Find the repetition before choosing the technology
A useful first AI project begins with a specific piece of work. Look for a task that a team repeats often enough to understand its inputs, decisions and handoffs. Finding the right policy, preparing a document summary or checking an incoming request can be a better starting point than a broad ambition to transform an entire department.
Ask someone who performs the task to walk through a recent example. What triggered it? Where did the information come from? Which parts were straightforward, and where did judgement matter? Follow the work as it happens, including the spreadsheet, message or manual step that a process diagram may leave out.
Give the project a clear beginning and end
Write a short description of the workflow in plain language: when a request arrives, use these approved sources to prepare this output for this person. Define what the system may do and where its responsibility stops. An assistant that prepares a supplier checklist has a different boundary from a system that approves a supplier.
Keep the first scope narrow enough that people can recognise a good result. Limit the document types, user group or decision being supported. That boundary makes exceptions visible and gives the team room to improve the workflow without changing several business processes at once.
Choose an owner who can judge the output
Name the person responsible for the business outcome, alongside the people responsible for implementation and access. The process owner should be able to explain the expected result, identify unacceptable mistakes and decide when the workflow needs a human handoff.
Bring that person into the design early. Their examples of ambiguous requests, outdated documents and missing information are as useful as examples that go smoothly. A first project needs a clear route for feedback and correction, not just an enthusiastic sponsor.
Make success observable
Agree how you will compare the new workflow with the current one. You might observe the time needed to prepare a reviewed answer, the number of incomplete submissions or how frequently someone has to find a missing source. Choose a small set of measures that describe the work rather than activity alone.
Collect a baseline before the pilot. Decide which examples will be used for evaluation and include cases that should be declined or escalated. A fast answer is useful only when it is suitable for the decision the team needs to make.
Expand from evidence
Run the pilot with the people who will use it. Review useful results and failures together, then adjust the sources, instructions or handoffs. Keep a record of what changed so that improvements can be distinguished from changes in the examples being used.
When the workflow is reliable enough for its agreed purpose, decide whether to widen the user group, add another source or introduce a further action. Take one step at a time. The result of a good first project is a useful operating pattern that the team understands and can maintain.
A Century guide. Use these questions as a starting point, then agree the details for your own workflow and environment.