This perspective paper explores our experiences as a doctoral candidate and dissertation chair leveraging and integrating Generative Artificial Intelligence (GenAI) as a secondary research and thought partner in a qualitative instrumental case study dissertation. Our purpose is to share lessons learned and provide strategies, insights, and ethical considerations for researchers in academia and the social sciences seeking to incorporate GenAI into their work responsibly. We developed protocols to ensure the doctoral candidate maintained their role as the primary research instrument, content producer, and analyst while leveraging GenAI as a supportive tool. GenAI assisted with data organization, theme identification, and iterative coding, which enhanced efficiency while preserving the researcher’s critical role in analysis and interpretation. Using domain-specific prompts and structured workflows, we found GenAI could complement traditional research methods by streamlining synthesis and coding processes, validating themes, and deepening insights without compromising rigor or integrity. This paper serves as a practical resource for researchers navigating the evolving landscape of AI-assisted research, offering a framework for using GenAI effectively and ethically in diverse contexts without compromising the integrity of the research process.