The COVID-19 pandemic has posed unprecedented challenges to global public health, economy, and society. Artificial Intelligence (AI) technologies have emerged as promising tools to address these challenges. This review discusses the innovative applications of AI in managing the pandemic, focusing on prediction, detection, control, and drug discovery. AI-based predictive analytics models use clinical, epidemiological, and omics data to forecast disease spread and patient outcomes. Deep neural networks enable rapid diagnosis through medical imaging. Intelligent systems support risk assessment, decision-making, and social sensing, improving epidemic control and public health policies. High-throughput virtual screening accelerates the identification of therapeutic drug candidates and opportunities for drug repurposing. Despite the promising results, barriers such as model generalization, data quality, infrastructure readiness, and ethical risks must be addressed. Multidisciplinary collaboration is essential for developing robust, responsible, and human-centered AI solutions to combat the pandemic and future public health emergencies.The COVID-19 pandemic has posed unprecedented challenges to global public health, economy, and society. Artificial Intelligence (AI) technologies have emerged as promising tools to address these challenges. This review discusses the innovative applications of AI in managing the pandemic, focusing on prediction, detection, control, and drug discovery. AI-based predictive analytics models use clinical, epidemiological, and omics data to forecast disease spread and patient outcomes. Deep neural networks enable rapid diagnosis through medical imaging. Intelligent systems support risk assessment, decision-making, and social sensing, improving epidemic control and public health policies. High-throughput virtual screening accelerates the identification of therapeutic drug candidates and opportunities for drug repurposing. Despite the promising results, barriers such as model generalization, data quality, infrastructure readiness, and ethical risks must be addressed. Multidisciplinary collaboration is essential for developing robust, responsible, and human-centered AI solutions to combat the pandemic and future public health emergencies.