AI impacting research hiring, early-career roles most affected
News provided byunitQ · 2 min read
AI is transforming research hiring, according to a recent study by unitQ, which found that 42% of research, design, and insights professionals have seen AI reduce or slow down research hiring. Early-career researchers and roles involving heavy execution are among the most affected.
In a survey of 160 professionals, 28% indicated that junior researchers are the first to feel the impact of AI, with more than half pointing to hands-on, execution-heavy work as the first to be automated. This shift is not about outright replacement but rather about automation of the more routine tasks that early-career researchers often handle.
“AI is quietly removing the rungs of the ladder researchers climb,” said Christian Wiklund, Co-founder and CEO of unitQ. “This is avoidable only if teams equip themselves with the right tools to hand off executional work, instead of simply eliminating roles.”
The study highlights a potential quality concern. While AI can increase the volume of research, it does not guarantee deeper insights. Among the professionals surveyed, 40% warned of deskilling or shallow, homogenized output, research that may appear confident but is often incorrect.
UnitQ Research, the AI platform used in the study, runs adaptive AI interviews and surveys, synthesizing themes, sentiment, and quotes in real-time. This tool aims to bridge the gap between the depth of qualitative interviews and the broad reach of surveys, providing teams with a deeper understanding of their data at a faster pace.
Wiklund emphasized that the value of AI in research lies in its ability to direct and correct the technology. “The judgment that researchers bring to the table is crucial,” he said. “Those who can effectively manage and oversee AI tools will thrive in this new landscape.”
Currently, unitQ Research is available with a free 30-day trial and is trusted by companies such as PayPal, Adobe, Pinterest, and Intuit. The platform unifies customer signals and connects them to critical business metrics, helping teams prioritize their efforts before key performance indicators (KPIs) shift.
As AI continues to reshape the research landscape, the challenge for teams lies in leveraging the technology while preserving the unique skills and insights of human researchers.