Artificial intelligence is transforming disease surveillance, but governance is failing to keep pace

Abstract

Artificial intelligence (AI) is transforming disease surveillance by enabling early outbreak detection, predictive modeling, and real-time analysis of diverse health data sources. These advances can strengthen epidemic preparedness and improve public health decision-making. However, AI adoption has progressed faster than the development of effective governance frameworks, creating challenges related to algorithmic bias, transparency, privacy, cybersecurity, accountability, and global equity. Low- and middle-income countries face additional barriers due to limited digital infrastructure and technical capacity. This policy brief highlights the urgent need for responsible AI governance through international standards, explainable algorithms, independent validation, strong data protection, and inclusive stakeholder engagement. Ensuring ethical and equitable AI implementation is essential to maximize its potential for improving disease surveillance and global health security.