Embracing AI tools in UX research
Interviews with 50 researchers across 24 countries
Our global AI study, conducted through a dual-method approach of ethnography and autoethnography, delves into the impact of GenAI on UX research. Key findings include insights on global sentiment, knowledge levels, usage patterns, GenAI applications in UX research, governance, and strategic recommendations for integrating GenAI ethically and effectively.
Connect with our AI experts to discuss the pivotal role of early-stage research in a rapidly evolving landscape.
Missed the webinar?
If you missed our December 2023 webinar, watch it now for a high-level overview of the whitepaper’s topics, questions, and findings. In this 30-minute presentation, Lindsey DeWitt Prat, PhD, brings clarity (and data) to the conversation, sharing findings directly from the global UX research community.
Early stage AI experts
We’ve spent years refining and defining methods that reveal user reactions to emerging technologies. Not only did we write the book, many of our researchers have advanced degrees in human-computer interaction. Early research of AI-enabled products is a crucial step in the product development process, allowing you to stay at the forefront of innovation, accelerate time to market, and ultimately deliver a product your users will love.
We wrote the book
Our practice has been focused on the symbiotic relationship between UX & AI for years. Our founding partners published one of the first books on the topic in 2020. This publication is based on early work explorations of AI technology across consumer electronics and healthcare.
Why AI needs UX
In the book, Gavin and Bob dive into what drives the usage and success of AI-enabled products. They argue it largely depends on a great user experience; context, interaction, and trust are the prerequisites for AI adoption. They detail how barriers to user trust can be overcome and how acceptance and conversion can follow. The book addresses areas including:
- Assessing GenAI capabilities for data management systems
- Understanding potential AI-human connectivity
- Measuring tools for trust & safety with AI technology
- Enabling dialogue around AI tools that don’t yet exist
Related content
Read our latest news & insights
Case studies
Three things to improve acceptance of AI
To truly deliver on the promise of AI, developers need to keep the end users in mind. By integrating three components of context, interaction, and trust, AI can be the runaway success that futurists predict it will be.
Case studies
