Purpose: Point-of-care ultrasound (POCUS) enhances integration of anatomy and clinical skills in preclinical medical education but is often limited by faculty availability for hands-on instruction. At Mercer University School of Medicine–Columbus, we piloted an AI-supported POCUS program using real-time formative feedback to promote learner development, self-directed learning, and integration of foundational science with clinical reasoning. Methods: During summer 2025, 20 second-year medical students voluntarily participated in an eight-session AI-guided POCUS program over four weeks. Sessions integrated anatomy review, patient-based clinical cases, and AI-assisted scanning using handheld ultrasound devices with AI overlays providing real-time anatomical labeling and probe guidance, followed by facilitated discussion. Educational outcomes were explored through thematic analysis of student reflections and feedback, supplemented by faculty observations. The study received IRB-exempt status. Results: Thematic analysis identified four recurring themes: iterative skill development through immediate AI-generated feedback, increased confidence and self-directed learning, deeper integration of anatomy with clinical application, and increased faculty capacity for mentorship. Faculty observed less time spent providing routine technical feedback, allowing greater emphasis on individualized coaching, anatomical reasoning, and clinical decision-making. Conclusion: AI-guided ultrasound created a feedback-rich learning environment that supported adaptive learning, reflection, and learner development. By enabling scalable formative feedback, AI complemented faculty mentorship and aligned with growth-oriented educational practices in health professions education, particularly in resource-limited settings.