  Generative artificial intelligence (GenAI) offers promising potential for
advancing human-AI collaboration in qualitative research. However, existing
works focused on conventional machine-learning and pattern-based AI systems,
and little is known about how researchers interact with GenAI in qualitative
research. This work delves into researchers' perceptions of their collaboration
with GenAI, specifically ChatGPT. Through a user study involving ten
qualitative researchers, we found ChatGPT to be a valuable collaborator for
thematic analysis, enhancing coding efficiency, aiding initial data
exploration, offering granular quantitative insights, and assisting
comprehension for non-native speakers and non-experts. Yet, concerns about its
trustworthiness and accuracy, reliability and consistency, limited contextual
understanding, and broader acceptance within the research community persist. We
contribute five actionable design recommendations to foster effective human-AI
collaboration. These include incorporating transparent explanatory mechanisms,
enhancing interface and integration capabilities, prioritising contextual
understanding and customisation, embedding human-AI feedback loops and
iterative functionality, and strengthening trust through validation mechanisms.
