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Qualitative research has entered its AI era—but trust hasn't caught up to adoption. This report breaks down where AI has earned researchers' confidence, where it hasn't, and what closes the gap.
Researchers have already made AI part of the qualitative research workflow. What they haven't done is decide it can be trusted with the work that matters most. This report lays out exactly where that line sits, grounded in a survey of qualitative and mixed methods researchers across academic and commercial settings.
Regular use rises with experience and varies sharply by role and sector—it isn't the newest researchers driving adoption.
Researchers trust AI most where its output is easy to check and least wherever a task demands real interpretation.
Manual verification and independent cross-checking are standing in for rigor most AI tools don't provide.





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