What it means in practice
Using public ChatGPT is like holding your important company meetings in a café on the main square. Your text and data travel over the internet to servers somewhere in the US. On-premise AI is the opposite: your own soundproof meeting room behind a closed door. The AI is installed directly on your company machine or a local server. Pull the internet cable out and your AI assistant carries on working with your data.
Why companies need to know this
- Full protection for sensitive data. Ideal for law firms, healthcare providers, accountants, and innovative companies that have to protect their know-how.
- Independence from the internet. It works even when your connection drops or a cloud AI provider has an outage.
- No usage fees. With local open-source models you are not paying per word processed, only once for the hardware the model runs on.
- Tailoring. You can fine-tune a local model to your specific company vocabulary without worrying that the data leaves.
An example from practice
An engineering firm designing patents for the automotive industry needed help analysing an enormous volume of technical documentation. For security reasons the owner strictly forbade uploading drawings to ChatGPT, to prevent industrial secrets leaking. Instead the company invested in a powerful server and deployed a local, on-premise model on it. Their engineers can now consult AI about patents without a single byte of data leaving the office walls.
In our company AI workshops we go through which kinds of process justify investing in your own local setup, and when a secure cloud version is entirely enough.