Any field where you ask a human to repeatedly collect, code, and sort data, a machine will eventually do it faster. Traditional user research practices; manual transcription, painstaking thematic analysis, repetitive usability testing are textbook examples. So it’s not surprising that AI is beginning to take on these tasks.
The more interesting shift is not the automation of the routine, but the expansion of the researcher’s role. My belief is that all human-centred design work will have an AI copilot. That means user researchers won’t become less essential, but their day-to-day work will evolve from spending hours on manual analysis to orchestrating intelligent agents, interpreting insights, and shaping design decisions.
In this early period, many teams are still figuring out how to embed AI into research workflows. Should it be used for recruitment? For notetaking? For clustering findings? For now, integration is uneven. But I remain convinced that the demand for people who think critically about human behaviour will only grow. Every design decision will soon be informed by AI-assisted research. That makes skilled researchers more valuable, not less, provided we design the right pathways.
This isn’t the same as user researchers disappearing. Think about survey research when online platforms first emerged. Many feared the craft would be diluted. Instead, the role expanded; researchers moved from paper surveys to agile feedback loops, data dashboards, and real-time decision support. AI will reshape user research in a similar way.
In the meantime, the uncertainty can feel daunting, especially for those just entering the profession. But it also presents a unique opportunity for an AI-native generation of researchers. If you are starting your career today, you can grow up working with AI copilots, learning how to balance automation with empathy, and helping organisations discover how to integrate AI into the design of services and products.
