This chapter explores the use of AI in data interpretation and discussion, providing a step-by-step recipe with practical, hands-on instructions. We demonstrate the application of AI in interpreting both quantitative and qualitative data through two case studies. We emphasise that human researchers must lead the process, using AI as a tool that requires ongoing guidance and refinement. Although human-generated interpretations offer greater depth, link to context, and engagement with literature and theory, AI enhances the process by increasing efficiency, reducing errors, and offering fresh perspectives through human-AI collaboration.