The most useful starting point for AI is not a tool. It is a task your team knows well: a recurring handoff, a pile of information to organise, or a question that arrives every day. Start by understanding that work before deciding what should change.
Start with the friction
Talk to the people doing the work. Ask which tasks repeat, where information gets lost, and which decisions need judgement. A simple process map can reveal whether the real need is better information, a clearer handoff or automation.
Write down the current process, including its exceptions. Record a baseline: how long the task takes, how often it happens and what a good result looks like.
Start with a useful problem, not a list of tools.
Choose a focused pilot
Pick a small, reversible use case with a clear owner. Avoid expanding the pilot into several unrelated workflows.
Agree what success means before building. A useful pilot has a defined input, an expected output, a review step and a fallback when the result is not good enough.
Keep people in the loop
Decide who reviews outputs, how corrections are recorded and when the process should stop for help. Make these decisions visible to the people who will use the system.
Use approved data and give the pilot only the access it needs. Treat mistakes as signals to improve the workflow.
Learn before you scale
Review the pilot with its users. Compare the result with your baseline and look beyond speed: does the work feel clearer, are corrections manageable, and is the output useful?
Keep what works, change what does not, and document the next iteration. A successful first project should leave your team with a better process and a clearer understanding of where technology belongs.
