AI Automation Audit Checklist: Controls Before More Scale
A practical AI automation audit covering purpose, data, access, human review, testing, monitoring, incidents, and retirement.
Insights
Choose and control the next workflow to automate
The best starting point for automation is a clear process with an accountable owner, understood inputs, and a useful result. These insights help teams examine recurring handoffs, approval steps, exceptions, and the controls needed before increasing scale. Map the existing work first, including where people must review a decision or recover from a failure. Then choose a bounded improvement that can be tested and maintained. AI involvement adds questions about permitted data, output review, and responsibility; it does not remove those obligations. Use the guidance to prepare a scoped workflow discussion, with implementation and ongoing support agreed separately rather than assumed from the technology.
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How to Choose the First Workflow Worth Automating
Choose a first workflow automation by scoring repetition, rules, data readiness, exceptions, ownership, and business value before selecting a tool.