Start with the work itself

Start with the work, not the tool. Look for repetitive tasks, information that is hard to find and steps where the team spends time copying data between systems.

For example, AI can help organize orders arriving through different channels, find answers in a collection of documents or prepare a first content draft for human review. Each use needs suitable data, clear limits and a way to check the result.

A small, verifiable application teaches more than a big promise.

Test before scaling up

Choose one small task, decide how to measure improvement and test with the people who do the work every day. Expand carefully if the result is useful and reliable. Otherwise, refine the idea before investing in a larger solution.

AI can also be part of a website, application or system. The important thing is that the technology solves an identified need and that someone is responsible for monitoring what it produces.