By Philip Burgess | UX Research Leader The rise of artificial intelligence has transformed many fields, including user experience (UX) research. AI tools can analyze large datasets, identify patterns, and even generate user insights faster than ever before. Yet, despite these advances, the future of UX research depends heavily on human skills that AI cannot replicate. Understanding why these skills remain essential helps UX professionals prepare for a future where technology

By Philip Burgess | UX Research Leader User experience (UX) design is evolving rapidly, and one of the biggest questions today is how much of this work will be done by artificial intelligence. Agentic AI, which can act independently to complete tasks, is advancing quickly. Some experts predict that it could replace up to 50% of UX tasks in the near future. This shift will change how designers work and what skills they need. Let’s explore what this means for UX design and how

By Philip Burgess | UX Research Leader User experience (UX) research is essential for creating products that truly meet user needs. With the rise of artificial intelligence (AI), many UX research tasks are evolving. AI tools can now handle data collection, analysis, and pattern recognition faster than ever. Yet, some parts of UX research still require human insight, empathy, and creativity. This post explores which UX research tasks AI will automate and which ones will remain

By Philip Burgess | UX Research Leader User experience (UX) research has always been a vital part of designing products that truly meet user needs. As technology advances, the methods and tools used in UX research evolve as well. Artificial intelligence (AI) is set to change the way UX researchers gather, analyze, and apply data by 2026 and beyond. This transformation will make research faster, more accurate, and more insightful, ultimately improving how products connect with

Discover how artificial intelligence is revolutionizing UX research, from automated data analysis to predictive user behavior. Learn best practices for combining AI's analytical power with human expertise.

Discover how artificial intelligence is revolutionizing UX research methodologies, making user insights faster, more scalable, and more actionable than ever before.

By Philip Burgess - UX Research Leader By Philip Burgess – UX Research Leader 📧 phil@philipburgess.net  | 🌐 www.philipburgess.net Understanding the Foundation: What Is UX Research Card Sorting? Card sorting has been a cornerstone of UX research and information architecture (IA) for decades. It’s a deceptively simple method—participants group related concepts or “cards” into categories that make sense to them.The outcome?A clearer understanding of how users mentally organize

Stay ahead in the ever-evolving field of UX research. Discover the top 5 trends that will shape the industry in 2025, from AI-powered insights to continuous user feedback.

Philip Burgess – UX Research Leader Exploring AI + UX Research to shape better human experiences A New Era for UX Research: The Future of AI and UX Research Artificial intelligence is transforming nearly every aspect of how we work, design, and interact. For UX research, this shift is especially powerful. Instead of replacing the researcher’s role, AI has the potential to amplify workflows, accelerate synthesis, and unlock new possibilities  for how we understand people. We a

As user expectations accelerate and product cycles compress, UX researchers must evolve beyond traditional study methods to embrace continuous, real-time feedback systems. Here's how to build research practices that keep pace with modern product development.

By Philip Burgess - UX Research Leader UX Research and AI: Why Cross-Cultural Research Matters As products scale globally, UX research must go beyond a one-size-fits-all approach. Cultural norms, language, accessibility expectations, and digital behaviors vary dramatically across markets. In the era of AI-powered tools, the challenge — and opportunity — is to adapt research methods to honor cultural context while still benefiting from automation and scale. The Risks of Ignori

By Philip Burgess - UX Research Leader Why UX Research Storytelling Matters in the Age of AI AI is transforming UX research by generating faster insights, surfacing hidden patterns, and analyzing vast datasets. But AI alone cannot bridge the gap between raw findings and strategic decisions. That bridge is storytelling . It’s how researchers translate complex, technical AI outputs into compelling narratives that executives can act on. The Challenge of AI-Generated Insights Ove

By Philip Burgess - UX Research Leader Rethinking Research Participants as UX Research AI Agents Traditionally, UX research relies on recruiting human participants to test products, uncover pain points, and validate assumptions. But with the rise of AI, a new possibility is emerging: AI agents acting as simulated users . While not a replacement for real human feedback, AI-driven participants can stress-test digital journeys, highlight obvious flaws, and accelerate pre-launch

Why ROI Matters More Than Ever In an era where AI is accelerating workflows and budgets are under constant scrutiny, UX researchers are being asked the same question more often: what’s the measurable business impact of our work?  Demonstrating the ROI (Return on Investment) of UX research is no longer optional — it’s essential for securing executive buy-in, scaling research programs, and proving strategic value. Traditional ROI Challenges in UX Research Intangible outcomes :

By Philip Burgess - UX Research Leader Resumes have barely changed in decades—static documents, bullet points, and PDFs that rarely capture who you are as a professional. They often feel more like checklists than stories, and they rarely give hiring managers, collaborators, or clients a chance to experience who you are in real time. So, I asked myself: What if a resume could talk back? What if it wasn’t just read—but experienced? That’s exactly what I set out to build with my

By Philip Burgess - UX Research Leader AI is no longer a futuristic concept—it’s quickly becoming a core part of how UX researchers work. From automating repetitive tasks to uncovering new insights, AI tools can enhance efficiency, but they must be used thoughtfully. The goal is not to replace the researcher’s judgment, but to augment human expertise with machine speed and scale . Why Pair UX Research and AI? Efficiency:  Automate time-consuming tasks like transcription, clus

By Philip Burgess - UX Research Leader Quantitative UX research is all about uncovering the “what” and “how much” behind user behavior. It leverages data from surveys, experiments, analytics, and large-scale usability testing to generate statistically valid insights. While qualitative research explains the why , quantitative research measures the scale  and impact . AI can supercharge this work by helping UX researchers craft better survey questions, analyze large datasets, i

By Philip Burgess - UX Research Leader Artificial Intelligence is becoming a powerful partner for UX researchers, not a replacement. With the right prompts, AI can accelerate analysis, uncover themes, draft reports, and even suggest new research questions. Below are 50 of the best AI prompts for qualitative UX research , organized by stage of the research process. 1. Research Planning “Suggest 5 open-ended interview questions to understand user frustrations with [product/feat

By Philip Burgess - UX Research Leader AI isn’t replacing UX research—but it can amplify our workflows if used thoughtfully. The key? Knowing how to prompt effectively  so the output supports research goals without introducing bias or over-simplification. Here are some of the the best UX Research AI prompts—plus why they matter and examples you can use right away. 1. Planning & Scoping When time is short, AI can help frame a structured research plan. Prompt Example: “Create a

By Philip Burgess - UX Research Leader Usability testing is the cornerstone of great UX—rich with user feedback, interaction pain points, and design validation. But once the sessions are over, one thing looms large: the dreaded usability report . For many UX researchers, analyzing sessions, pulling quotes, tagging issues, and building a report can take hours —sometimes days . But what if AI could automate that process without sacrificing depth? Here’s how we used AI to automa