Purpose of Review <p>This review critically examines the dual role of Artificial Intelligence (AI) in either mitigating or exacerbating racial health disparities for African American patients, with a specific focus on emergency medicine. It seeks to answer how algorithmic bias emerges, whether race-neutral corrections achieve equity, and what ethical frameworks are needed for responsible deployment.</p> Recent Findings <p>Recent studies demonstrate that AI models trained on biased data perpetuate inequities, such as under-allocating resources to Black patients. Race-neutral algorithm adjustments, while well-intentioned, can produce unintended clinical consequences. Diagnostic imaging and triage tools show differential accuracy across racial subgroups, yet diverse training data and practical ethical oversight remain critically lacking.</p> Summary <p>AI in healthcare presents both promise and peril. Achieving equity requires inclusive data, continuous monitoring, community engagement, and adherence to bioethical principles as reported by Beauchamp and Childress (2019). For emergency physicians, informed skepticism and advocacy for transparent, validated systems are essential to ensure AI advances just care for marginalized populations.</p>