People facing a problem tend to choose the most obvious solution, and with AI, these solutions are now generated even faster and appear perfectly crafted. It’s much faster to use AI to gather data and create a persona than to laboriously discuss it as a team. You don’t even need to have “UX” in your job title to do this. We need more people who question this new pace, don’t shy away from experiments, research, and verify whether the assumptions are correct. Where does the learning process fit into efficient processes?
As teachers, we ask ourselves: What do our students need to learn, and how do people learn these days? I mostly mentor students in the “Digital Innovation and Business” bachelor’s program. This program covers many topics and skills typically associated with a UX professional, such as user research, problem-solving skills, some design, creativity, data analytics, project management, communication skills, and so on. Nevertheless, we don’t know what kinds of roles our students will end up in. I sometimes tell them that this program equips them with the approaches tools they need to create their own future jobs.