Most enterprise AI initiatives stall between proof of concept and production — not because the technology fails, but because the surrounding architecture, governance, and data infrastructure were never designed for production scale. This article provides a phased six-month roadmap covering data pipeline architecture, security design, model serving, retrieval systems, human oversight, cost controls, and executive monitoring — with the phase gates and failure mode patterns that determine whether an AI programme delivers measurable business value or becomes an expensive demonstration.
