🗞 AI-Assisted User Research: A Practical Framework

✍️ Spotlight: On My Mind

The highest-leverage thing you can do as a UX researcher isn’t running better studies.. it’s understanding that every stakeholder conversation is fundamentally about power and self-preservation.

I used to focus too much on optimizing for methodological rigor when I should have optimized more for psychological safety. When a PM pushes back on delaying a feature, they’re not questioning your data quality. They’re worried about signaling weakness to their team, their manager or missing their OKR.

The unlock is simple but counterintuitive: lead with understanding their constraints before introducing yours. This isn’t about being nice. It’s about removing friction from decision-making.

What has worked for me:

• Map the real incentives: That PM might not be skeptical of research. They’re protecting sprint velocity metrics that determine their promotion
• Reframe through their lens: Don’t say “users are confused”. Say “the confusion may lead to a drop in user engagement”
• Create psychological cover: Give stakeholders research-backed language to defend unpopular but correct decisions upward

The best researchers I know treat influence like a product. They understand their users (stakeholders), reduce activation energy for adoption, and measure outcomes in changed decisions, not better insights.

The research that wins is the research that feels inevitable to do.​​​​​​​​​​​​​​​​

Happy Researching, 
Jan 🙌

PS: If you are job hunting, check out these 82 UXR jobs that were posted in the last 24 hours.

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📚 Articles of the Week

Create case studies for the business value of “old” customer research
Old research is a goldmine waiting to be mined, not waste. Start by identifying quick wins, collaborating with product teams, running experiments based on prior insights, and showcasing measurable impact to get leadership on board. Jake Burghardt

The Impact of Invisible Stigma on User Interviews: Lessons for UX Researchers
Invisible stigma skews interviews, hiding real effort and masking needs. Checklist: listen to understand; research contexts; prioritize lived experience; encourage safe disclosure; increase diverse samples. Laura Wissiak

UX Research Isn’t Intersectional. It Barely Sees Ethnicity at All.
UX research centers a narrow, white, middle-class default that erases ethnic and intersectional realities. Checklist: recruit beyond convenience panels; pay marginalized participants; partner with communities; build cultural competence; design for complexity. Leena Haque

AI-Assisted User Research: A Practical Framework
AI accelerates analysis but can’t replace human empathy or subtle cues. Checklist: Automate pattern tasks, augment coding and summarization, avoid AI for nuanced interviews and emotional reads. Meg Pugh

Digital twin modeling: a vision of an AI future with UX at the helm
Digital twin modeling is the clearest path for UX designers to apply AI and improve outcomes. Pick predictive behaviors, run experiments, build small adaptive models, then scale to proactive prediction. Kai Wong

How to Use NNGroup’s UX-Maturity Model Without a Formal Assessment
Treat UX maturity as a living system, not a one-time score. Checklist: log signals, run retros by the four factors, map team maturity, track quarterly snapshots, pilot one team. Kate Kaplan

The practical 'human in the loop' framework
Human-in-the-loop is dangerously vague and fails without authority, time, and context. Checklist: define what you optimize for and what's at stake; grant decision authority and thinking time; add circuit breakers and feedback learning. Tey Bannerman

Lessons in self-advocacy: My journey as a solo Research Ops specialist
Solo Research Ops collapses without self-advocacy, clear communication, and priority-setting. Checklist: build a support system, show workload visually to leaders, automate repeat tasks, and set firm boundaries. Clark Shetter

The Importance of Critical Thinking in User Research
Critical thinking is a UX-research superskill that reduces bias and reveals nuance. Checklist: question assumptions, avoid binary choices, verify sources, test nonleading questions. Stephanie Wilson

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🎥 Video of the Week

Jake Burghardt explores how to stop research from gathering dust 🗂️, why timing matters more than tools ⏳, and how to make customer insights truly count for teams and strategy 🚀.
Jake Burghardt

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🔉 Audio of the Week

Using user insights to bring teams together
Center user insights to align product, sales, and engineering for faster, informed decisions. Run lightweight studies, share concise findings weekly with all teams, and embed researchers in sprint planning. Olivia Ponedel & Tina Lickova

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🗓 UserCalendar.com: Upcoming Events.

AI Do’s and Don’ts for User Research Analysis
August 20 @ 11:00 am – 12:00 pm EDT
Nick Babich outlines responsible AI practices, pitfalls, and workflows for UX research analysis to improve speed, quality, and scale while preserving nuance and ethics. Learn more

The AI vs. Human Dilemma: How to Make the Right Call
August 28 @ 10:00 am – 11:00 am EDT
Psychologist and research leader Noam Segal shares a framework to choose AI-first or human-first approaches, identify human non-negotiables, and integrate AI thoughtfully within product teams. Learn more

Submit events here.