Industrial AI Pilot-to-Production Readiness OS
Industrial AI proofs of concept can demonstrate technical promise without becoming trusted production systems. The gap between a pilot and operational deployment includes production data pipelines, OT/legacy-system integration, operator workflows, model verification, cyber and safety controls, regulatory/quality evidence, ownership, ROI baselines and ongoing monitoring—areas that are often handled separately or discovered late. Operational consequences: Promising pilots are shelved after grant or innovation funding ends, teams repeat the same readiness work, production staff maintain manual workarounds, and leadership cannot tell whether a pilot is genuinely safe and scalable. Unclear ownership and missing baselines make ROI hard to prove, while unresolved OT/cyber/safety dependencies can turn an apparently successful prototype into a long integration project.