Breaking Up with NVivo: AI Delivers Faster, Deeper, and Better Qualitative Insights

This study empirically compares the performance of AI-assisted qualitative analysis software (AILYZE) against traditional computer-assisted qualitative data analysis software (NVivo) in thematic analysis tasks. Ten graduate students with prior NVivo qualitative research training were randomly assigned to analyze interview transcripts about childhood flu vaccination using either AILYZE (n=5) or NVivo (n=5). Participants were blind to the study's comparative nature and were tasked with identifying themes and writing a report. Participants submitted time logs detailing how long they took to conduct the analysis. A structured blind pairwise comparison process was conducted where five independent expert qualitative researchers each conducted five evaluations (25 total comparisons), in order to assess the quality of the reports written. Results demonstrate that AILYZE-generated analyses were 73% faster (mean 7.38 vs. 27.71 hours, t=-11.45, p<0.0001) and received higher quality rankings in 76% of pairwise comparisons (19 out of 25, p=0.0073). These findings suggest that AI-assisted qualitative analysis tools may significantly enhance research efficiency while improving analytical comprehensiveness and depth, with important implications for qualitative methodology across disciplines.