Artificial intelligence has fundamentally changed the economics of translation. For organisations operating across borders the speed and efficiency of AI are genuinely transformative. Whether they’re managing multilateral contracts, rolling out global product launches, or communicating with regulators in multiple jurisdictions, everything moves so much faster. But speed without security is not a long-term solution. In fact, it might very well be a liability.
As AI translation tools become embedded in enterprise workflows, a critical question is emerging in organisations across the globe: what exactly happens to our data when we use said tools?
The hidden risk in consumer AI tools
Many employees already use publicly available AI tools to translate internal documents: a contract clause here, a supplier email there. It feels harmless. In practice, it can represent a serious data governance failure.
Consumer-grade AI translation tools typically process and may retain user inputs to improve their models. This means that confidential pricing terms, personal employee data, or legally sensitive correspondence could end up feeding a system whose data practices you have never reviewed, let alone approved.
Under the General Data Protection Regulation (GDPR), organisations (data controller) are responsible for what happens to personal data, regardless of which third-party tool (data processor) processed it. A translation tool is not exempt from that accountability. Neither is the organisation that deployed it.
This is not a hypothetical concern. In 2023, Samsung made international headlines when engineers used ChatGPT to help debug code and, in doing so, inadvertently uploaded proprietary source code to external servers. The tool processed the data according to its standard terms. Samsung had not anticipated this and the breach prompted an internal ban on generative AI tools.
Make no mistake, this was not an isolated incident. In February of this year, cybersecurity company Cyberhaven issued its AI Adoption & Risk Report. According to this report, 39.7 percent of all AI interactions involve sensitive data. On average, employees input sensitive data into AI tools once every three days. The lesson is clear: the convenience of AI and the requirements of data security are not automatically aligned. But they can be.
What "secure AI translation" actually means
Secure AI translation is not a single action, but consists of structural solutions to keep data safe. It is a set of architectural, contractual, and operational commitments that ensure your data remains under your control throughout the translation process.
For enterprise clients, this means asking the right questions of any language service provider (LSP) or technology vendor:
- Where is the data processed? Reputable providers offer options for in-region processing — keeping EU data within EU infrastructure, for instance. This is particularly relevant for organisations in regulated sectors such as finance, pharmaceuticals, or public administration, where data residency requirements are explicit.
- Is the data used for model training? A secure setup guarantees that your content is never used to train or fine-tune AI models — neither the provider's own nor those of any upstream technology partner. This should be specified in a Data Processing Agreement (DPA), not just referenced in marketing copy.
- Who has access? Zero-retention architectures and role-based access controls ensure that only authorised personnel — and no one else — can interact with your content. This extends to subprocessors and cloud infrastructure partners.
- Is transmission encrypted? End-to-end encryption, both in transit and at rest, is non-negotiable for enterprise-grade deployments.
More than Compliance
It would be tempting to frame secure AI translation purely as a compliance checkbox, something the legal team worries about while everyone else gets on with business.
Trust is a genuine commercial asset. When your organisation communicates with clients, partners, or regulators in their language, you are not just conveying information, you are projecting competence, care, and professionalism. A data breach tied to a translation vendor does not just create regulatory exposure; it damages the relationship you worked to build.
For European enterprises in particular, where GDPR has raised the baseline expectation of data stewardship, clients and partners increasingly ask about your third parties' data practices, not just your own. Secure AI translation is part of that answer.
The right partnership makes the difference
Not all AI translation is created equal, and not every provider has made the investment required to deliver genuine enterprise-grade security alongside AI-driven efficiency.
At ELAN Languages, data security is of the utmost importance. ELAN AI Bridge, our custom-built AI infrastructure, was created with this in mind. As a content and language partner, secure workflows and trust are paramount. Our three main pillars of data protection?
- Data is never stored and used for other purposes
- Data is encrypted. Even if it your data is intercepted, it is completely useless for a third party.
- Our model-agnostic approach means that we select the best possible option for your existing security processes and needs.
Are you increasingly using AI in your organisation for your communication and translation processes but are you worried about your data security? Get in touch with Johan Noël via johannoel@elanlanguages.com or +32 11 43 47 64 to discuss how you can upgrade your data protection with a model-agnostic infrastructure that works with your needs and workflows.