AI & Automation / Insights
How to Choose Your First AI Workflow Project
Start with a narrow task, a clear owner, and a way to tell whether the result is actually useful.
Look for repeated work with a clear boundary
A useful first project often supports a task that happens frequently and follows an understandable process: locating policy information, drafting a response for review, or moving structured details between tools.
Avoid beginning with a vague goal such as “add AI to the business.” Name the user, the input, the decision, and the expected output.
Check the data and the owner
Someone needs to maintain the source material, review failures, and decide when the output is acceptable. If the information is incomplete or no one owns the workflow, model selection will not solve the problem.
- What source material can the system use?
- Who can correct outdated information?
- What should be reviewed by a person?
- What happens when the system is uncertain?
Prove value with a small pilot
Compare the pilot with the current way of working. Track measures that matter for the task, such as time to complete, answer quality, error rate, and the effort needed for human review.
Include examples that are messy or ambiguous. A demo built only around ideal inputs can create false confidence.
Design the production path early
Plan for access controls, cost, monitoring, and handover before scaling. A focused pilot should make those needs visible, not postpone them indefinitely.
Expand once the system reliably helps the people doing the work.
