What it means
On-premises AI means running AI models on hardware that the organisation owns or directly controls, such as its own data centre or a dedicated government computing centre. Data does not need to leave the organisation's infrastructure for processing.
Real-world example
A federal authority wants to use AI to help staff search documents classified as "VS – Nur für den Dienstgebrauch". Because these documents may not be processed by external cloud services, the authority runs an open-weight language model on servers in its own data centre.
Why it matters for AI adoption
On-premises operation gives more control over data and dependencies, which matters for sensitive information. But it requires investment in hardware, skills, security and maintenance, and the models that can be run locally may be less capable than the largest cloud models. Control does not automatically mean better security.
Questions to ask
- Do we have the hardware, skills and budget to operate and update models ourselves?
- Which model can we run locally, and is it good enough for this task?