The field of qualitative research is moving towards increased integration with artificial intelligence (AI) and large language models (LLMs). This development is driven by the potential of AI to automate and augment various aspects of qualitative analysis, such as data coding and theme identification. Researchers are exploring the benefits and limitations of using LLMs in qualitative research, including their ability to reduce coder fatigue and improve inter-rater reliability. However, challenges remain, such as addressing human bias and improving contextual understanding. Noteworthy papers in this area include: Development and Benchmarking of a Blended Human-AI Qualitative Research Assistant, which presents a rigorous benchmarking of an AI-powered qualitative research system. Text Annotation via Inductive Coding: Comparing Human Experts to LLMs in Qualitative Data Analysis, which investigates the performance of LLMs in inductive coding and reveals a peculiar dichotomy in their performance compared to human experts.