Most AI pilots never end — they fade into zombie status because nobody defined what failure would look like. This playbook writes the charter that prevents that: hypothesis, success thresholds, measurement method, duration, counterfactual, and kill/scale criteria — all signed before launch, when everyone is still honest.
Workflow area: AI Opportunity & Feasibility · Tier: Advanced · Hands-on time: ~40 minutes
The moment a pilot goes live, incentives corrupt measurement: the sponsor needs it to work, the vendor needs it to work, and the team that built it needs it to work. The only time you can get an honest definition of failure is before launch. That is what the pilot charter is — a pre-registration of the experiment, written by the analyst, agreed by the sponsor, that turns "let's pilot it and see" into a test that is allowed to conclude no.
Extract the hypothesis from the business case and make it falsifiable. "Improve claims handling with AI" is a hope. A hypothesis names the mechanism and the number: "AI-drafted first responses will cut median handling time from a measured 14.2 min to under 10 min, without raising the QA error rate above its 2.1% baseline." Baselines must be measured (pb-38), not recalled — if there is no baseline, the pilot's first two weeks are baseline capture, and the charter says so.
Draft the charter with AI, then negotiate the numbers by hand. Feed the business case and process context to your assistant:
Draft a one-page AI pilot charter from the material below.
Sections:
1. HYPOTHESIS — falsifiable, with the mechanism named
2. SCOPE — pilot group, case types in/out, duration (weeks)
3. SUCCESS THRESHOLDS — 2-4 metrics with numeric targets AND
the measured baseline for each
4. GUARDRAIL METRICS — what must NOT degrade (quality, CSAT,
compliance), with current values
5. MEASUREMENT METHOD — data source per metric, who measures,
cadence, and the counterfactual (control group, A/B, or
pre/post with stated limitations)
6. KILL CRITERIA — conditions that end the pilot early
7. SCALE CRITERIA — what result triggers a rollout decision
8. ROLES — sponsor, measurement owner, decision forum, decision date
Mark any number you had to invent as [NEEDS BASELINE].
Material: [BUSINESS CASE + PROCESS NOTES]
The AI produces structure; the thresholds themselves are negotiated with the sponsor and metric owners — that negotiation is the analysis.
Design the counterfactual honestly. The question every pilot must answer is "compared to what?" Options in descending rigor: parallel control group working the same queue without the tool; alternating assignment (A/B on cases); pre/post with seasonality named as a limitation. Pick the strongest one operationally feasible and write down why. A pilot measured only against memory of how things felt before is unmeasurable by design.
Make the kill criteria specific and pre-authorized. Good kill criteria trigger on evidence, not sentiment:
KILL CRITERIA (any one, verified over a full week):
- Guardrail breach: QA error rate > 3.5% (baseline 2.1%)
- Adoption floor: < 40% of pilot group using the tool in
week 3 despite training
- Safety event: any Sev-1 incident per the incident matrix
- Economics: cost per case > 2x the charter estimate
Decision: measurement owner reports the trigger; sponsor must
kill or file a written exception within 5 working days.
The pre-authorization clause is the teeth — the charter states in advance that a triggered criterion requires a decision, so ending the pilot is executing the plan, not admitting defeat.
Get signatures and calendar the decision. Sponsor, metric owners, and the person who runs the pilot group sign the charter. Book the go/no-go review for the pilot's end date now, with the charter's decision table as the agenda. An unbooked decision meeting is how pilots become zombies.
Pilot measurement means collecting data about identifiable employees' speed and error rates — agree with HR and works-council equivalents what is measured and at what aggregation before launch, state it in the charter, and keep individual-level pilot data out of performance management under DPDP/GDPR purpose limitation.
A pilot without pre-agreed kill criteria is not an experiment, it is a slow-motion purchase — the charter's power is entirely in its timing: thresholds negotiated before launch are evidence standards; thresholds negotiated after are alibis.