Which processes should you automate first?

Automation and artificial intelligence promise a lot, but the real value shows up when they're applied to the right process. Before choosing a tool, choose the problem carefully.

Signs of a good candidate

• It happens often: daily or weekly, not once a quarter.
• It follows fairly clear rules, even if there are exceptions.
• It takes up valuable people's time with low-value work.
• It involves copying information between systems, emails or documents.
• Manual errors are costly: rework, complaints or losses.

Signs it's not time yet

• The process changes constantly, or nobody can describe it clearly.
• It rarely happens and the savings would be minimal.
• It depends almost entirely on an expert's judgment.
• The data you need doesn't exist or isn't usable yet.

In these cases, the first step is usually to organize the process or the data, not to automate it.

How to prioritize

For each candidate, estimate three things and start with the one that combines the most impact with the least complexity:

• Impact: how many hours it takes each week and how many people are involved.
• Risk: how much an error costs when it happens.
• Complexity: how many systems, rules and exceptions are involved.

What about artificial intelligence?

AI is especially useful when the process involves language or documents: classifying requests, extracting data from invoices, summarizing information or answering common questions. For fixed rules, traditional automation is usually simpler, cheaper and more predictable. And where mistakes are costly, a person should review the uncertain cases.

Start with a pilot

Pick one process, measure the baseline (time, volume and errors), automate a well-scoped part and compare. A well-measured pilot tells you whether to scale and gives you the arguments to do it.