Finding the Work Worth Automating

Ask your team which questions they answer over and over, and which details they copy from one system to another. Write down three to five of those jobs. Each one should have a clear start and a clear end, like "check whether an order has tracking."

Jobs that happen often, follow the same steps and use records you trust. A five-minute task done 30 times a day costs more time than a one-hour headache once a week.

Multiply how many times it happens by the minutes it takes, then divide by 60. For example, 20 order-status emails a day at 6 minutes each, over 22 working days, is 44 hours a month.

No. It is the time the job takes today. Someone still has to check the results, and some cases will still need a person. You only know the real saving after you test it.

No. If a job is the same every time, a simple rule or a spreadsheet formula may be enough. AI helps when the details change each time, like POs in different layouts or supplier emails written in different ways.

Anything where a mistake costs money or upsets a customer: special pricing, credits, disputed invoices, promises about late orders. Software can pull the facts together. A person makes the call.

Fix them first. If two price lists disagree, no tool can tell which one is right. Pick one source everyone trusts, then come back to the job.

Check five things: records you trust, access to the systems it uses, a clear idea of a correct result, a list of cases that go to a person, and someone to own it and check it. If any of these is blocked, fix that first.

Score each one from 1 to 3 on value, effort, risk and readiness. Do not just pick the highest total. A smaller job that is ready today is often a better start than a bigger one still waiting on access.

Try it on past requests first, without sending anything or changing records. Have someone check every result. After about four weeks, see whether it got the answers right and saved time, counting the time spent checking.