guide · AI & Automation
Where automation pays off, and where it does not
Most businesses are told they should be using automation and AI. The harder question is where. Starting from the tool almost always ends in scattered experiments. Starting from the work usually ends somewhere useful.
List the work first
Write down the tasks that people repeat: entering the same details in two systems, chasing an approval, sorting incoming documents, answering the same question. Do not worry yet about how any of them could be automated.
Judge each piece
For each task, three questions decide whether it is worth attention.
- How often does it happen, and how long does it take each time?
- Is it the same every time, or does it need judgement?
- What goes wrong when it is done by hand: delay, error, or both?
Prefer the simplest thing that works
A rule that always does the same thing is more reliable than a model that mostly does. Connecting two systems so information is entered once often removes more work than any AI tool would. AI earns its place where the input is untidy and a person would otherwise have to read and decide.
What does not pay
Tasks that happen rarely, tasks that change constantly, and tasks whose value lies in a person's judgement rarely repay the effort of automating them. Every automation also needs an owner and limited access, so a small task can cost more to run than it saves.
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