Customer asks for help.
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Customer service · release decision
Test the way out before you open the way in.
Model one customer AI journey, test the handoff to a person, and leave with a release decision, 12 acceptance cases, a recovery script, and a weekly review plan.
All calculations use your inputs and your release gates. Nothing is submitted.
Step one
Name the promise and the escape path.
Use one channel and one group of customer issues. A narrow promise is easier to prove and safer to fix.
Why the exit matters: Gartner reported on September 2, 2026 that 87% of surveyed customers said access to a human was essential when companies use generative AI in service. Only 27% said they would try a chatbot again after a negative experience. This study is context, not an input to the calculations.
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Step two
Follow 1,000 customer conversations.
Use observed data when you have it. If you use estimates, mark them for replacement during the limited release.
The model scales to this volume.
Percent with a correct, complete outcome.
Percent of customers still needing help.
Percent of successful handoffs resolved.
Percent of customers reaching a person.
From handoff request to human response.
Extra work caused by missing context.
The evidence label appears in the memo.
Correct and complete.
Handoff succeeds.
Needs recovery.
Step three
Set the gate, then run the ugly cases.
The thresholds below are Aule defaults, not industry standards. Change them to match the promise, risk, and service level your business accepts.
Eight operating controls
Twelve acceptance cases
Check a case only after it passes in the real channel with the intended user identity.
Step four
The release decision.
This packet combines your modeled journey, chosen gates, operating controls, and completed acceptance cases.
0readiness
Recommended laneHold
Full journey resolved0%
Clean handoff0%
Cases passed0/12
Gaps to close
Seven-day action plan
Leadership release memo
Customer AI Handoff Test
Decision
Owner
Evidence
Recovery
Copy-ready recovery script
Want an outside review of the handoff?Bring Aule the service promise, gaps, and decision pack. The source and modeled result can travel with the request.
Bring the evidence to Aule →Sources, method, and limits
- Gartner, September 2, 2026. Gartner says its survey included 3,566 B2B and B2C customers in February and March 2026. It reports that 87% considered access to a human essential when companies use generative AI in customer service and that 27% would try a chatbot again after a negative experience. This is self-reported survey evidence, not a measured churn study.
- Microsoft Copilot Studio, updated August 3, 2026. Microsoft documents that a configured live-agent handoff can share conversation history and relevant variables, and that customers can ask for a live agent at any point. Product behavior depends on the connected channel and engagement hub.
Method: Journey counts are simple arithmetic using only the values entered above. Full-journey resolution equals AI-resolved conversations plus successful human resolutions after handoff. Customer time equals time waiting for a person plus repeat-context time. Readiness gives 55% weight to the four chosen outcome gates, 25% to the eight controls, and 20% to the twelve acceptance cases. The release lane requires every named gate, not only the score. Aule defaults are planning choices, not published industry standards.