The term "UX in AI" is currently confusing with many interpretations. Digital twin modeling offers a clear pathway for UX designers to engage with AI. This concept originated with NASA's Apollo 13 mission, where a replica spacecraft served as a crucial tool. Modern digital twins are used in various industries like energy, smart buildings, and healthcare for monitoring and optimization. UX is vital in digital twins to identify essential data for user decision-making. AI can be used to predict and influence user behavior, as demonstrated by a hypothetical healthcare digital twin for medication adherence. Digital twins address three key design problems: "design in the dark," the "set it and forget it" trap, and the "AI skills gap." To build digital twins, designers must master metric selection, experiment design, data translation, and continuous optimization. Learning digital twin modeling involves mastering data-informed design, studying applications, building behavioral models, and scaling to intelligence. Digital twin modeling provides a concrete and proven use case for applying AI to UX problems. It enables designers to build real-time models of user behavior for improved experiences. This approach offers clarity and a practical path for UX professionals in the evolving AI landscape.