How to Choose the First Process for AI Automation.
The strongest first use case is not the most ambitious one. It has repeated work, accessible data, bounded consequences, a measurable baseline and an owner who can change the process.
Start where the work is repeated and written down
A good first candidate happens many times a week, follows a describable rule set, and already leaves a trail in a system. If nobody can write down how the work is currently done, automation will encode confusion rather than remove it.
Check the cost of being wrong
Suitability is a function of consequence. A misrouted internal request is recoverable; a wrong clinical or credit decision is not. Choose a first process where an error is visible quickly, correctable cheaply, and never harmful to a customer.
Confirm the data is already good enough
The workflow must be able to read what it needs from a system of record, not from a spreadsheet somebody maintains by hand. If the data needs a project to become usable, that project is the real first phase.
Make sure someone owns the outcome
Every automated workflow needs a named operational owner who sees its output, reviews the exceptions and can switch it off. Without that person, nobody notices when quality drifts.
Pick a repeated, written-down, low-consequence workflow with usable data and a named owner. Prove it, then move up in consequence.