This article discusses the integration of artificial intelligence (AI) into thematic analysis, a widely used qualitative research method. Thematic analysis involves identifying, organizing, and interpreting patterns or themes within qualitative data. The article emphasizes the importance of using AI as a complementary tool rather than a replacement for human analytical skills. While AI can enhance the efficiency and depth of thematic analysis, it is crucial to ensure that the analyst's critical evaluation and interpretive abilities are not overshadowed. The article provides guidance on how to incorporate and document AI tools in each phase of thematic analysis, highlighting the need for careful consideration of the limitations and potential risks associated with AI use. It also outlines the key steps and considerations for conducting thematic analysis with AI, including the importance of transparency, reproducibility, and the ethical use of AI in research. The article concludes by reiterating the importance of maintaining the human element in qualitative research and the need for rigorous evaluation and validation of AI-generated findings.This article discusses the integration of artificial intelligence (AI) into thematic analysis, a widely used qualitative research method. Thematic analysis involves identifying, organizing, and interpreting patterns or themes within qualitative data. The article emphasizes the importance of using AI as a complementary tool rather than a replacement for human analytical skills. While AI can enhance the efficiency and depth of thematic analysis, it is crucial to ensure that the analyst's critical evaluation and interpretive abilities are not overshadowed. The article provides guidance on how to incorporate and document AI tools in each phase of thematic analysis, highlighting the need for careful consideration of the limitations and potential risks associated with AI use. It also outlines the key steps and considerations for conducting thematic analysis with AI, including the importance of transparency, reproducibility, and the ethical use of AI in research. The article concludes by reiterating the importance of maintaining the human element in qualitative research and the need for rigorous evaluation and validation of AI-generated findings.