AI Hallucinations: What They Are, Why They Waste Time, and How They Can Undermine Your Translations
AI hallucinations are not a theoretical risk in translation. They are already causing factual errors, invented terminology, and misleading claims in published content, often without anyone noticing until it is too late.
In translation, a hallucination is not a stylistic quirk or a slightly odd word choice. It is when an AI confidently invents meaning that does not exist in the source text. A regulation becomes more permissive than it is. A product claim becomes legally risky. A technical instruction quietly changes.
The problem is not that AI makes mistakes. Human translators do too. The problem is that hallucinations are plausible, fluent, and difficult to detect unless you know the subject matter and the source language well. In a translation context, that combination is particularly dangerous.
This is why AI translation works best when it is constrained, reviewed, and used with clear judgment about what content can tolerate risk and what cannot.
What Are AI Hallucinations and Why Do They Happen?
AI hallucinations occur when LLMs (Large Language Models) like ChatGPT, Claude, and DeepSeek produce information that sounds plausible but is not true.
This happens because AI systems do not “know” facts in the way people do. Instead, they predict words based on patterns in the data they have been trained on. If those patterns are noisy, inconsistent, or lacking in detail, the result can be a sentence that looks good but is completely wrong.
Think of it like a student who has not read the book but tries to bluff their way through a test; fluent, confident, and totally unreliable.
Why AI Hallucinations Waste Time and Money
While AI is meant to save time, hallucinations often lead to more work, not less. Someone still has to check, correct, or even rewrite what the AI has produced.
A 2024 study found:
- Employees spend an average of 4.3 hours per week verifying AI-generated content, which adds up to over 200 hours a year per person.
- This equates to around $14,200 in productivity costs per employee each year.
- 27% of communications teams have had to issue public corrections after publishing AI-generated content containing hallucinated errors.
(Source: AllAboutAI.com Hallucinations)
Even more frustrating, many people waste time chasing phantom errors flagged by AI tools. These are problems that do not actually exist. The result is a slow erosion of trust in the tools themselves.
Feeling uneasy about what AI might be getting wrong in your translations?
You’re not alone. Hallucinations don’t just waste time, they damage trust.
👉 Let Brightlines sanity-check your AI generated content
Real-World Example: AI Makes Up Legal Cases
This problem is not just theoretical. Attorneys in the US have made the headlines and been fined thousands of dollars for submitting legal filings created by ChatGPT that cite non-existent court cases. This has prompted Judges to express serious concern about the use of AI in the legal system.
(Source: Washington Post, June 2025)
These are extreme examples, but the principle applies widely. If you are not reviewing AI output carefully, you are taking a risk.
Real-World Example: AI Invents a UK Podcast Transcript
Journalist Sam Coates recently shared an incident on Sky News where AI hallucinated the entire script to one of his podcasts. The LLM claimed that it already had the transcript for a podcast that Sam had not yet uploaded. When challenged, it produced a transcript that looked very credible in tone and style but was entirely fictitious. Even more worryingly, ChatGPT doubled down when questioned, gaslighting Sam by stating categorically that the transcript had not been made up. Watch the video here.
Right now, millions of professionals are using AI to summarise, transcribe, or support content creation. The real-world implications of these confident falsehoods can be extremely serious.
Translation and Localisation: A Hidden Danger Zone
At Brightlines, we specialise in helping companies reach international audiences through accurate, culturally sensitive translation and localisation. That is why we are particularly attuned to the risks of AI-generated translations, especially when they make things up.
When AI hallucinates during translation, it can:
- Invent terminology
AI might generate a translation for a brand name, slogan, or technical term that does not exist in the target language, damaging clarity or making the message sound absurd. - Misrepresent facts
AI has been seen to subtly alter product descriptions or service terms, adding or removing capabilities the client did not intend to communicate. - Damage SEO with incorrect keywords
When AI translates keywords literally or makes them up entirely, it affects search visibility in local markets, potentially losing valuable traffic.
The hallucinations can be subtle. A product becomes ‘fully waterproof’ when it’s not. A service suddenly includes a lifetime guarantee or full refund policy that was never intended. These inaccuracies may seem small, but they can expose companies to legal and financial risks if customers start holding them to promises they did not realise they had made.
Even when the consequences aren’t immediate, the damage can be lasting. These aren’t just technical errors, they’re credibility killers. And once published, they can stay live for days, weeks, or even months before anyone realises something’s wrong.
Our Approach at Brightlines
At Brightlines, we have seen the effects of AI hallucinations first-hand through our own internal experiments.
We have encountered incorrect terms, made-up words, and, on more than one occasion, AI has tried to send us on wild goose chases for grammatical errors that simply did not exist. These hallucinations were not always obvious. Some looked entirely plausible on the surface, which is what makes them so risky.
Even more revealing, when questioned, AI will readily admit its own blunders. ‘You’re absolutely right to point that out’ ChatGPT exclaims without a hint of embarrassment. Ask it to justify a fabricated translation or explain a suspicious correction, and it may backtrack or offer a revised answer. But that only helps if you already know enough to ask the right question. That level of judgement still relies on human expertise.
That is why we would never rely on AI alone for any customer-facing translation or localisation work.
AI has its place; it can assist with first drafts, basic level terminology checks, or speeding up simple repetitive tasks. But without native-speaking human oversight, there is no guarantee that what the AI produces is accurate, appropriate, or trustworthy.
At Brightlines, every translation is reviewed and refined by professional linguists with sector-specific knowledge. We ensure your content is clear, culturally aligned, and fully credible, because your reputation should never be left to guesswork.
AI Is Powerful, But Not Plug-and-Play
AI hallucinations are not a reason to reject AI outright. They are a reason to use it deliberately.
For high-volume, low-risk content, AI-supported workflows can be efficient and cost-effective when paired with proper human review. For content that carries legal, technical, reputational, or commercial risk, fluent guesswork is not good enough.
The real decision is not “AI or human.” It is whether the content can safely absorb error, ambiguity, or invention. If it cannot, human expertise remains essential.
If you would like to discuss which parts of your content are suitable for AI workflows and where human-led translation is non-negotiable, we are happy to advise.
