Clearline resource pillar
Dealership AI governance and quality assurance
Set ownership, permissions, escalation, testing, and review standards before customer-facing AI represents the dealership.
Built for
Dealer principals, compliance leaders, general managers, and operational owners
Use the rollout checklistGovern the workflow, not the label
A policy that says a dealership uses AI responsibly is not an operating control. Governance becomes useful when each workflow has an owner, purpose, approved data, allowed actions, prohibited actions, escalation path, test set, and review cadence.
Different workflows carry different risk. A general-hours answer is not equivalent to a pricing promise, appointment write-back, safety question, or marketing message. Controls should follow the action the system can take.
Quality assurance must continue after launch
Pre-launch scenario testing establishes whether the workflow follows dealership policy. Ongoing review finds new failure patterns, outdated information, weak handoffs, and edge cases that only appear in real conversations.
A practical review process samples completed and failed interactions, classifies errors, assigns corrective action, and records who approved each material workflow change.
Questions to settle before launch
- Who owns each workflow and can pause it?
- Which data, claims, and actions are allowed or prohibited?
- What customer requests always require a human?
- How are incidents, complaints, and recurring quality failures reviewed?
Start here
Core guides for this workflow
Every automated workflow has a named owner, approved boundaries, tested exceptions, and a review process that can stop or correct it.