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Research · The Edit Distance Report · 2026

Where your translation team's time matters most

We measured 27 million translated sentences. People change about 8% of AI suggestions and 15% of machine translation.

Download the report (PDF)Read it online

Free. No form, no email.

How much people change
Context-sensitive AI suggestions8%
Plain machine translation15%
Context-sensitive suggestions draw on your translation memory, glossary and past corrections.
27 million sentences measured14 sectionsPublished by wxrks, formerly Bureau Works

Four numbers from the report

47%less editing than machine translation
84 of 100AI suggestions go out unchanged
42% to 16%editing, month one to month ten
98 of 100sentences pass review unchanged

The person who runs localisation

Your role matters more than ever

Editing a suggestion is only 7% faster per word. The time comes back in the reading, because most of it is already right.

So the work moves to deciding what gets read, what goes to review, and what the memory keeps. Whoever runs that flow decides how much time AI saves.

You run the flow

  1. 1SuggestAI suggests from your memory and glossary. 84 of 100 go out as written.
  2. 2ReadYou choose what gets a full read. Smells flags where meaning may have drifted.
  3. 3ReviewYou choose which passes run. Keep them where the risk is.
  4. 4KeepYou decide what the memory and glossary keep. As they fill up, editing falls.

Editing falls as the memory fills up

Average share of words changed in new accounts.

0%20%40%42%16%0510
Months since the account started

Never has 8% mattered so much

Half of all sentences go out untouched. The editing that's left is where a person's judgement changes the result.

How much people change, per 100 sentences
  • 52%Untouched
  • 13%Light, up to 5%
  • 8%Moderate, 5 to 15%
  • 13%Heavy, 15 to 50%
  • 14%Rewritten, more than half

It depends on the language

  1. Spanish (United States)9%
  2. Latin American Spanish13%
  3. Brazilian Portuguese14%
  4. Korean (South Korea)18%
  5. Spanish19%
  6. Japanese (Japan)20%
  7. Chinese (China)20%
  8. European Spanish21%
  9. Dutch (Netherlands)21%
  10. French (France)22%
  11. German (Germany)22%
  12. Canadian French24%
  13. Brazilian Portuguese → American English25%
  14. Italian (Italy)26%
Average share of words changed, by language pair, from English.

How we measured

Data
27 million sentences on the wxrks platform, August 2024 to September 2026.
Measure
Edit distance, the share of words a person changes before a sentence ships.
Privacy
Group numbers only. No client is named and no text was read.
Author
wxrks, formerly Bureau Works.

What the data does not show

  • It counts changes, not quality. Quality is the next study.
  • It is production data, not a lab test.
  • The learning curve follows accounts that stayed.

What's inside

  • 2024 against 2026
  • Editing by origin
  • The learning curve
  • Editing by language
  • Review and in-country review
  • Speed
  • Method and privacy

Questions

Is it free?

Yes. No form, no email.

What is edit distance?

The share of words a person changes in a suggestion before it ships. 0% means it was accepted as it came.

Can I share it?

Yes. Send the link or the PDF to anyone.

Bring it to your next planning meeting

Free, no form.

Download the report (PDF)Read it online

How we designed the Kenya page

We read the country's most visited websites and its culture scores, and let both shape the Kenya page.

  • Built like a clean landing pageThe top 10 here is mostly global sites like google.com, youtube.com and chatgpt.com, so the page follows the global pattern.
  • In British English, with ‘you’Short sentences, numbers first and no hype, the way B2B software sites here write.
  • Written for the teamIndividualism is 27 here, so the page talks to the team and makes sharing easy.
  • Balanced coloursIndulgence is 40 here, so the palette sits in the middle. Our own brand green stays out.

On the Kenya page, culture scores are a regional estimate.See the research behind these pages