Enterprise software is undergoing its most significant architectural shift in four decades — from deterministic CRUD systems that record human decisions to AI-native platforms that generate, evaluate, and execute decisions autonomously. This article provides technology and business leaders with a grounded, architecturally deep guide to understanding this transition: why it matters strategically, how AI-native systems are designed and deployed at enterprise scale, what the real cost and risk tradeoffs look like, and how organizations should think about platform investment versus point solutions. Written from a practicing architect's perspective, it covers the full journey from proof of concept to global autonomous platform — including production infrastructure design, multi-agent orchestration, governance frameworks, observability strategy, and the organizational capabilities needed to make AI-native architectures succeed in the real world.