AI for Qualitative Data Analysis: What Works, What Fails, and How to Stay in Control
Many researchers are experimenting with AI tools such as ChatGPT, Claude, Gemini, or NotebookLM. The results can be impressive, but also raise important questions: Can AI be trusted with qualitative data? What happens to confidential material? How do we deal with hallucinations? And how can we make sure that analysis remains grounded in the actual data?
In this live webinar, we will look at how AI can support qualitative data analysis in a responsible and methodologically sound way. We will discuss common concerns around data security, hallucination, traceability, and the limitations of general-purpose AI tools.
You will also see how QInsights was designed specifically for qualitative analysis: not as a one-click replacement for the researcher, but as an AI-supported workspace where findings remain linked to the source material and the researcher stays in control.
The session includes a short conceptual introduction, a practical demonstration, and time for questions.