Purpose
With the rise of generative AI tools in medical education, questions around academic integrity are becoming more complex. Both educators and students are learning together, sometimes cautiously, sometimes creatively, how to use these tools ethically. This study explored how students and faculty co-navigate concerns, expectations, and learning practices related to integrity in the context of AI assisted education.

Methods
This qualitative study involved reflective dialogues with fifteen educators and twenty four medical students who had experience using generative AI tools in academic settings. Participants took part in paired and group conversations where they reflected on real situations involving assignments, feedback, and classroom discussions. These shared stories were analyzed thematically, focusing on how integrity was discussed, misunderstood, negotiated, or redefined during the learning process.

Results
The conversations revealed that academic integrity is no longer a fixed concept, but something evolving with context and conversation. First theme, walking the line together, described how students and educators often figured out boundaries in real time, balancing curiosity with caution. Second theme, more than rules, reflected how meaningful discussions about intent, responsibility, and learning goals helped shift the focus from punishment to growth. Many participants valued transparency and open dialogue, especially when policies were unclear or changing. Still, some felt uncertain or hesitant to ask questions, worried about being misunderstood.

Conclusion
As generative AI becomes part of the learning space, integrity must be shaped not just by rules, but by relationships. When students and educators engage in open, respectful conversations about AI use, they build a shared understanding of what ethical learning looks like. Supporting this co-navigation requires clarity, empathy, and space for reflective dialogue.