The difference between generic translation and domain-specific translation is the difference between "mostly right" and "precisely right." In safety-critical training, that difference matters.
The Problem with Generic Translation
General-purpose translation engines optimise for the most common meaning of words and phrases. "PPE" might be left untranslated, transliterated phonetically, or translated as a generic phrase. "LOTO" (Lockout/Tagout) is unlikely to be recognised at all. "Permit to Work" might be translated literally rather than using the established term in the target language.
For casual communication, this is acceptable. For safety training where a mistranslation of a procedure name could lead to confusion about which procedure is being referenced, it is not.
How Glossaries Work
A saved glossary is a list of term pairs: the source term and its correct translation (or a definition that guides the AI to the correct translation). When the glossary is loaded into a session, the AI translation engine gives these terms priority — using the glossary-defined translation instead of its default choice.
Building Effective Glossaries
The most effective glossaries focus on: industry-specific acronyms (PPE, LOTO, COSHH, RAMS), procedure names (Permit to Work, Toolbox Talk, Method Statement), equipment names (specific to the site or industry), and organisation-specific terminology (internal process names, project codes). A focused glossary of 20-50 terms dramatically improves translation accuracy for domain-specific content.
Organisational Assets
Saved glossaries become organisational assets that improve over time. As trainers identify terms that need consistent translation, they add them to the relevant glossary. The glossary grows in value with use, creating a continuously improving translation quality baseline for the entire organisation.