Where should your business AI live?

A subscription or cloud service is usually the easiest way to try a job. You can start with one person and a small, non-sensitive sample. Running AI on a server you control gives you a different set of responsibilities. It does not make those responsibilities disappear.

Compare two complete setups

Write down where the model runs, where your documents live, who can see them and which services the workflow calls. A model running in your office can still send data to a cloud tool. A cloud product can have controls worth evaluating. Look at the actual setup rather than its label.

Cloud: less to maintain yourself

Ask what is included in the subscription or usage bill, what the limits are, and how your team will work when the service is unavailable. Check the provider’s data terms for the exact account and service you plan to use. Do not assume every plan has the same terms.

Your own server: someone owns the upkeep

Budget for hardware, power, backups, updates and the person who diagnoses a failure. Test the model on your actual job before buying equipment. A model that fits on the machine may still be too slow or too inaccurate for your working day.

What happens when the internet drops?

List every step in the job. Reading a local file might work offline. Fetching an email, checking an online calendar or sending an answer might not. Try the full workflow with the connection disabled before calling it an offline solution.

A useful first decision

Start with the simplest setup that meets the job’s data and reliability needs. Keep a manual fallback. Only take on a server when its benefits are concrete enough to justify owning it.

This is a decision framework, not a benchmark or a claim about a particular hosting provider. For customer data, get the supplier’s terms in writing.