AI-powered personalization has become a foundational capability for streaming media platforms, yet many organizations still approach it as a collection of isolated algorithms rather than a cohesive product innovation discipline. As streaming platforms scale across content catalogs, devices, and user contexts, this fragmented approach increasingly limits impact. In this session, I introduce the STREAMS framework, an original product innovation framework for AI-powered personalization in streaming media platforms that shifts the focus from individual recommendation models to end-to-end product systems. The session explores how personalization can be designed as a platform-level capability that informs content discovery, experience orchestration, growth experimentation, and continuous learning across the streaming lifecycle. Grounded in product-led growth leadership experience building and scaling personalization platforms, the talk outlines how streaming organizations can evolve AI-powered personalization into an adaptive product growth operating model that balances user engagement, business objectives, and platform governance. Attendees will leave with a clear framework they can use to assess personalization maturity and guide platform-scale product innovation.