Susanne Schmidt-Rauch

How to cannibalize the user research process and why we benefit

Everyone is talking about AI these days. Some are afraid of losing their jobs. Others predict that we will be spared AI for quite a while yet. All euphoria or fear aside, if we want to use the new technologies constructively, we need to know two things: What does it bring to us and how do we need to change?

Let's start with "what it offers." When we started exploring AI solutions to improve ourselves in 2021 with the "evux Lab", we found many early solutions and so-called "signals" that looked quite interesting. That same year, we were able to narrow down the technologies and start an experiment with an AI-generated persona technology vs. a human user researcher. After that, we were able to design the product and launch it by the end of 2021. Since then, we have done several projects where these personas were part of the information process.

In doing so, it seems easier for me as a computer scientist to see the opportunities before being afraid of the technology. But that's not common. If you've ever tried to introduce any technology into a work process where there wasn't any technology before, people aren't particularly appreciative of it at first. And that's where "how do we need to change?" starts. In other projects, user researchers would start working now to understand what the barriers are and how to remove or mitigate them. But what if we introduce technology into the user research process? Big surprise: user researchers respond the same way! You can't introduce technology into a process without changing and informing the new process through user research. So what are the fears directly in the research process, what are the weaknesses, and where do the potentials arise?

I will show you the path we are taking with experimentation and standardization to evaluate AI (and other technologies) for our processes, giving you perspectives on how to successfully use technology in existing processes.