UX research is shifting dramatically due to the integration of artificial intelligence. Researchers are moving from merely studying static interfaces to actively shaping human-AI collaboration. This transition highlights a significant misalignment in AI investment, where 41% of funds are directed towards automating tasks that workers don't want automated. Meanwhile, essential human needs remain unaddressed. AI UX researchers are crucial in bridging this gap, ensuring that technology development prioritizes human agency and real-world issues. The traditional focus on personas and user journeys is becoming outdated. Current product ecosystems require continuous insights for adaptive human-AI systems that can respond to user needs in real-time. With product lifecycles shortening, there's a growing demand for ongoing learning systems instead of delayed reports. This necessitates a shift in AI UX research methodologies towards agile and integrated strategies. As AI evolves, the roles within UX research are expanding beyond simple job replacement narratives. New modes of human-AI collaboration are emerging, such as assistive collaboration and supervised automation. Researchers are now expected to connect organizational silos and synthesize insights from various data sources. They will also need to reframe problems and envision solutions that go beyond AI's current capabilities. Potential new roles include "learning architects" and specialists in "human-AI systems design and evaluation." While these changes may be challenging, they present a significant opportunity for researchers to redefine their roles. By embracing their position as architects of human-AI collaboration, they can ensure that new AI-driven products and services better meet human needs.