Purpose
Mentorship is crucial for medical students' well-being and career development, as emphasized by Kram’s Mentoring Theory and mandated by the Liaison Committee on Medical Education. However, only a third of students’ report having a mentor, highlighting significant gaps in career advising and well-being support. Technology-driven solutions, including web-based mentorship programs, address barriers like time constraints and accessibility. They offer scalable and flexible opportunities, including enhanced personalization through AI. This study uses Kram’s Mentoring Theory to examine the impact of a 5-month web-based mentorship program, exploring how technology and AI can bridge these gaps.

Methods
This study evaluated the impact of a 5-month structured web-based mentorship program guided by Kram’s Mentoring Theory using a structured codebook. Students were randomized into two groups: one paired with physician mentors and another receiving standard academic advising. AI-powered tools within the program provided personalized content recommendations, session analytics, and progress tracking to enhance the mentoring process.

Results
Feedback was analyzed using a structured codebook based on Kram’s Mentoring Theory, identifying major themes of career development and psychosocial function, with multiple subthemes. Qualitative data provided rich insights into mentors’ and mentees’ experiences, highlighting the benefits of accessible and flexible mentorship interactions enabled by technology. AI-powered tools, such as agenda generators, enhanced mentorship by streamlining preparation through personalized feedback and real-time analytics, compiling mentee information into concise summaries of recommendations, blockers, and top wins, which allowed mentors to efficiently focus on meaningful and personalized interactions.

Conclusions
Qualitative findings highlighted mentorship's role in fostering career development, psychosocial support, and professional growth. Technology played a pivotal role in enhancing mentorship interactions by streamlining mentor preparation and enabling personalized, efficient, and focused sessions. These results highlight the potential for web-based and AI-enhanced mentorship programs to address gaps in traditional mentorship, offering scalable, flexible, and accessible solutions for diverse learners.