Free template
AI Workflow Readiness Checklist for Enterprise Operations
Evaluate whether a repeated business process is ready for governed AI execution before connecting systems or granting permissions.
Outcome readiness
A workflow is easier to automate when completion can be observed in the real systems involved.
- The trigger is identifiable.
- The required outcome is explicit.
- The final system state can be verified.
- The workflow occurs often enough to evaluate.
Process readiness
The workflow does not need to be perfectly documented, but owners must agree on the normal path and important exceptions.
- Inputs and systems are known.
- Decision rules can be stated.
- Escalation owners are named.
- Common failure cases are available for testing.
Control readiness
Permissions and approvals must be designed before autonomous execution.
- Low-risk actions are separated from sensitive actions.
- A named person owns each approval gate.
- Service-account permissions can be restricted.
- Prohibited actions are documented.
Evidence readiness
The team agrees what must remain after each run.
- Inputs and sources are traceable.
- Actions and changed records are logged.
- Approvals identify the decision and decision-maker.
- Errors, retries, and unresolved exceptions remain visible.
Pilot decision
A strong first pilot has clear boundaries, accessible data, a responsible owner, and an evaluation set. If one of those is missing, fix that dependency before expanding the scope.
Start with one workflow and prove the boundary.
Map the event, systems, permissions, approvals, exceptions, and evidence before granting access. The result is a pilot scope your operations and technical teams can evaluate together.
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