UX research is riding a wave of increased popularity, and increased need. With more software products than ever before, and a new normal of hybrid and work-at-home environments, understanding user experience is more important than ever. With the advent of AI being used in the workplace and consumer sectors, the integration between UX research and AI products is increasingly apparent and important to understand. Here are several ways AI is making a mark on the UX research industry.

Good UX research can make AI’s perform better when they get stuck

A huge number of AI products are based on providing customer service or answering questions users might have, like chatbots or siri. One major issue with these products is that they aren’t programmed to handle every possible interaction that can happen; there are certain moments where the AI could get stuck and be unable to provide adequate responses to the user. UX Research can figure out the right conversation flows in the event of the AI not getting all the information right by gathering data from users about instances where the AI got stuck. This research can be passed on to teams who can then create workarounds that prevent the AI from getting stuck in the user. 

UX researchers can make AI more approachable to the average user

AI products are often billed as “cool,” with advanced functionalities that seem like they would go a long way to solving a user’s problems. However, AI products are often designed to complete their task first, with user experience being a secondary goal. UX research can help bridge the gap between building products that don’t just do cool things, but allow users to do these tasks in a way that is conducive to their experiences and needs. Users need products that are approachable with clean interfaces, easily managable outcomes and easy to figure out how they work.

AI tools can help UX researchers find the root of user’s problems ‍

While UX research has a number of ways to help AI products, there are also plenty of products created with the goal of helping UX researchers make their life easier. One example is Weka, a tool with pre-built machine learning algorithms that can help analyze your data more efficiently. This can help streamline the UX research process by reducing the amount of time spent analyzing data. Another tool is Laxis, an AI meeting assistant that automatically transcribes your digital meetings and creates AI generated insights based on your transcript. Laxis allows UX researchers to keep track of user interviews without actually taking notes, making these conversations more informative and easier to conduct.