AI Bias in Healthcare: What Every C-Suite Needs to Know for 2025
This article investigates the significant business risks associated with algorithmic bias in healthcare artificial intelligence (AI) systems. It presents compelling evidence from leading institutions to reveal how AI bias can cause financial, operational, and reputational harm, disproportionately disadvantaging women and minority patients. The article unpacks the root causes of bias—including flawed data, human and institutional blind spots, and opaque algorithms—then outlines a strategic framework, based on University of Chicago research, for robust AI governance and bias mitigation. Ultimately, it argues that customized AI solutions, rather than off-the-shelf products, offer healthcare organizations the control necessary to address these risks, safeguard patients, and protect long-term value.
