Audit material
AI automation audit checklist
Use this checklist to decide whether a workflow is worth automating, which risks require human approval, and what a realistic first build should include.
1. Workflow fit
- Is there a named owner for the workflow?
- Does the workflow happen often enough to justify automation?
- Is the business impact measurable through response time, scheduled work, hours saved, data quality, or customer experience?
- Can the first version be scoped to one workflow and a small number of systems?
2. Current-state mapping
Document the trigger, owner, inputs, tools, manual decisions, outputs, delays, failure points, and handoffs. If the current workflow cannot be explained clearly, map it before automating it.
3. Data and system inventory
- Which sources create the work: forms, calls, inboxes, CRM, spreadsheets, chat, documents?
- Which fields are required for a useful output?
- Where does the final record need to live?
- Who can grant access and test with real sample data?
4. Human approval requirements
AI should stay under review when the workflow touches customer-facing messages, pricing, legal/medical/financial claims, sensitive data, irreversible system changes, or anything the client would not want sent silently.
5. Risk and failure handling
For each automated step, define what happens when data is missing, confidence is low, an integration fails, a message is ambiguous, or the output could create customer risk. Good automation fails visibly and routes work to a human.
6. Success metrics
Choose 2–4 metrics before building. Examples:
- First response time
- Leads with follow-up inside SLA
- Estimates or appointments closed
- CRM completeness
- Manual hours saved
- Owner or office-manager satisfaction
7. Initial build scope
A solid v1 has a clear trigger, restricted input sources, a visible approval point, a fallback path, and a weekly reporting loop. Avoid trying to automate every edge case in the first build.
8. Ship or pause decision
Move forward when the pain is measurable, systems are accessible, risk can be controlled with review gates, and the first build can create value in 1–3 weeks. Pause when the workflow is unclear, data is unavailable, the client wants unsafe full autonomy, or the value is too small for the cost.
Next step
Request an AI Client Ops audit
Get a workflow map, risk review, and first automation recommendation before committing to a larger build.