AI can now generate personas, journey maps, and research summaries before a single user has been interviewed. AI-Assisted UX Research examines what that means for a discipline whose value has never resided in its artifacts, but in the evidence, interpretation, and decisions behind them. AI can accelerate the work, but it cannot replace the researcher's responsibility to frame the right problem, choose the right method, interpret behavior in context, and determine whether an output is actually supported.The book follows AI across the UX research lifecycle, from planning and desk research through interviews, usability testing, synthesis, personas, journey maps, reporting, and stakeholder communication. It examines where AI provides genuine leverage and where it creates new risks, including polished but ungrounded outputs, compressed discovery, weakened traceability, misplaced confidence, and research theater accelerated by AI.It also addresses the growing responsibility of UX researchers to evaluate AI-enabled products themselves, including questions of trust, uncertainty, explainability, appropriate reliance, and failure. This is not an argument against AI. It is a practical framework for using it without confusing speed for understanding. The future of UX research is not AI-driven. It is judgment-driven, AI-assisted.