The Hidden Risk of DIY AI Translation
Fragmented Tools, Fragmented Brand Voice
When you use AI tools independently with public models, you can often lose control over brand tone and terminology. And once inconsistencies reach different markets, they're costly to undo.
For example, if a regional marketing team quickly translates campaign slogans with a public AI tool, the system might ignore approved terminology or miss cultural nuances. The result could be conflicting taglines or even unintentional mistranslations that damage the brand’s image. With no shared glossary or multilingual brand guidelines, it becomes impossible to ensure that every market communicates in the same voice or complies with corporate standards.
These inconsistencies are more than stylistic; they create governance and compliance risks. Each time a team member uses a public tool, there's a risk of exposing confidential data or errors that break internal content guidelines. That’s why enterprise translation requires more than just speed. It demands systems that embed expertise-connecting tools with additional improvements like human review, quality metrics, and centralized governance.
That's why using the right tool, or partnering with an expert in implementing an AI translation platform, can help. Leena offers a telling analogy:
"If a lawyer and a layman both ask ChatGPT to find a legal reference, the lawyer will get better results, because they know how to ask. The same goes for translation. Without linguistic expertise, you risk losing meaning."
Leena Peltomaa
The Governance and Compliance Gap
Unmanaged use of AI translation tools can also create serious governance and regulatory risks.
Beyond accuracy, governance means having visibility and control over every step of the translation process: from how data is collected and stored, to who has access to it, and how results are audited. Enterprises operating in some markets now need documented accountability chains showing what content was generated by AI, what was reviewed by humans, and how linguistic assets are protected.
Compliance frameworks such as ISO 17100 and ISO 27001, together with regional regulations like the EU AI Act, now demand demonstrable transparency. That can include knowing which models are used, how training data is sourced, and how bias or security risks are mitigated.
Without proper oversight and governance controls, businesses risk not only inaccuracies but also breaches of data protection, intellectual property misuse, and reputational harm, a serious concern when handling sensitive or public-facing content.
