Value migration, a framework popularized by Adrian Slywotzky in 1996, tracks how market leadership and profitability shift as technology evolves and customer preferences change, with commoditization collapsing margins at legacy layers while new value accrues to emerging control points. In the AI era, this migration is reshaping industries from foundational capabilities such as transformer architectures, self-supervised training, and distributed compute, to specialized infrastructure layers including AI chips, cloud platforms, vector databases, and developer tools, to enterprise applications embedding AI into workflows and decision-making. The current landscape is dominated by semiconductor companies like NVIDIA in foundational compute, cloud providers (AWS, Azure, Google Cloud) capturing recurring infrastructure revenue, foundation model creators (OpenAI, Anthropic, Google DeepMind) in the core intelligence layer, and specialized platforms competing for enterprise mindshare. A critical shift is underway as value migrates from AI producers to AI users: as models and infrastructure commoditize, advantage comes from owning workflows and data, so enterprises with proprietary data, workflow optimization, and distribution channels are poised to capture expanding margins. Gartner warns that 40% of agentic AI projects will be canceled by 2027 due to unclear value propositions. Future winners will likely include specialized vertical AI companies, regionally protected ecosystems such as China, workflow-native platforms, and enterprises transforming operations around AI-driven outcomes, as value accrues to outcome owners rather than tool builders.