What Makes Translation So Complex?
Translation takes a deep understanding of context, culture, and communication, not just dictionary definitions. The most common translation problems stem from three core areas:
- Cultural context that doesn’t transfer between languages
- Linguistic structures that have no equivalent in the target language
- Technical constraints that limit accuracy
These problems of translation can derail entire projects, lead to misinterpretation by readers (or viewers in the case of poorly translated subtitles) and potentially cause rather costly mistakes for businesses.
From dealing with idioms that make no sense when translated literally to compound words that don’t exist in your target language or cultural references that fall flat with international audiences, understanding these translation challenges is the first step toward overcoming them. Here are 11 main problems of translation that every translator faces, and what you can do to avoid them.
Cultural Issues and Linguistic Translation Problems
Cultural issues are some of the most frustrating challenges translators encounter. When cultural references don’t exist in the target culture, even experienced translators might struggle to find equivalent expressions that resonate with their audience. A joke that’s hilarious in one culture can be completely incomprehensible in another, and sarcasm often loses its punch when cultural context disappears.
Idioms present another major headache. English expressions like “kick the bucket” or “piece of cake” have no logical equivalent in most languages, forcing translators to (hopefully) skip the awkward literal translation and find culturally appropriate alternatives that convey the same meaning. This becomes even more complex when the idiom carries emotional weight or appears in marketing copy where tone of voice plays a big role.
Compound words can present hurdles, especially when translating from languages like German or Dutch into English. These languages routinely combine multiple concepts into single words that have no direct equivalent in the target language. Translating compound words sometimes requires lengthy explanations that disrupt the flow of the original text, or creative solutions that just may not capture the full meaning.
Figures of speech and linguistic structures add yet another layer of complexity. Some languages use grammatical constructions that simply don’t exist elsewhere. Turkish, for example, has a grammatical category called evidentiality, which marks how the speaker knows something. When a verb and preposition combination in one language expresses a concept that requires an entirely different grammatical approach in another language, translators have to reconstruct entire sentences while preserving the original intent.
Technical translation brings its own set of problems, too. Documents full of technical jargon often contain terms that have no established equivalent in the target language, so translators either have to create new terminology or use lengthy descriptions. This is even more challenging in rapidly growing fields like generative AI or biotechnology, where new concepts emerge faster than translation standards can develop.
The translator’s job is even more difficult when dealing with context-dependent meanings. The same word can have completely different meanings depending on the industry, audience, or cultural setting. Without proper context from the source text, even professional translators might be prone to producing translations that are technically correct, yet out of place for the intended use.
Technical and Process Challenges of Translation
Machine translation has come quite a long way. AI translation is changing the entire language industry, and can now produce results that rival human translators for many types of content. But this technological leap has created entirely new problems of translation. Clients often now expect instant, perfect translations at a miniscule fraction of traditional costs, not realizing that even the best AI still struggles with nuanced content.
The biggest challenge now is knowing when AI translation is good enough, and when you still need human expertise. AI handles straightforward business documents remarkably well, but doesn’t catch all those cultural subtleties that matter for marketing copy, for example. The problem is that AI-generated text often looks perfect on the surface, making it harder to spot these subtle but critical errors.
Translation memory systems, while helpful for consistency, can also become a trap when they store outdated and incorrect translations. When previous work contains errors or terminology that’s no longer current, these systems spread those mistakes across new projects and, nowadays, across large language models trained on them. In theory, translators and language service providers need to regularly evaluate whether stored translations still make sense. The problem with that is project timelines rarely allow for such a level of granular review.
Source text quality is one other level of complexity that technology can’t solve. When original documents are poorly written, contain errors, or lack clear structure, even AI translation tools struggle. Human translators face the same impossible choice they always have: translate the problems faithfully or fix them and risk changing the author’s intent?
Project coordination remains a persistent headache. Multiple team members working on large translation projects might use different terminologies for the same concepts, leading to inconsistent results. Translation services try to solve this with style guides and glossaries, but these tools only work when everyone actually follows them.
Struggling with AI-generated content? Get in touch and we’ll clean it up!
Last, time pressure continues to compromise translation quality, regardless of the tools available. Rushed work leads to mistakes that would normally get caught during proper review cycles. Quality translation processes need adequate time for research and revision, especially for specialized content that requires a rather deep level of subject matter expertise.
These translation challenges aren’t going away anytime soon, even as AI continues to improve. The reality is that most clients still don’t understand what causes translation projects to fail, which means the same problems keep happening over and over. If you’re planning a translation project, don’t assume that throwing AI at the problem will solve everything. You’ll get better results when you account for cultural complexity, give translators proper context about your source material, and build in time for the research and revision that quality work requires.
