How to choose your first AI project
Quick answer: Choose a repeated task with clear inputs, a useful output, and a person who can check it. Test the smallest version against a saved template before connecting live systems.
Start with the task you can explain in one sentence: “When this arrives, we turn it into that.” A clear input and output make a pilot easier to test.
Look for repetition, not excitement.
A frequent, familiar task gives you examples to learn from and a baseline to compare against. Drafting replies from an approved FAQ is easier to evaluate than asking a system to “improve customer experience.”
Choose something a person can check.
You should know what a good result looks like before trying to produce it faster. Name the reviewer and the checks: correct facts, appropriate tone, complete next steps. If nobody can reliably judge the result, clarify the process first.
Try the simpler answer, too.
Sometimes a saved reply, a checklist, or a better form removes the friction. Test that option alongside an AI draft. A useful improvement does not have to involve AI.
A manageable first scope: Draft replies to one type of inquiry from approved business information. A person reviews every reply and sends it manually.
Keep the pilot reversible.
Begin with public, invented, or appropriately sanitized examples. Keep the current process available. A first experiment should help you learn before you connect live customer systems or promise automatic action.
Define the stop condition.
Stop or revise the pilot if important facts are wrong, reviewers cannot catch mistakes, or checking takes longer than the original task. Choosing not to automate can be a useful result.