ChatGPT in the company: 5 data protection traps — and how to avoid them

Employees have long been using public AI services — often without management knowing. That is understandable, because the tools are helpful. In a corporate context, however, risks arise that you should be aware of.

Trap 1: Company data in the prompt

Anyone who copies a contract or an internal protocol into a public AI tool gives that content away. Countermeasure: clear rules on which data must never go into external services — and an internal alternative that runs locally.

Trap 2: Unclear data processing

Where are the inputs stored, for how long, and are they used for training? With many services this is hard to trace. Countermeasure: providers with EU processing and a data processing agreement — or a solution in your own house from the start.

Trap 3: No traceability

Public models answer without a source. In case of doubt, no one knows what a statement is based on. Countermeasure: systems with source references (RAG) that make every answer verifiable.

Trap 4: No roles and permissions

A general AI service doesn’t know your permission structure. Everyone potentially sees everything. Countermeasure: a permission concept that controls which knowledge sources are available to whom.

Trap 5: Shadow IT

If there is no approved solution, employees fall back on their own tools. Countermeasure: an official, privacy-compliant offering that is good enough that no one needs to reach for alternatives.

The common denominator

All five traps have the same root: control is lost as soon as data leaves the house. A locally operated AI that makes your knowledge usable with source references and a clean permission concept closes these gaps — without you having to forgo the benefits of AI.

This is not an argument against AI. It is an argument for introducing it properly.