Artificial intelligence (AI) has rapidly become integrated into medical student learning, yet many receive little guidance on how to use these tools effectively, ethically, and in ways that promote genuine learning. Without structured guidance, students may develop patterns of passive AI use that risk reducing active engagement with course material and fostering over reliance on technology. To promote responsible AI integration and support the development of adaptive, self-regulated learners, we developed a near-peer educational resource introducing effective and reflective AI use during the transition to medical school. Drawing on experiences from second-year medical students and survey findings demonstrating widespread AI utilization among peers (n = 42), we collaborated with faculty to develop a pre-matriculation educational module integrated within our institution's medical school readiness community in Canvas. The resource introduced students to commonly used AI platforms, prioritizing those provided by our institution and behind institutional firewalls, while emphasizing strengths, limitations, and appropriate use cases. Near-peer demonstrations highlighted active learning strategies such as generating practice questions, organizing course content, creating study resources, identifying knowledge gaps, and integrating AI within spaced-repetition tools. Emphasis was placed on critical evaluation of AI-generated content, source verification, academic integrity, and avoidance of passive learning behaviors. Utilization metrics and learner feedback are being collected to inform ongoing revision and expansion. Preliminary engagement data demonstrate learner interest in AI-focused guidance during the transition into medical school. Participants reported valuing practical demonstrations, curriculum-specific examples, and explicit discussion of AI limitations. Future work may assess changes in learner confidence, study behaviors, and perceptions of responsible AI use.