AI experimentation is deceptively inexpensive. Production AI is not. This article breaks down where enterprises actually spend in Year 1, Year 2, and Year 3 — across infrastructure, inference, data engineering, platform layers, and governance — and provides the architectural and financial frameworks leaders need to understand before scaling AI investment. The key insight: the time to model AI economics is before the architecture is built, not after the cost curve becomes undeniable.