AI pilot board review · production readiness · go-live evidence

AI pilot board review FAQ: what evidence is needed before go-live?

A board-friendly FAQ for executives, founders, product leaders and risk owners deciding whether an AI pilot is ready to scale, needs remediation, should stay restricted, or should pause before making public ROI, safety, compliance, accuracy or production-readiness claims.

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Truth boundary

This is a buyer-education readiness asset only. It is not a real customer case study, board audit, endorsement, certification, legal/compliance/security advice, safety guarantee, ROI proof, ranking evidence, demand evidence, lead, customer or revenue evidence. No outreach was sent.

Board evidence checklist

Before the meeting

  • Use-case scope, excluded uses and human-review boundary.
  • Data source, data residency, retention, deletion, training-use and subprocessor evidence.
  • Evaluation method, representative test cases, known failure modes and regression evidence.
  • Security/access owner, privileged access review and incident escalation route.
  • Cost exposure for LLM, GPU, cloud, tooling, integration and support spend.

During the decision

  • Name the owner for scale, restrict, remediate or pause decisions.
  • Check rollback readiness and customer/user communication boundaries.
  • Review unsupported external claims before website, sales, investor or board material repeats them.
  • Separate adviser questions from operating evidence: legal, privacy, security, clinical and finance sign-off must come from qualified owners.
  • Record unresolved blockers with owner, due date and decision impact.

Executive FAQ

1. What evidence should a board ask for before an AI pilot goes live?

Ask for scope, user impact, data/privacy boundaries, evaluation evidence, cost exposure, security/access review, named owners, rollback plan, incident/override path and approved external claim wording. AICS treats this as a decision-evidence pack, not a slide-deck promise.

2. Is a successful AI demo enough?

No. A demo can show potential, but production approval needs owner accountability, failure-mode handling, monitoring, rollback, cost controls and clear human handoff rules. Demo success is readiness input, not a production guarantee.

3. What questions reveal unsafe go-live risk?

Ask who can stop the pilot, what happens when the model is wrong, what data the vendor can reuse, who approves a budget overrun, whether rollback has been tested and whether public claims are backed by evidence rather than ambition.

4. When should the decision be “restrict” instead of “go”?

Restrict when value is plausible but evidence is incomplete: limited user group, no public claims, tighter spending cap, human approval on sensitive actions, monitored runbook and a dated remediation queue.

5. Where does AICS fit?

AICS helps turn scattered AI pilot material into board-readable evidence: risk register, readiness intake, evidence room, rollback checklist, incident/override log, remediation record, budget approval log and external-claim control. This page does not claim AICS has produced a client result for this exact review.

Companion evidence assets

AI pilot readiness intake questionnaire · Production readiness evidence room · Board risk register template · Rollback readiness checklist · Budget overrun approval log · Governance vs MLOps/GRC comparison