What is the 30% rule in AI?
A rule of thumb that says start by automating the 30% of a workflow that is repetitive and low-judgment. Leave the 70% that needs context, approval, or nuance to humans.
The rule is a deliberately conservative starting point. It prevents the "automate everything" mistake that wrecks workflows, frustrates staff, and usually ends with a rollback.
In practice, this means looking at any process and splitting it into parts. The 30% that is templatized, repeatable, and low-risk is a good target for automation. The 70% that involves judgment, client-specific context, or accountability stays with people. Over time, as trust and data build up, that balance shifts.
The risk of ignoring this rule: teams automate tasks they did not fully understand, the AI makes confident errors on edge cases, and trust in the system collapses. Starting at 30% and growing slowly is almost always faster than starting at 80% and cleaning up.
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