AI-assisted translation systems offer impressive opportunities to speed up multilingual processes – but their effectiveness depends crucially on carefully considered terminology management. Only by systematically managing specialist terminology can a company fully harness the potential of AI whilst preserving its brand’s linguistic identity.
What is terminology management?
Definition:
Terminology management is the systematic compiling, maintenance and use of technical terms to ensure consistent communication across all languages.
Why it’s important:
- It defines how a company talks about its products, services and brand values
- It prevents inconsistencies and a loss of quality in translations
Example:
The German term “Leitung” can be translated in various ways in technical documentation, for example as “line” or “cable”. But it can also be rendered “head” in a business sense to refer to the person in charge of a department.
This person is responsible for the overall management, organisation and daily operations of the department under their control, acting as the primary bridge between their own team and upper management.
Centralised terminology management for AI translations ensures that the same, brand-compliant translation is always used.
Why terminology is crucial in the translation process
A lack of systematically managed terminology can lead to the following problems:
- Inconsistent translations of the same term
- Increased effort required for corrections
- Increasing costs for multilingual content
- Inconsistent brand communication
- Misunderstandings among customers or users
Key message:
Consistent terminology management is crucial for ensuring quality, efficiency and brand identity in translations.
Why terminology is becoming even more important in the age of AI
LLMs and generative AI programs enable rapid translations, but they are not familiar with company-specific terminology.
- Without clearly defined terms, inconsistencies arise
- Quality control and branding may suffer as a result
- Human expertise remains indispensable
Terminology management is essential to ensuring that AI-assisted translations are consistent and brand-compliant.
How AI makes terminology work more efficient
AI can support terminology work, but it can’t replace it. Typical applications:
- AI terminology extraction: Automatic identification of relevant technical terms from texts
- Establishing terminology databases: Suggestions for synonyms, variants and metadata
- Terminology checks: Assistance with revision, taking the overall context into account
Please note:
Final validation by human experts is always required.
The limits of AI in terminology work
LLMs can:
- “Hallucinate” terms (they can generate plausible but incorrect terms)
- Overlook customer-specific requirements
- Put confidential data at risk if it is processed on public systems
In summary:
AI supports translators, but it isn’t a replacement for human expertise.
Best practices for terminology management in the age of AI
- Centralisation: Manage all terms in a central database
- Integration: Direct access for translators via CAT tools
- AI as an assistant: Assistance with research, data extraction and verification; final validation by humans
- Security-conscious: Process sensitive data only in systems that comply with data protection regulations
- Regular updates: Continuously adapt terminology to new products, markets or guidelines
Pro tip:
This approach ensures that translations are consistent, efficient and brand-compliant – regardless of the technology used.
Terminology as strategic corporate knowledge
Terminology is a company’s linguistic memory. It ensures that both man and machine speak the same language, builds trust, reduces errors and safeguards the quality of multilingual content.
Key message:
Companies that systematically maintain terminology and use it with the assistance of AI increase efficiency, consistency and brand value.
Frequently asked questions about terminology management and AI
What is the difference between a glossary and a terminology database?
→ A glossary is static. A terminology database is dynamic, centrally managed and directly integrated into the translation workflow.
Can AI generate terminology automatically?
→ AI can provide suggestions, generate synonyms and supply metadata, but it does not replace human validation.
Why is terminology crucial in LLM translations?
→ LLMs operate on a statistical basis, not in compliance with brand guidelines. Without standardised terminology, inconsistencies arise and quality suffers.
Conclusion
Terminology management is more important than ever in the age of AI. Used correctly, it combines human expertise with AI assistance, ensures consistency, achieves a coherent brand identity, and makes translation processes more efficient.
What next? Contact us to have your terminology professionally established, consistently maintained, and optimised with the assistance of AI.
