PHILIP BURGESS

By Philip Burgess | UX Research Leader Research teams often face the challenge of managing vast amounts of information while trying to stay focused on their core tasks. An AI research assistant can help by automating routine tasks, organizing data, and providing quick insights. Building such a tool tailored to your team’s needs can boost productivity and improve the quality of research outcomes. AI research assistant interface on laptop screen AI Research Assistant: Understan

By Philip Burgess | UX Research Leader Artificial intelligence (AI) has transformed many industries, from healthcare to finance, by automating tasks and uncovering insights from vast data. Yet, despite rapid progress, AI systems often fall short of their full potential. The key to unlocking more effective AI lies not just in technology but in the expertise of experienced researchers. These professionals bring critical skills and judgment that machines alone cannot replicate.

By Philip Burgess | UX Research Leader Creating user experience (UX) designs quickly without losing quality is a challenge many designers face. AI prompt templates offer a practical way to speed up UX synthesis by providing structured starting points for generating ideas, wireframes, and user flows. This post explores how using AI prompt templates can help UX professionals work more efficiently while maintaining creativity and clarity. UX wireframe template displayed on lapto

By Philip Burgess | UX Research Leader Artificial intelligence has transformed many fields, including research. Yet, AI’s role in research often gets misunderstood. It is not a researcher in the traditional sense but serves best as a research critic. This distinction matters because it shapes how we use AI tools effectively and ethically in academic and scientific work. AI analyzing research data with critical insights Understanding the Difference Between Researcher and Resea

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

By Philip Burgess - UX Research Leader 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 Challenge

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