The automation of execution-heavy tasks—such as transcribing interviews or coding open-ended responses—is creating what some respondents call an "expertise drought." By removing the foundational work typically assigned to junior researchers, teams risk losing the apprenticeship process necessary to develop future senior talent. This shift suggests that companies may struggle to cultivate seasoned researchers, only noticing the skill gap once their veteran staff eventually departs.
AI is erasing the apprenticeship rungs in research hiring
Forty-two percent of research and insights professionals report that artificial intelligence has slowed or reduced hiring, according to a study by unitQ. The findings suggest that while technology accelerates data collection, it is disproportionately displacing entry-level roles and the manual tasks traditionally used to train the next generation of experts.
Beyond hiring shifts, the study highlights a growing concern regarding output quality. Forty percent of professionals warned that reliance on AI risks producing "research slop"—shallow, homogenized insights that lack the rigor of human analysis. While AI enables teams to increase volume and speed, it does not inherently guarantee accuracy. Christian Wiklund, CEO of unitQ, argues that the industry must pivot toward providing teams with specialized tools for execution rather than simply eliminating the roles responsible for that work. Success now depends on a researcher’s ability to direct AI and exercise the judgment required to identify when the machine provides confident but incorrect answers.
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