Exploring Agent-Assisted Qualitative Analysis

This article investigates how AI agents can assist in qualitative analysis, a process of interpreting unstructured data to find patterns and insights. The author, a PhD graduate, experiments with naive agentic setups for grounded theory, a method that builds answers from data without fixed hypotheses. The post covers background on qualitative analysis, experimental design varying human-in-the-loop levels, findings from coding and categorization tasks, and future research directions. It targets tech-savvy readers interested in AI applications for research workflows, blending programming concepts with data analysis methodologies.