POLARIS

Enterprise AI · Problem brief

AI PoC Is Not Reaching Production

DIRECT ANSWERAn AI PoC usually stalls because it proved an impressive output rather than a production decision. Re-state the user, workflow, baseline, acceptance criteria and failure path; evaluate representative cases with cost, latency and human review; then run a shadow workflow owned by the operating team. Do not rebuild the interface until the promotion gap is explicit.

Updated September 28, 2026Diagnosis · Evidence · First proof

Start with these five checks.

Ask for only what can change the answer.

Test one reversible move.

Run the existing candidate in shadow mode on a fixed representative task set. Log model version, evidence, tool calls, output, reviewer decision, latency and cost. Promote only if it passes pre-set outcome and guardrail thresholds; otherwise the failure breakdown determines whether to change data, workflow, model or scope.

A decision your team can use.

Common questions.

What is the difference between a demo and PoC?

A demo shows capability; a PoC tests a specific decision against a baseline and acceptance criteria.

When is it ready for a pilot?

After hidden evaluation passes and the workflow has an owner, controls, monitoring, review and rollback.

Should a better model be tried first?

Only when failure analysis shows model capability is the constraint rather than data, workflow or integration.

Authoritative references.

  1. NIST, AI Risk Management Framework
  2. NIST, AI RMF Playbook
  3. UK ICO, Guidance on AI and data protection

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