As AI rewrites the design toolkit in real time, UX research sits at a particular crossroads. Synthesised insights, automated analysis, simulated participants; the production layer of research is compressing fast. For design leaders trying to prove strategic value inside organisations, that creates both an opportunity and a threat.
This talk moves beyond tool-centric debates to ask the harder question: when parts of the research process can be automated or simulated, what does good research actually require — and what does it cost an organisation when that gets lost?
From the perspective of a design leader accountable for decisions, not just methods, Jason Giles reflects on how AI is exposing long-standing assumptions about certainty, evidence, and judgment. Drawing from real experiences where trade-offs had to be made and judgment was tested, he explores where human expertise still matters most, which responsibilities cannot be delegated to systems, and how we maintain authenticity and trust when insight is increasingly co-produced by humans and machines.
This is not a talk about prompts, platforms, or productivity hacks. It is a candid, values-driven reflection on responsibility, discernment, and ethical judgment in an AI-augmented world—and an invitation for researchers and design leaders to re-ground their craft around what must remain human, even as their tools evolve.
