Thematic analysis is possibly the most used qualitative method in social sciences. It's also one of the most time-intensive: read, reread, code, compare, revise. A project with 30 interviews can require weeks of analysis work.
How AI-Assisted Thematic Analysis Works
AI doesn't replace the researcher's judgment — it assists it. The process combines computational power for processing large text volumes with the researcher's expert interpretation.
Phase 1: Automated Familiarization
Instead of manually reading all transcripts, AI generates a summary of each interview with main themes mentioned. The researcher can do a first pass of 20 interviews in 2 hours instead of 2 days.
Phase 2: AI-Assisted Initial Coding
AI suggests initial codes based on frequency and co-occurrence of concepts across transcripts. The researcher accepts, modifies, or rejects each suggestion. It's a dialogue, not blind automation.
Phase 3: Pattern Identification
With coded texts, AI can identify which themes frequently co-occur, which idea sequences are common across different participants, and which concepts appear in unexpected ways.
Important methodological limit: AI identifies patterns in the text, but interpreting their meaning remains the researcher's responsibility. Delegate the search; keep the interpretation.