Most teams considering AI automation get stuck at the same point: there are dozens of processes that feel like candidates, and no clear way to pick one. The good news is that the starting point is usually obvious once you know what to look for.
Look for volume and repetition, not complexity
The best first project isn’t the most impressive one. It’s the task your team already does the most often, in roughly the same way each time. A workflow that runs twenty times a day and follows a predictable shape will pay back faster than a rare, judgment-heavy process, even if the rare one sounds more interesting to automate.
Write the process down before you touch any tooling
Before evaluating platforms, write out the current process step by step, including the messy exceptions. That document becomes your specification. It also usually reveals that part of the process is broken independent of automation, which is worth fixing first.
Once you have one workflow mapped and one clear owner for it, you’re in a position to automate something real instead of a hypothetical. Everything else, including which tools to use, gets easier to decide from there.
