This paper addresses health equity as a major factor for bridging the gap between medical AI and clinical practice. Addressing and mitigating bias is key for reducing existing health disparities and preventing their exacerbation through AI-technologies. I argue that the gap between artificial and human intelligence is one potential cause of exacerbating health disparities through bias. In turn, bias causes a gap between the possibilities of AI in healthcare and its clinical application. Reconciling human and artificial intelligence through technical bias mitigation, human-centered AI and thick data approaches, and regulations, is necessary to enable equity in an AI-based healthcare setting.