor, tone, brand style, and subtle phrasing needs a human touch to feel truly natural. Additionally, AI won’t fix your formatting issues or help you localize the translated content back into your source file. Depending on the content, the machine output may not always capture every nuance that a fully human translation would.

You still get a dependable and correct translation. If you ever need deeper cultural shaping or more stylistic polish, we can guide you to the workflow that adds that level of refinement.

Client Story: Human Resources & A Compliance Nightmare

Picture an HR director who thought MTPE wouldn’t just be the fastest choice – it would also cut enough from the budget for their team to go to the next big HR conference.

Translating with AI looked straightforward. Click a button, and it translates the on-screen text. With tight timelines and budgets getting slashed, the team decided to use the AI translation feature without deeper localization or a professional human review.

Button clicked. Translations done.

Problems started appearing with their internal bilingual reviewers. Basic concepts were translated correctly, but the message did not land the way it needed to. The style felt off. The terminology did not match what the brand usually uses. There wasn’t a natural conversational flow – it felt instructional and impersonal. Several important phrases lost their intended meaning… because the nuance was never adjusted by a fully human workflow.

Then the translation went for compliance review. Where they got the news there is no way the courses would pass a compliance audit.

This is exactly why we explain that post-delivery changes based on preference or brand style can lead to a revised quotation. MTPE works well for accuracy and clarity, but it does not always provide the level of localization needed for complex concepts. When you know that ahead of time, you can choose the workflow that protects your timeline, your budget, and your message.

Common Pitfalls And How to Avoid Them

• Overreliance on Raw MT: A team rushing a product update once relied on raw machine translation because the output looked fine at first glance. They skipped post-editing to save time and moved straight to publication. Days later, users reported confusion because a key concept had been translated literally and lost its intended meaning. The cleanup took far longer than a simple review would have. Even strong MT needs a human pass to prevent these avoidable setbacks.
• Inadequate Glossaries: A global company discovered that outdated terminology can derail a project without warning. Their teams used different names for the same features, and the machine produced a mix of all of them. Reviewers flooded the file with conflicting edits, which slowed everything down and created unnecessary frustration. Once they updated their glossary and kept it current, the machine output immediately became more consistent. A living termbase saves everyone time and protects brand clarity.
• Quality Blind Spots in Low-Resource Languages: An organization expanding into a new region trusted MT to handle training materials for a low-resource language. The engine struggled with two similar terms that carried very different meanings, and a safety instruction ended up incorrect. A native reviewer caught it before release, which prevented confusion. The experience showed that MT performance varies widely across languages. Early involvement from native specialists avoids risks that engines cannot always detect.
• Post-Editor Fatigue: A linguist working long hours on MTPE started the day sharp and attentive, but began skimming as fatigue set in. Small inconsistencies slipped through, and the tone drifted away from the brand voice. The final text was technically correct but lacked polish. Rotating linguists and setting realistic throughput targets fixed the issue quickly. Quality stays higher when reviewers are not stretched beyond their limits.

Case Study: Course Localization into Spanish

If you’re looking into AI and MTPE for your organization, Interpro can guide you through the process to help avoid missteps and make sure your translations are accurate and reliable. When Kinetic Instruction came to us, they needed to translate eLearning modules quickly but still maintain quality. We worked with them to build a custom workflow, aligning on terminology and using human reviewers to ensure everything sounded natural and on-brand. Our team handled different file types, flagged formatting issues early, and made sure everything was ready to launch. In the end, they got translations that were both fast and effective.

Learn more about how we did it for Kinetic Instruction.

Frequently Asked Questions About MTPE

Is AI + Machine Translation Post-Editing suitable for technical documents?

Yes, the technical documents are a great fit for an AI + MTPE workflow. Intepro would provide complimentary consultations to understand your language goals, markets, and challenges. Then we would provide advice and a workflow to support technical document, or any other material you need to translate.

How do I know if my content is MT-ready?

Generally, content with short, well-structured sentences and consistent terminology boost MT accuracy. Interpro will always conduct a translation assessment or quality estimation to provide consultative advice and recommendations for when you should use AI translation and when to skip it.

Will my data remain confidential?

Interpro uses industry-standard, secure, private MT engines to protect the confidentiality of your sensitive and proprietary materials. Interpro has high-quality standards that extend to only using the best technology to keep our clients protected.

What languages benefit most from MTPE?

Mature Language Pairs (such as EN->ES) will see the biggest speed gains, but even lower-maturity language pairs improve with translation and training.

Can MTPE handle highly creative marketing copy?

It can, but it’s much less likely to create the same experience that will resonate with your target audience. Consulting with your translation partner and transcreation will deliver a better localized experience in your authentic brand voice. Our consultants can help you make the decision.

Ready to get started with AI + MTPE?

AI + Machine Translation Post Editing marries machine speed with human finesse, slashing turnaround times, controlling budgets, and unlocking new markets. Ready to elevate your global content with confidence? Contact Interpro Translation Solutions today and discover how we can help you turn raw machine output into polished, publish-ready prose.

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