PHILIP BURGESS

By Philip Burgess | UX Research Leader When I first started using ChatGPT in my UX research projects, I was curious but cautious. Could an AI really help me understand users better? Over time, I discovered practical ways to use ChatGPT that saved me time, sparked new ideas, and improved the quality of my research. If you are a UX researcher looking to enhance your process, this post shares my experience and tips on how to use ChatGPT effectively. ChatGPT conversation on UX re

By Philip Burgess | UX Research Leader When I first encountered AI confidence scores, I assumed they worked just like the confidence levels I learned about in research studies. It seemed natural to think that a high AI confidence score meant the same thing as a high confidence interval in scientific research. Over time, I realized this assumption was misleading. The two concepts serve different purposes and come from very different processes. Understanding these differences c

By Philip Burgess | UX Research Leader Artificial intelligence has become a powerful tool in research, offering data-driven recommendations that can accelerate discovery and improve decision-making. Yet, what happens when AI suggestions clash with evidence or insights gathered by researchers themselves? This tension between machine-generated advice and human judgment is a challenge many research leaders face today. I want to share how I and others in the field navigate these

By Philip Burgess | UX Research Leader When I first started working in UX research, measuring user experience felt like trying to catch smoke with my bare hands. We relied heavily on surveys, interviews, and manual observation. These methods gave us valuable insights but often lacked precision and speed. Today, artificial intelligence (AI) is reshaping how we measure UX research, making the process faster, more accurate, and more insightful. I want to share how AI has transfo

By Philip Burgess | UX Research Leader I remember the first time I relied heavily on AI-generated metrics to evaluate a user experience (UX) project. The numbers looked impressive: high engagement scores, positive sentiment analysis, and smooth navigation paths. I felt confident presenting these findings to the team, convinced we had nailed the user journey. But soon, real user feedback told a different story. The AI metrics had painted an overly optimistic picture, missing c

By Philip Burgess | UX Research Leader When I first joined a UX research team, our work revolved around manual data collection, lengthy interviews, and hours spent sifting through notes. The process was slow, and the pressure to deliver actionable insights often felt overwhelming. Over the past few years, I’ve witnessed a significant shift in how AI tools have transformed our daily tasks and the expectations placed on our team. This change is not just about faster workflows b

By Philip Burgess | UX Research Leader When I first started working with AI tools in research, I believed they could solve nearly every problem. After all, AI can process vast amounts of data faster than any human. But over time, I realized that even with perfect data, AI falls short in making the nuanced judgments that research demands. This post explores why human judgment remains essential in research, despite advances in AI and data quality. Researcher reviewing complex d

By Philip Burgess | UX Research Leader When I first started using AI tools in my UX research, I was excited about the speed and scale they offered. But I quickly realized that without clear guardrails, these tools could lead me astray. AI can generate insights fast, but it can also introduce bias, misinterpret data, or overlook important human context. Designing guardrails for AI-assisted UX research is essential to get reliable, ethical, and useful results. In this post, I’l

By Philip Burgess | UX Research Leader User experience (UX) research has always played a key role in shaping products that meet user needs. Today, artificial intelligence (AI) is transforming this field, shifting UX research from a purely tactical function to a strategic driver of innovation and business growth. This change affects how teams gather insights, make decisions, and design experiences that truly resonate with users. UX researcher reviewing AI-driven insights AI En

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 Research today moves faster than ever, and artificial intelligence plays a key role in helping scholars, scientists, and students manage data, analyze results, and generate insights. Choosing the right AI tools can save time, improve accuracy, and open new possibilities in research. This post highlights some of the best AI tools available in 2025 that are worth using for various research tasks. Researcher working with AI software on lapt

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) researchers face growing challenges as AI tools become part of their daily workflow. Crafting effective AI prompts can unlock powerful insights, speed up analysis, and improve design decisions. Yet, many UX researchers struggle to write prompts that deliver clear, relevant, and actionable results. Mastering the right AI prompt frameworks can transform how you gather and interpret user data. This post explores 10 esse

By Philip Burgess | UX Research Leader User experience (UX) research is essential for creating products that truly meet user needs. Recently, artificial intelligence (AI) tools have become popular for speeding up data analysis and generating insights. While AI offers clear benefits, relying too heavily on it in UX research can lead to serious pitfalls. This post explores why depending too much on AI can harm the quality of UX research and what researchers should keep in mind

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

By Philip Burgess | UX Research Leader User experience (UX) research relies on clear, accurate insights to shape products that truly meet user needs. As artificial intelligence (AI) tools become more common in UX research, they offer powerful ways to analyze data and uncover patterns. Yet, AI can also introduce errors that reduce the quality of research findings. Avoiding these mistakes is essential to maintain trust in your UX insights and build better user experiences. This

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 research demands creativity, precision, and efficiency. AI tools can help researchers generate ideas, analyze data, and communicate findings faster. However, knowing which AI prompts to use can make a big difference in the quality and speed of your work. This post shares essential AI prompts every UX researcher should save to improve their workflow and deliver better insights. A UX research dashboard with visual data and

By Philip Burgess | UX Research Leader Agentic AI is changing how we think about artificial intelligence. Unlike traditional AI that follows strict instructions, agentic AI acts with a degree of autonomy, making decisions and taking actions to achieve goals. This shift has significant implications for UX research and the professionals who shape user experiences. What Is Agentic AI? Agentic AI refers to systems designed to operate independently, with the ability to set objecti

By Philip Burgess | UX Research Leader User experience (UX) research has always played a key role in shaping products that meet user needs. Traditionally, UX research involved manual data collection, interviews, and usability testing, which could be time-consuming and limited in scope. Today, artificial intelligence (AI) is transforming how UX research informs decisions, making the process faster, more precise, and more insightful. This shift is changing how teams understand