AI pilot exit readiness · vendor lock-in · production approval

AI pilot vendor lock-in FAQ: what to prove before the pilot becomes hard to leave

A buyer-safe FAQ for founders, boards, procurement, security and AI product owners who need evidence that an AI pilot can be exited, switched, paused or run in fallback mode before it scales.

Request exit-readiness review scopeUse go/no-go recordCheck data evidenceMap vendor answers

Truth boundary

This is a buyer-education readiness asset only. It is not a real customer case study, testimonial, certification, legal/security/privacy/procurement advice, compliance proof, switching guarantee, ranking evidence, demand evidence, lead, customer or revenue evidence. No outreach was sent.

When this FAQ is useful

Before pilot scale approval

Use it when the team is ready to expand users, data, geographies or integrations but cannot prove how the system would be paused, replaced or run manually if the vendor path changes.

During procurement or security review

Use it when buyer teams ask who owns prompts, embeddings, workflow logic, logs, evaluation sets, exports, admin rights, retention evidence and subprocessor records.

Before public claims

Use it when sales, website, investor or board material implies production readiness, cost control, resilience or portability before exit evidence has been reviewed.

Exit-readiness evidence map

Evidence to collect

  • Data export format, frequency, owner, retention period and deletion path.
  • Prompt, policy, workflow, tool-call, guardrail and evaluation-set ownership.
  • Retrieval corpus source map, embedding/index rebuild process and stale-source controls.
  • Contract notice periods, pricing step-ups, minimum commitments and support handoff terms for adviser review.
  • Fallback operating procedure if the AI service, model, integration or vendor support is unavailable.

Decision outputs

  • Scale, restrict, remediate, renegotiate, pause or exit decision with named owner.
  • Switch-over blocker list for engineering, security, privacy, procurement and finance.
  • External claim status: approve, revise, withdraw or hold until portability evidence is complete.
  • Cost-exposure summary for duplicate runs, migrations, re-testing and staff fallback.
  • Board-readable residual-risk note and adviser-question list.

Executive FAQ

1. What should we check when an AI pilot may create vendor lock-in?

Check whether the business can export required data, rebuild retrieval assets, retain logs/evidence, transfer prompts/workflows, switch models, preserve human-review queues and keep serving users if the vendor, model or commercial terms change.

2. Is model portability the same as exit readiness?

No. Model portability is one part. Exit readiness also includes data, retrieval sources, workflow logic, approvals, cost exposure, operational fallback, contract review and the evidence owners need before production approval.

3. Should production approval wait until every exit risk is removed?

Not always. Some risks may be accepted by named owners, but accepted-risk decisions should be explicit, dated and supported by fallback steps, cost ranges, adviser questions and trigger conditions for rollback or renegotiation.

4. What claims should be held if exit evidence is weak?

Hold or qualify claims about portability, resilience, cost predictability, compliance readiness, production readiness and future-proofing until evidence has been checked and the relevant owners approve the wording.

5. Where does AICS fit?

AICS helps convert scattered vendor answers, architecture notes and procurement questions into a board-readable exit-readiness pack: ownership map, export evidence, fallback plan, cost exposure, adviser questions and claim boundaries. This page does not claim AICS has delivered a client outcome for this exact situation.

Companion evidence assets

Data residency and subprocessor evidence checklist · AI vendor security-questionnaire answer source map · Production go/no-go decision record · Rollback readiness checklist · External claim approval log · AI security and sovereignty