Marco Rovagnati, Co-Founder at Quallie.Ai, shares how AI-powered research tools are eliminating tedious UX research and product discovery tasks, making insights more dynamic and actionable, and ensuring research remains accessible for strategic decision-making.

Tanya Berlina, Client Success Director at Yasna.ai, discusses how AI-powered research tools like Yasna enable UX researchers and product managers to scale qualitative research without losing depth, blend qualitative and quantitative insights for smarter decision-making, and streamline routine tasks while keeping human expertise at the center of the research process.

Eric Li, Co-Founder of Versive, discusses how AI tools are transforming customer research by enabling faster interview-like studies, allowing for more research that produces better product decisions, and shifting researchers toward more strategic roles.

Kene Anoliefo, Co-founder at Heard, discusses how AI-powered research is transforming product discovery by making it faster, more iterative, and seamlessly integrating qualitative and quantitative insights.

Matteo Cera, Co-Founder and CEO at Glaut, discusses how AI-moderated interviews are bridging the gap between qualitative and quantitative research, enabling global insights in hours, and shifting UX research from surveys to natural conversations.

Natan Voitenkov, Co-Founder and CEO of Genway AI, discusses how tools like Genway are expanding the target audience for research insights to include designers, product managers, and broader consumer insights functions.

Basel Fakhoury, Co-Founder and CEO at User Interviews. Basel discusses how User Interviews’ AI-powered platform and integrations enable faster participant recruitment and AI’s potential to democratize research workflows and increase the ROI of user insights.

Ben Hookway, CEO at Relative Insight, shares a comparative linguistics approach that delivers clear, evidence-based metrics that support decision-making by analyzing open-ended NPS responses.

This guide highlights the essential AI research skills for 2025, practical applications of AI, and key considerations to help UX professionals excel in this rapidly evolving field.

Jonathan Fairman, VP of Product at dscout, emphasizes how AI tools integrated into dScout help researchers handle the overwhelming amount of data from diary studies or large research projects efficiently.

Michael Bamberger, Founder at Tetra, explains how AI tools like Tetra are automating insights, leveraging organic data, and enabling faster, more explorative research workflows across an organization – freeing up time for creative human research and amplifying the impact of UX research.

 Kathryn Topp, CEO and Founder at Yabble, discusses how AI tools are impacting UX research and consumer product innovation by accelerating insights, enabling rapid product iteration, and uncovering emerging trends like the convergence of physical and digital experiences.

Jack Bowen, Founder at CoLoop, discusses the future of qualitative research and how Coloop uses AI to elevate research processes without taking over.

Tash Ahmed, co-founder at User Evaluation, discusses how AI tools are enhancing insight generation for UX research and product discovery, significantly reducing analysis time, and addressing trust issues with AI-generated analysis.

Chad Reynolds, CEO at Vurvey, shares how the tool enhances UX research and product development with scalable insights, AI Agents for analysis, and on-demand consumer interactions. 

Arnob Mukherjee, Co-Founder at Olvy, discusses how AI tools like Olvy are allowing product teams to dramatically increase the number of evidence-based decisions they make by analyzing multiple data streams at once.

In our AI vs. Human series, we've discussed in detail how AI tools compare to human research at each phase of a generative qualitative interview study. Read on to explore our key learnings from this research and how AI stands to impact UX research going forward.

A variety of AI tools can be leveraged to create experience maps, from general AI tools that can help with data synthesis and copy to design tools that can put the content into a visual format.  In this post, we share findings from our head-to-head comparison of these tools and human researchers when it comes to creating useful experience maps.

Brilliant tested the limits of both human researchers and AI tools (and combinations of the two) in creating personas. In this post, we continue to share findings from the synthesis phase of our AI vs. Human study, focusing this time on how and when to involve AI in persona creation.

In this post from Brilliant’s head-to-head study comparing the effectiveness of AI tools and human UX researchers throughout the generative research process, we’ll delve into our findings from the synthesis phase, starting with our experience generating key insights from the data in each condition.