AI in low resource languages, why quality drops and what it means for global medical translation
As organisations expand into new markets, multilingual content has become essential. However, when it comes to the use of artificial intelligence for translation, not all languages are treated equally. Recent findings from the European Language Council report on AI for translation and interpreting reveal a significant performance gap between languages that have abundant digital resources and those that do not.
For life science companies translating critical content such as IFUs, labels, patient leaflets, software interfaces, or clinical documentation, these gaps present real compliance and safety risks.
Below, we explore what the report reveals about AI limitations in low resource languages and how life science organisations can protect the quality and accuracy of their multilingual materials.
The invisible imbalance in AI training data
According to the report, AI translation models are trained primarily on English and a few Western European languages. As a result, their performance is far stronger for:
- English
- French
- Spanish
- German
- Italian
For low resource languages, the situation is very different. The report highlights that AI outputs show significant and unpredictable quality drops when the target language is one with limited digital content available for training.
These include languages from regions such as:
- Eastern and South Eastern Europe
- The Balkans
- Central Asia
- Africa
- South East Asia
For scientific and medical content, the consequences of these gaps are amplified. AI systems may struggle with terminology accuracy, sentence structure, context interpretation, or regulatory phrasing, which are all essential in life sciences.
What the report says about quality and reliability
The findings from the survey of 635 translation professionals across 55 countries make the issue clear.
Respondents noted that:
- Quality variations in low resource languages are substantial
- Errors are more frequent and harder to predict
- AI misunderstandings increase when content is technical or domain specific
- Terminology inconsistency is a recurring problem in specialised fields
These insights confirm what many project managers in regulated industries already experience: raw AI output is not reliable enough for medical content, especially when working across diverse global markets.
For organisations rolling out products internationally, this means that depending exclusively on AI can result in inconsistent documents and compliance concerns across different regions.
Why this matters in life sciences translation
Medical and pharmaceutical content leaves no room for uncertainty. A mistranslated dosage instruction, misinterpreted device setting, or incorrect warning symbol can put patient safety at risk or delay a product release.
Low resource languages increase this risk because:
- Medical terminology may be missing from AI training data
- Regional regulatory phrasing may not be recognised
- AI models may default to general language patterns that do not apply to medical contexts
- Inconsistent sentence structures can distort clinical meaning
Even when AI performs reasonably well for English or larger European languages, the same workflow will not be equally reliable for markets such as Serbia, Latvia, Kazakhstan, Vietnam, or Kenya.
This can create uneven quality across multilingual deliverables, which is one of the core concerns highlighted by the report.
How Novalins manages quality in low resource languages
At Novalins, we see the imbalance in AI performance as a reminder of why human expertise remains essential. Our approach is designed to guarantee accuracy and consistency for all languages, not only those where AI performs well.
Our process includes:
Expert medical translators in local markets
We work with specialists who understand both the medical domain and the linguistic characteristics of each target market. This ensures that every translation captures regional terminology, clinical phrasing, and regulatory expectations.
AI used as a tool, never as a standalone solution
AI can support productivity, but it is always combined with human review by a medical expert. This safeguards against errors that AI frequently produces in low resource languages.
Testing multiple MT and AI engines for each language pair
Before starting new projects, our team evaluates several machine translation and AI tools to identify which engine performs best for the specific language pair and document type. This ensures that the technology is tailored to the linguistic and technical requirements of each project rather than applying the same solution across all languages.
Structured quality control under ISO certification
Our workflow includes multiple layers of checking, validation, and final QA to ensure that all languages meet the same quality standard.
Consistency across multilingual projects
Whether a project covers 5 or 25 languages, we ensure that all versions are aligned in terminology, structure, and compliance, regardless of the underlying complexity of each language.
Why understanding AI limitations helps clients
For medical device and pharmaceutical companies entering global markets, being aware of AI limitations allows for better planning and risk mitigation.
Understanding these limitations helps clients:
- Avoid compliance issues in smaller markets
- Prevent terminology conflicts across multilingual documentation
- Ensure that patient and user materials remain accurate everywhere
- Maintain a consistent brand and regulatory image internationally
- Build workflows that are scalable and safe
In short, awareness of AI performance gaps makes multilingual strategy stronger, not more complicated.
Conclusion, a smarter use of AI begins with the right expertise
AI is a valuable tool in medical translation, but it is not an equal performer across all languages. The data from the European Language Council report highlights a crucial truth. Without human medical reviewers, AI alone cannot guarantee accuracy, especially for low resource languages where training data is limited.
By combining AI with expert linguists and strict quality controls, Novalins ensures that every language version, from English to Serbian or Vietnamese, meets the precise standards required in life sciences.
Would you like to see how our medical linguists and AI driven workflows work together across all languages?
Try a free pilot project with Novalins and discover how we ensure accuracy, consistency, and compliance.
References
- https://media.licdn.com/dms/document/media/v2/D4E1FAQHxzUOOqP2mCg/feedshare-document-pdf-analyzed/B4EZp9cAwcKkAc-/0/1763041091836?e=1764201600&v=beta&t=pPLV071TFRpMfczP1THcnVEqGJK7TfLf_bod4AqJwNc, Accessed November 23, 2025