AI and GDPR for business
AI adoption in business is not only a quality question. It is also about where data is sent, what the provider can do with it and whether your organisation can document responsible use.
This guide helps teams use AI without losing control of privacy, customer data and internal documents.
Start with the data type
Separate information into risk levels before choosing tools. A generic marketing idea is very different from customer data, contracts, employee issues or health information.
A useful classification:
- public information
- internal but non-sensitive information
- confidential business information
- personal data
- special categories of personal data
The higher the risk, the stricter the requirements for vendor terms, access control and logging.
Free tools are rarely enough
Free AI tools are useful for learning and low-risk drafting. They should not be the default for customer data or internal documents. Business plans and API agreements usually provide clearer terms, better controls and the possibility of data processing agreements.
Check whether data is used for training, where it is stored, whether a DPA is available, who has access and how data can be deleted.
Create a simple AI policy
A useful AI policy does not need to be long. It should state which tools are approved, which data must never be pasted into AI tools, and who can approve new use cases.
A short policy people actually read is better than a long document nobody uses.
Combine benchmark and compliance
The best model for a marketing draft may not be the right model for HR documents. Use benchmark results together with privacy, legal and operational requirements.