Role of artificial intelligence in public health

Abstract

Artificial intelligence (AI) is quickly reshaping public health by facilitating faster, more precise and scalable responses. As global burden of infectious and non-communicable diseases grows, AI’s capacity to analyze extensive and varied datasets, recognise patterns, and produce practical insights makes it a valuable asset for enhancing health outcomes worldwide. The current review provides a comprehensive synthesis of AI applications in public health, examining enabling technologies, key benefits, prevailing challenges, and future directions. It aims to guide researchers, practitioners, and policymakers in leveraging AI for equitable and effective public health strategies. We conducted a narrative review of recent literature and case studies, concentrating on AI’s role in disease surveillance, predictive modelling, diagnostics, healthcare operations, and public health communication. The review also explores the integration of AI with mobile health (mHealth), tele-health, cloud computing, Internet of Things (IoT), and blockchain technologies. AI has transformed disease monitoring and early outbreak identification by combining inputs from electronic health records (EHR), social media platforms, environmental monitoring systems, and satellite data. Through machine learning (ML) and natural language processing (NLP), it enables real-time data analysis, predictive modelling, and risk assessment, facilitating timely interventions and optimal use of resources. AI offers transformative potential for public health, improving surveillance, diagnostics, operational efficiency, and access to care. To fully realize these benefits, it is crucial to address technical, ethical, and infrastructural challenges through robust governance, workforce development, and global collaboration. With responsible innovation and inclusive policy, AI can help build more responsive, equitable, and resilient public health systems worldwide.