An AI roadmap is a plan for the problems to explore, the order of work and how your team will use and check the results.
Start with the problem
Look at issues such as slow reporting, repeated copying or missed follow-up. Choose a clear outcome and record what happens today so you can compare results.
Try a manageable first step
Pick a task with an owner and a sensible level of risk. Test whether AI helps before investing in a more complicated change; a simpler process may be enough.
Plan for the team
Include training, feedback, access, approvals and support. Use what you learn from the first trial to decide what, if anything, to do next.
Turn ideas into a sequence
List the work the team wants to improve and describe the result each change should achieve. Compare the likely benefit, the information required, the effort to implement it and the impact of an error. Choose a small trial with an owner and a clear review point.
After the trial, review what changed, including checking time and unexpected problems. Decide whether to improve it, stop it or expand it. Share the decision with the people doing the work so the plan stays useful as priorities change.
An example sequence
A team might first map how it prepares weekly reports and record the time and errors involved. Next it checks which source documents can be used, chooses a report owner and tests a few past examples with an approved tool.
At a review, the owner compares the draft and checking time with the original process and asks colleagues whether the output is useful. If important figures are unreliable or permissions are unresolved, the next step is to correct or stop the trial, not roll it out. Dates and costs remain estimates until tested.
Start with the AI readiness checklist if you are choosing a first project.
For more on helping a team build AI skills, see the UK government’s employer guide to AI upskilling.