The best first AI project is usually a task your team already understands. Look for work that happens often, follows a recognizable pattern and leaves someone copying information between tools.
Follow the work before choosing a tool
Ask a teammate to walk through one recent example. Where did the request arrive? What information did they need? Which decisions required judgment? Write down the steps, including the awkward exceptions. A workflow diagram that ignores exceptions is a poor starting point for automation.
Pick a narrow outcome
“Use AI in sales” is too broad to test. “Prepare a draft CRM update after a discovery call” gives you a specific input and an output someone can review. Start with one team and one type of call. Expand when the workflow earns that trust.
Keep approval close to the action
Let AI prepare a draft before it changes a customer record or sends a message. The reviewer should see the source material and the proposed action together. Define what happens when the information is missing or contradictory: pausing for review is a valid outcome.
Measure the whole process
Record how long the task takes today, including corrections. During the pilot, measure review time, mistakes and how often someone needs to take over. Time saved in drafting can disappear if checking the result takes longer.
Give the workflow an owner
Choose someone who can review failures, update instructions and decide when to stop the automation. A useful first project is small enough to maintain and clear enough to improve.