AI automation is genuinely valuable for the right process — and a waste of budget for the wrong one. Before automating anything, it's worth checking whether a process actually meets the bar.
1. The process is repetitive and rule-describable
If you can explain the process to a new hire in a checklist, it's a strong automation candidate. If every case genuinely requires deep judgment that varies wildly, automation will struggle — though even then, an agent can often handle the routine 80% and escalate the rest.
2. Someone is doing it manually, often
Automation pays off fastest on high-frequency tasks. A process done twice a year isn't worth automating regardless of how tedious it is; one done fifty times a day almost always is.
3. The data it needs already exists somewhere accessible
Automation needs to read from and write to your actual systems — CRM, inbox, database. If the information lives in someone's head or a system with no API, that's a prerequisite to solve first, not a blocker to give up on.
4. Mistakes are recoverable, or you can add an approval gate
Not every process needs full autonomy on day one. High-stakes actions — sending money, deleting records — should have a human approval step even in an otherwise automated flow. Start with an agent that drafts and a human that approves; expand autonomy once you trust the output.
5. You can measure whether it's working
- Is there a clear success metric (tickets resolved, leads qualified, hours saved)?
- Can you compare before-and-after performance?
- Is someone actually going to review the automation's output regularly?
If you can't measure it, you won't know if it's working — and you won't catch it quietly breaking.
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