Best Practices
Case studies and articles on AI in research — real workflows from leading organizations
Nielsen Norman Group: The methodological problems hiding in your research tools
Maria Rosala examines how UX research platforms introduce silent methodological errors, a risk that intensifies as AI now automates study design and analysis.
UX leadership in AI disruption — dscout case study
dscout CEO Michael Winnick urges UX leaders to treat AI as a design material rather than a threat, moving beyond polarized debates about replacement.
Daniel Mitev: What 100 UX researchers said about AI in 2026
An analysis of a December 2025 Lyssna survey of 100 UX researchers, covering adoption rates, synthetic participants, the shifting ownership of research, and why ROI remains unsolved.
AI-moderated interviews in UX research — NN/g case study
Nielsen Norman Group's study of AI interviewers (Marvin and UserFlix) with 10 participants, identifying four specific use cases and clear limitations.
Dscout: Why researchers should lead AI evaluations
Nathan Reiff makes the case that UX researchers are uniquely positioned to run AI evals, bridging the gap between engineering metrics and real user value.
UX research in the age of LLMs — practical guide
Connor Joyce argues that LLMs make UX research more strategic, not less relevant, and proposes a new process for defining quality in AI-generated outputs.
dscout: A six-step framework for embedding AI into your UX practice
Rose Beverly, UX AI researcher at PayPal, introduces the MASTER framework — six steps for assessing which research tasks to automate and how to build AI into repeatable workflows.
AI in UX research — achieve more with less
Paul Boag shares lessons from real client projects on using AI across research, design, and development, with the mental model of treating AI as an intern.
Responsible AI workflows for UX research — practical guide
A practical playbook mapping what to automate and what to keep human across every stage of the UX research process, with ethical guardrails.
AI-simulated behavior in user research — NN/g evaluation
NN/g reviews three academic studies on digital twins and synthetic users, assessing when AI simulations can fill research gaps and when they fail.
Using generative AI for UX research — practitioner case study
Tania Ostanina shares her updated AI research method using ChatGPT Enterprise Deep Research, with a real case study and step-by-step prompting approach.
Generative AI research agenda for UX — NN/g study
NN/g proposes four major research areas exploring how generative AI changes both what UX teams study and how they conduct research.
AI tools for UX research workflows — ResearchOps case study
Adam Malamis maps six practical ways AI can improve UX research workflows, from planning through sentiment tracking, with clear automation boundaries.
Arguing against AI-first research — Smashing Magazine analysis
Vitaly Friedman makes the case against synthetic AI testing as a replacement for user research, with practical counter-arguments for stakeholder conversations.