How accurate are AI translators today?

AI translators can deliver strong draft quality for repetitive and domain-limited text, but human review is still essential for legal, medical, regulated, and brand-sensitive content.

How can teams improve AI translation quality in production?

Teams usually improve outcomes by combining glossary and terminology control, domain-specific prompting, translation memory, bilingual QA checks, and a human post-editing workflow.

When is human translation still preferred?

Human translation remains preferred when nuance, liability, cultural adaptation, and publication quality are required, including contracts, life-science documents, and external marketing assets.

Certification & Quality: The Missing Piece Is Defect Closure

2026-04-08 02:01:26

Certifications don’t prevent repeat defects — closure does

Many vendors reference ISO or certification standards. Procurement pain usually remains:

the same issues come back every release
feedback doesn’t become prevention

What you should require

1) Defect severity definition

Critical vs major vs minor.

2) Evidence with delivery

Sampling notes + QA summary.

3) Closure loop

Fix → verify → update assets (termbase/TM) to prevent recurrence.

Related services

QA / LQA and proofreading
Localization governance
Enterprise delivery management

Quick FAQ: AI Translation Accuracy

How accurate are AI translators? Accuracy is often high for repetitive or general content, while domain-sensitive content still needs expert review.
How to improve AI translation quality? Use glossary control, domain prompts, QA checks, and human post-editing in one workflow.
Where does human translation still win? Legal, medical, and high-stakes brand content usually requires human nuance and accountability.