Case Study: An Approval-Gated Customer Workflow
Updated
A fictional logistics firm automates claim responses - AI drafts, a human approves, the audit trail satisfies the compliance team, and the override-rate metric tells you whether the gate is safety or theater.
Fictional training case, not a real engagement.
Situation
"Falcon Freight" (fictional) handles 300+ damage claims weekly. Responses are formulaic; mistakes are expensive and regulated. The COO wants "AI to just handle it"; compliance requires a named human accountable for every outbound claim response.
The delivery arc
- Metrics: median response time 2.4 days → same-day for approvals-within-policy; override rate expected 15-40% initially (a healthy number - zero overrides means the gate is decorative).
- Design: retrieval over claims history + policy; draft generation with citations; approval UI showing draft + sources + policy checklist; approve/edit/reject actions logged with approver identity.
- The human factors: approvers initially rubber-stamped drafts (override rate 6%) - fixed by surfacing two "consider" checks (precedent differences, tone flags) which pushed overrides to a meaningful 19%.
- Audit: every outbound response traceable: draft version, edited diff, approver, timestamp, cited policy paragraphs.
- Result framing for the COO: same-day responses for 82% of in-policy claims; no unapproved outbound in the audit trail (the compliance metric, which was the real success).
What learners should extract
- Override rate is a diagnostic: too low = rubber stamp, too high = bad drafts.
- The audit trail is a product feature, not paperwork (approval pattern).
- "AI proposes, human disposes" is the deployable pattern for regulated workflows.
Practice version
The public Customer Workflow Delivery capstone brief includes an approval-gate requirement and an audit-trail self-review criterion.