A practical sequence: copilot, metrics, policy, then automation.
RevOps teams are under pressure to "automate" with AI. The failure mode is automating chaos: faster sends, same broken messaging, and no way to explain results in a pipeline review. This checklist is the order we recommend when moving from copilot to anything hands-off.
1. Copilot with reviewers in the loop
Start with assisted drafting and next-step suggestions. Measure time-to-first-reply and approval turnaround, not just send volume. If reviewers consistently approve in seconds, you are seeing either excellent policy fit or rubber stamping—validate which before widening automation.
2. Metrics that survive leadership questions
Before autopilot, define how you will report AI-assisted touches: per segment, per stage, and per outcome. You need at least one chart that finance and legal can understand without a tutorial on tokens.
CRAIM exposes approval logs and message lineage for this reason. If you cannot answer "what went out and who blessed it," pause automation until you can.
3. Policy in configuration, not in tribal knowledge
Encode what never gets said, which claims require legal review, and which accounts are off limits for automation. If those rules live only in Slack, autopilot will eventually violate them at scale.
4. Automation last
Only then expand to autopilot for narrow slices: a single use case, a single segment, with budgets and kill switches. Expand breadth after you have a month of clean metrics—not the week the board asked for AI adoption.