Many companies start AI with the idea that looks best in a presentation: a chatbot that answers everything, or a model that forecasts sales. Projects like that often stall at the pilot stage because the data is not ready and the results are hard to measure.
A safer starting point is the work your team finds most tedious.
Four signs of a good candidate
- High volume. Work done dozens or hundreds of times a week makes a visible difference even if each instance saves only a few minutes.
- Rules you can explain. If a senior staff member can teach a new hire how to do it in an hour, a system can most likely be trained or programmed to do it too.
- The data already exists. Emails, invoice PDFs, or forms stored digitally are far easier to process than knowledge that lives only in people’s heads.
- A human checkpoint. Choose a process where the automated result can still be checked before it affects customers or financial reports.
Examples that often fit
Matching supplier invoices to purchase orders, routing incoming email to the right team, and extracting data from shipping documents often meet all four criteria.
Measure before and after
Record the time and error rate of the current process before automation starts. Without a baseline, it is hard to show that the first project deserves a second.
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