What happens to your data when your teams paste it into a public LLM?

In brief.
In most companies, employees are already pasting business documents (specifications, price lists, elements of strategy) into consumer generative AI tools. This is shadow AI: the use of AI tools outside any governance framework. That data then leaves the perimeter you control: depending on the offer, it may or may not be used to improve the models, but in every case it passes through a provider’s servers, often subject to foreign law. A specification reveals your strategy, your prices, your weaknesses.

Shadow AI is already here

In most organisations, employees are already using public LLMs on business documents, with good intentions and without realising the implications. Banning it does not work in the long run: the tool is too useful and too accessible. The question for leadership is not “are my teams using AI on our tenders?” (the answer is yes), but “do I control where, how and with what data?”.

Three clarifications that frame the issue

One: “your data is not used to train our models” is a guarantee about use, not about jurisdiction; the data passes through the provider and can be demanded by foreign authorities. Two: the main risk is not always training, it is the leakage of intellectual property and competitive advantage. Three: for some sectors (defence, healthcare, the public sector, operators of vital importance), leaving the European legal perimeter is a regulatory or contractual red line. The mature response combines a clear policy with a tooled alternative for sensitive documents.

The Optivalue.ai approach

Optivalue.ai provides that alternative: a private AI for each customer, deployed on-premise or on a European sovereign cloud, not shared, with guaranteed deletion of data at the end of the contract. Your files leave neither your perimeter nor your jurisdiction.

Do the enterprise offers of LLMs really protect you?
They protect use (no training), not jurisdiction: the data stays with a provider subject to its own national law.

‍How should shadow AI be handled?
With an explicit boundary (what may go through a public LLM and what may not) and a sovereign tool for the other side.