The global shortage of specialized medical expertise, especially for rare and complex diseases, is a pressing healthcare challenge. Imagine a world where access to expert diagnosis and treatment isn't limited by geography or availability. That's the promise of democratizing medical expertise, and AI could play a crucial role. Researchers explored the potential of AMIE, an experimental AI system designed for medical diagnosis, to bridge this gap in specialized cardiology. Using real-world data from 204 complex cardiology cases at Stanford, they assessed AMIE’s ability to diagnose, triage, and manage patients. Subspecialist cardiologists, blinded to the source, evaluated AMIE’s performance alongside that of general cardiologists. Impressively, AMIE outperformed general cardiologists in five out of ten assessment areas, demonstrating its potential to provide expert-level input. When general cardiologists had access to AMIE's analysis, their own assessments improved significantly in over 60% of the cases. This suggests AI could act as a powerful support tool, guiding generalists towards more accurate diagnoses and management plans, especially in specialized fields. While general cardiologists were more concise, AMIE's thoroughness proved valuable in identifying potential issues often missed. The research highlighted a key difference: general cardiologists' errors stemmed primarily from overlooking crucial information, while AMIE's were more often related to recommending additional, sometimes unnecessary, tests. The potential of AI like AMIE to elevate the capabilities of general cardiologists is clear. By integrating these tools into clinical workflows, we can move closer to a future where specialized medical expertise is readily accessible to all, although real-world validation and responsible implementation are critical next steps.